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            "description": "The data in these Appendices to the Global Anthropogenic Emissions of Non-CO2 Greenhouse Gases (1990-2020) report provide historical and projected estimates of emissions from over 90 countries and 8 regions for all major non-CO2 greenhouse gas emission sources. The gases included in this data set are methane (CH4), nitrous oxide (N2O), and the high global warming potential (high GWP) gases (hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6)). See the full report at https://www.epa.gov/climatechange/economics/international.html.",
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            "description": "The Clean Air Markets Program Data (CAMPD) application, accessible at https://campd.epa.gov/, allows users to view Clean Air Markets data through the Custom Data Download Tool and Bulk Data Files. These tools are driven by APIs documented in the CAM API Portal https://www.epa.gov/airmarkets/cam-api-portal, which is accessible through CAMPD. The Custom Data Download Tool and APIs allow users to create custom queries to explore CAMD\u2019s database through different data types: emissions, allowances, compliance, and facility attributes. Prepackaged Bulk Data Files are also available for commonly requested datasets and larger data downloads. EPA's Clean Air Markets Division (CAMD) manages several market-based regulatory programs designed to improve air quality and ecosystems. The most well-known of these programs are EPA's Acid Rain Program and the Cross-State Air Pollution Rule (CSAPR) Programs, which reduce emissions of sulfur dioxide (SO2) and nitrogen oxides (NOx)-compounds that adversely affect air quality, the environment, and public health.",
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            "description": "The CASTNET Download Data module allows users to select, view, and download CASTNET data (Raw, Aggregate, Modeled & Factual Data) based on user selections.\n  \nCASTNET sites are located in or near rural areas and sensitive ecosystems collecting data on ambient levels of pollutants where urban influences are minimal. CASTNET, which was initiated in 1986, is able to provide data needed to assess and report on geographic patterns and long-term temporal trends in ambient air pollution and dry atmospheric deposition. CASTNET can also be used to track changes in measurements associated with climate change (such as temperature and precipitation).",
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                "environment",
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                "united states",
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            "title": "Clean Air Status and Trends Network (CASTNET) Download Data Module",
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            "title": "Clean Air Status and Trends Network (CASTNET): Ozone",
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            "geo": "No",
            "holdren": "No",
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            "description": "This site includes  the global warming potential (GWP) of ozone depleting substance substitutes, their atmospheric lifetime, and uses.",
            "keyword": [
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                "chemicals",
                "substances",
                "pesticides",
                "human health",
                "health risks",
                "toxicity",
                "environment",
                "environment",
                "united states",
                "health"
            ],
            "title": "Global Warming Potentials (GWP) of ODS Substitutes",
            "issued": "2014-01-01",
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            "programCode": [
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            "contactPoint": {
                "hasEmail": "mailto:Maranion.Bella@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Bella Maranion, U.S. EPA Office of Air and Radiation (OAR) - Office of Clean Air Programs (OCAP)"
            },
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            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EPA Office of Air and Radiation, Office of Atmospheric Programs",
            "sourcefile": "https://edg.epa.gov/data/public/OAR/OAP/METADATA/OAR-OAP.JSON"
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                "name": "U.S. EPA Office of Air and Radiation (OAR) - Office of Atmospheric Programs (OAP)"
            },
            "accessLevel": "restricted public",
            "description": "The ENERGY STAR Partner Directory provides a list of all organizations that have partnered with ENERGY STAR.  This includes product manufacturers, retailers, homebuilders, and commercial building owners and operators, amongh others.",
            "keyword": [
                "epa",
                "oar",
                "oap",
                "istar",
                "integrated strategic tracking and recruiting database",
                "energy star",
                "clean air act",
                "office of atmospheric programs",
                "environmental protection agency",
                "cppd",
                "climate change",
                "caps",
                "environment",
                "energy efficiency",
                "united states",
                "environment"
            ],
            "title": "ENERGY STAR Partner Directory",
            "issued": "2014-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
                "020:00"
            ],
            "references": [
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            "description": "AirCompare contains air quality information that allows a user to compare conditions in different localities over time and compare conditions in the same location at different times of the year.",
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            "description": "TThis page contains large files of data intended for use by people who understand the EPA ambient air quality monitoring program and data. Some contain data summarized on an annual basis (annual summary files), some contain data summarized on a daily basis (daily summary), and some contain raw data (sample data as reported). These are the standard time aggregations EPA calculates and stores (we do not have monthly data). All but the annual summary have data files grouped by parameter: Criteria Gases, Particulates, Meteorological, Toxics, Ozone Precursors, and Lead Blanks (Blanks are empty cannisters that are measured for speciation quality assurance reasons)",
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            "description": "Air Trends provides geographic trend information for specific air pollutants. There are links to two types of summaries provided on this page - air quality trends and air quality design values. The air quality trends summaries are intended to reflect actual air quality and therefore include concentrations that may have been impacted by episodic events like wildfires and dust storms.  Air Quality Design Values are used to designate and classify nonattainment areas and intended to reflect air quality that is not impacted by exceptional events.",
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            "title": "National Air Quality: Status and Trends of Key Air Pollutants",
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            "description": "Ambient ozone concentrations for 2007 from the national ambient air quality monitoring networks stored in the Air Quality System (AQS).",
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            "description": "Quality Data Asset includes all current and historical data on the quality of water with regard to the presence of water pollutants of all kinds regulated by the Clean Water Act. Under the new Interagency Agreement with the Department of Energy (DOE), the Radiation & Indoor Environments National Laboratory (R&IE), Office of Radiation and Indoor Air (ORIA), EPA, located in Las Vegas, NV, conducts a Long-Term Hydrological Monitoring Program (LTHMP) providing laboratory sampling/analysis and Quality Assurance and Control to measure radioactivity concentrations in the water sources near the sites of former underground nuclear explosions. The results of the LTHMP provide assurance that radioactive material from the tests have not migrated into water supplies.",
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                "name": "U.S. EPA Office of Air and Radiation (OAR) - Office of Transportation and Air Quality (OTAQ)"
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            "description": "This asset provides identification data on renewable fuel producers, importers, laboratories, and facilities.",
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            "title": "Request Tracker Mailbox. Fuels Program Registration",
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                "greenhouse gases",
                "ghg",
                "clean air act",
                "energy policy and conservation act",
                "energy independent security act",
                "office of air and radiation",
                "office of transportation and air quality",
                "environmental protection agency",
                "climate change",
                "environment",
                "environment",
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                "environment"
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            "title": "Fuel Economy Label and CAFE Data Inventory",
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        },
        {
            "publisher": {
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                "name": "U.S. EPA Office of Air and Radiation (OAR) - Office of Transportation and Air Quality (OTAQ)"
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            "accessLevel": "public",
            "description": "The Engine and Vehicle Compliance Certification and Fuel Economy Inventory contains measured emissions and fuel economy compliance information for all types of vehicles (mobile sources of air pollution) excluding snowmobile, marine (diesel), and heavy duty engines whichsummary data is updated on an annual basis. Data is collected by EPA to certify compliance with the applicable fuel economy provisions of the Clean Air Act, Energy Policy and Conservation Act (EPCA) and the Energy Independent Security Act (EISA) of 2007.",
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            "title": "Mobile Source Emissions Regulatory Compliance Data",
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        },
        {
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            "accessLevel": "public",
            "description": "The EV-GHG Mobile Source Data asset contains measured mobile source GHG emissions summary compliance information on light-duty vehicles, by model, for certification as required by the 1990 Amendments to the Clean Air Act, and as driven by the 2010 Presidential Memorandum Regarding Fuel Efficiency and the 2005 Supreme Court ruling in Massachusetts v. EPA that supported the regulation of CO2 as a pollutant. Manufacturers submit data on an annual basis, or as needed to document vehicle model changes. This asset will be expanded to include medium and heavy duty vehicles in the future.The EPA performs targeted GHG emissions tests on approximately 15% of vehicles submitted for certification. Confirmatory data on vehicles is associated with its corresponding submission data to verify the accuracy of manufacturer submissions beyond standard business rules.Submitted data comes in XML format or as documents, with the majority of submissions sent in XML, and includes descriptive information on the vehicle itself, emissions information, and the manufacturer's testing approach. This data may contain proprietary information (CBI) such as information on estimated sales or other data elements indicated by the submitter as confidential. CBI data is not publically available; however, CBI data can accessed within EPA under the restrictions of the Office of Transportation and Air Quality (OTAQ) CBI policy [RCS Link]. Pollutants data includes CO2, CH4, N2O. Datasets are divided by vehicle/engine model and/or year with corresponding emission, test, and certification data. Data assets are stored in EPA's Verify system.Coverage began in 2011, with summary light duty data available to the public on request. Raw data is only available to select EPA employees.EV-GHG Mobile Source Data submission documents with metadata, certificate and summary decision information is stored in Verify after it has been quality assured. Where summary data appears inaccurate, OTAQ returns the entries for review to their originator.",
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            "title": "EV-GHG Mobile Source",
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        },
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                "name": "U.S. EPA Office of Air and Radiation (OAR) - Office of Transportation and Air Quality (OTAQ)"
            },
            "accessLevel": "public",
            "description": "The Engine and Vehicle Compliance Certification and Fuel Economy Inventory contains measured emissions and fuel economy compliance information for light duty vehicles. Data is collected by EPA to certify compliance with the applicable fuel economy provisions of the Energy Policy and Conservation Act (EPCA) and The Energy Independent Security Act of 2007",
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            "title": "Fuel Economy Label and CAFE Data",
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                "name": "U.S. EPA Office of Air and Radiation (OAR) - Office of Transportation and Air Quality (OTAQ)"
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            "accessLevel": "public",
            "description": "This asset includes compliance data (registrations and reports), including reports related to reformulated gasoline and conventional gasoline (anti-dumping), gasoline sulfur, mobile source air toxics (including gasoline benzene), sulfur content of on-road and non-road diesel fuel, and renewable fuels under 40 CFR Part 80; and includes registration and compositional information related to fuels and fuel additives under 40 CFR Part 79.",
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            "title": "Fuels Reporting System Data",
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            "@type": "dcat:Dataset",
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            "description": "The Mobile Source Emissions Regulatory Compliance Data Inventory data asset contains measured summary compliance information on light-duty, heavy-duty, and non-road engine manufacturers by model, as well as fee payment data required by Title II of the 1990 Amendments to the Clean Air Act, to certify engines for sale in the U.S. and collect compliance certification fees. Data submitted by manufacturers falls into 12 industries: Heavy Duty Compression Ignition, Marine Spark Ignition, Heavy Duty Spark Ignition, Marine Compression Ignition, Snowmobile, Motorcycle & ATV, Non-Road Compression Ignition, Non-Road Small Spark Ignition, Light-Duty, Evaporative Components, Non-Road Large Spark Ignition, and Locomotive. Title II also requires the collection of fees from manufacturers submitting for compliance certification. Manufacturers submit data on an annual basis, to document engine model changes for certification. Manufacturers also submit compliance information on already certified in-use vehicles randomly selected by the EPA (1) year into their life and (4) years into their life to ensure that emissions systems continue to function appropriately over time.The EPA performs targeted confirmatory tests on approximately 15% of vehicles submitted for certification. Confirmatory data on engines is associated with its corresponding submission data to verify the accuracy of manufacturer submission beyond standard business rules.Section 209 of the 1990 Amendments to the Clean Air Act grants the State of California the authority to set its own standards and perform its own compliance certification through the California Air Resources Board (CARB). Currently manufacturers submit compliance information separately to both the EPA and CARB. Currently, data harmonization occurs between EPA data and CARB data only for Motorcycle & ATV submissions.Submitted data comes in XML format or as documents, with the majority of submissions being sent in XML. Data includes descriptive information on the engine itself, as well as on manufacturer testing methods and results. Submissions may include information (CBI) such as information on estimated sales, new technologies, catalysts and calibration, or other data elements indicated by the submitter as confidential. CBI data is not publically available, but it is available within EPA under the restrictions of the Office of Transportation and Air Quality (OTAQ) CBI policy [RCS Link]. Pollution emission data covers a range of Criteria Air Pollutants (CAPs) including carbon monoxide, hydrocarbons, nitrogen oxides, and particulate matter. Datasets are segmented by vehicle/engine model and year, with corresponding emission, test, and certification data. Data assets are primarily stored in EPA's Verify system. Data collected from the Heavy Duty Compression Ignition, Marine Spark Ignition, Heavy Duty Spark Ignition, Marine Compression Ignition, and Snowmobile industries, however, are currently stored in legacy systems the will be migrated to Verify in the future.Coverage began in 1979, with early records being primarily paper documents that did not go through the same level of validation as the digital submissions that began in 2005.Mobile Source Emissions Compliance documents with metadata, certificate and summary decision information is made available to the public through EPA.gov via the OTAQ Document Index System (http://iaspub.epa.gov/otaqpub).",
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            "title": "Mobile Source Emissions Regulatory Compliance Data Inventory",
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            "geo": "No",
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            "description": "SmartWay helps companies benchmark their freight performance and improve fuel efficiency. This asset contains data collected by EPA for the program to calculate fuel efficiency metrics, fuel savings, and criteria pollutants (NOx & PM) emission rates associated with freight transportation operations.",
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            "title": "Smartway Transport Partnership Data",
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        {
            "title": "The EPA Automotive Trends Report: Greenhouse Gas Emissions, Fuel Economy, and Technology since 1975",
            "description": "This annual report is part of the U.S. Environmental Protection Agency's (EPA) commitment to provide the public with information about new light-duty vehicle greenhouse gas (GHG) emissions, fuel economy, technology data, and auto manufacturers' performance in meeting the agency's GHG emissions standards. EPA has collected data on every new light-duty vehicle model sold in the United States since 1975, either from testing performed by EPA at the National Vehicle and Fuel Emissions Laboratory in Ann Arbor, Michigan, or directly from manufacturers using official EPA test procedures. These data are collected to support several important national programs, including EPA criteria pollutant and GHG standards, the U.S. Department of Transportation's National Highway Traffic Safety Administration (NHTSA) Corporate Average Fuel Economy (CAFE) standards, and vehicle Fuel Economy and Environment labels. The downloadable data are available in the report PDF or spreadsheet (XLS) formats.",
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                "fn": "Aaron Hula",
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            "modified": "2019-03-01",
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            "programCode": [
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            "geo": "No",
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            "accessLevel": "public",
            "description": "Provide public access using keywords to find technical and scientific research information contained in EPA Publications.",
            "keyword": [
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            "distribution": [
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                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "219137d0-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "FAIN",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The Federal Award Identification Number (FAIN) is the unique ID within the Federal agency for each (non-aggregate) financial assistance award.",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Award Balances: ID by TAS- Program Activity-Object Class-\nAward-Direct Reimbursable"
            ],
            "modified": "2020-08-05",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21913a3c-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "URI",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "Unique Record Identifier. An agency defined identifier that (when provided) is unique for every reported action.",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Award Balances: ID by TAS- Program Activity-Object Class-\nAward-Direct Reimbursable"
            ],
            "modified": "2020-08-05",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21913c8a-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Program Activity Code",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Section 200 of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below. \n\nCode of a specific activity or project as listed in the program and financing schedules of the annual budget of the United States Government.  ",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Award Balances: ID by TAS- Program Activity-Object Class-\nAward-Direct Reimbursable"
            ],
            "modified": "2020-08-05",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21913f14-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Program Activity Name",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Section 200 of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below. \n\nName of a specific activity or project as listed in the program and financing schedules of the annual budget of the United States Government.  ",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Award Balances: ID by TAS- Program Activity-Object Class-\nAward-Direct Reimbursable"
            ],
            "modified": "2020-08-05",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21914518-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Object Class",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Section 83 of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below.\n\nCategories in a classification system that presents obligations by the items or services purchased by the Federal Government.",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Award Balances: ID by TAS- Program Activity-Object Class-\nAward-Direct Reimbursable"
            ],
            "modified": "2020-08-05",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21914784-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "By Direct Reimbursable Funding Source",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "Holds an attribute flag which specifies that the funding source of the associated data value is either a Direct or Reimbursable Funding Source.",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Award Balances: ID by TAS- Program Activity-Object Class-\nAward-Direct Reimbursable"
            ],
            "modified": "2020-08-05",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "219149e6-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Transaction Obligated Amount",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Section 20 of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below. \n\nObligation means a binding agreement that will result in outlays, immediately or in the future. Budgetary resources must be available before obligations can be incurred legally.",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Award Balances (by TAS-Program Activity-\nObject Class-award-Direct Reimbursable): Transaction Obligated Amount"
            ],
            "modified": "2020-08-05",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21914c34-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Obligations Incurred Total By Award CPE",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Appendix F of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below. \n\nFor unexpired accounts:\nAmount of obligations incurred from the beginning of the current fiscal year to the end of the reporting period, net of refunds received that pertain to obligations incurred in the current year. Include upward adjustments of prior obligations. \n\nFor expired accounts:\nAmount of upward adjustments of obligations previously incurred. Upward adjustments are limited by the amount available for adjustments. No new obligations may be incurred against expired or canceled accounts.",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Award Balances (by TAS-Program Activity-\nObject Class-award-Direct Reimbursable): Obligations Incurred Total by Award"
            ],
            "modified": "2020-08-05",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21914e82-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Obligations Undelivered Orders Unpaid Total CPE",
            "spatial": "USA",
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                    "@type": "dcat:Distribution",
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                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
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                    "@type": "dcat:Distribution",
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                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
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                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21919dce-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
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            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "USSGL487100 Downward Adjustments Of Prior Year Unpaid Undelivered Orders Obligations Recoveries CPE",
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            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The amount of recoveries during the current fiscal year resulting from downward adjustments to obligations originally recorded in a prior fiscal year in USSGL account 480100, \"Undelivered Orders - Obligations, Unpaid.\" (Per USSGL TFM Part 2, Section II, Accounts and Definitions.)",
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            },
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            ],
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                    "@type": "dcat:Distribution",
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                    "description": "EPA File A submission to comply with the DATA Act.",
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            ],
            "identifier": "2191a03a-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
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            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
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            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "USSGL497100 Downward Adjustments Of Prior Year Unpaid Delivered Orders Obligations Recoveries CPE",
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            "description": "The amount of recoveries that were originally recorded in a prior fiscal year during the fiscal year resulting from downward adjustments to USSGL account 490100, \"Delivered Orders - Obligations, Unpaid.\" (Per USSGL TFM Part 2, Section II, Accounts and Definitions.)",
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                "hasEmail": "mailto:webb.brian@epa.gov",
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            "publisher": {
                "@type": "org:Organization",
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            },
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            ],
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            ],
            "modified": "2020-08-05",
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                    "@type": "dcat:Distribution",
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                    "description": "EPA File A submission to comply with the DATA Act.",
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                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "2191a2d8-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
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            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "USSGL487200 Downward Adjustments Of Prior Year  Prepaid Advanced Undelivered Orders Obligations Refunds Collected CPE",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The amount of cash refunds during the current fiscal year resulting from downward adjustments to obligations that were originally recorded in a prior fiscal year in USSGL account 480200, \"Undelivered Orders - Obligations, Prepaid/Advanced.\"  (Per USSGL TFM Part 2, Section II, Accounts and Definitions.)",
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                "020:00"
            ],
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                "@type": "org:Organization",
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            },
            "language": [
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            ],
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                "Award Balances (by TAS-Program Activity-\nObject Class-award-Direct Reimbursable): Deobligations Recoveries Refunds"
            ],
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                    "accessURL": "https://api.usaspending.gov",
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                    "@type": "dcat:Distribution",
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                    "@type": "dcat:Distribution",
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                },
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                    "description": "EPA File A submission to comply with the DATA Act.",
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                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "2191a95e-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
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            "title": "USSGL497200 Downward Adjustments Of Prior Year Paid Delivered Orders Obligations Refunds Collected CPE",
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            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The amount of cash refunds during the fiscal year resulting from downward adjustments to USSGL account 490200, \"Delivered Orders - Obligations, Paid,\" that were originally recorded in a prior fiscal year. (Per USSGL TFM Part 2, Section II, Accounts and Definitions.)",
            "programCode": [
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            ],
            "bureauCode": [
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            ],
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            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Award Balances (by TAS-Program Activity-\nObject Class-award-Direct Reimbursable): Deobligations Recoveries Refunds"
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            "dataQuality": true,
            "distribution": [
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                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
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                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
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                    "@type": "dcat:Distribution",
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                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
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                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "2191abca-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Obligations Incurred By Program Object Class CPE ",
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            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Appendix F of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below. \n\nFor unexpired accounts:\nAmount of obligations incurred from the beginning of the current fiscal year to the end of the reporting period, net of refunds received that pertain to obligations incurred in the current year. Include upward adjustments of prior obligations. \n\nFor expired accounts:\nAmount of upward adjustments of obligations previously incurred. Upward adjustments are limited by the amount available for adjustments. No new obligations may be incurred against expired or canceled accounts.",
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            ],
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            ],
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            },
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            "publisher": {
                "@type": "org:Organization",
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            },
            "language": [
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            ],
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            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
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                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
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                {
                    "description": "EPA File A submission to comply with the DATA Act.",
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                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "2191d2b2-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Obligations Undelivered Orders Unpaid Total FYB",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Section 20 of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below. \n\nA legally binding agreement that will result in outlays, immediately or in the future.",
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                "020:028"
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            ],
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            },
            "language": [
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            ],
            "keyword": [
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                "Program Object Class"
            ],
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            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
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                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
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                },
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                    "description": "EPA File A submission to comply with the DATA Act.",
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                }
            ],
            "identifier": "2191d82a-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "USSGL480100 Undelivered Orders Obligations Unpaid CPE",
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            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The amount of goods and/or services ordered, which have not been actually or constructively received and for which amounts have not been prepaid or advanced. This includes amounts specified in other contracts or agreements such as grants, program subsidies, undisbursed loans and claims, and similar events for which an advance or prepayment has not occurred. This account does not close at yearend. (Per USSGL TFM Part 2, Section II, Accounts and Definitions.) ",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
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                "@type": "vcard:Contact",
                "fn": "Brian Webb"
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                "@type": "org:Organization",
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            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Obligations",
                "Program Object Class"
            ],
            "modified": "2020-08-05",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
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                    "@type": "dcat:Distribution",
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                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
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                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
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                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "2191da78-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "USSGL490100 Delivered Orders Obligations Unpaid FYB",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The amount accrued or due for: (1) services performed by employees, contractors, vendors, carriers, grantees, lessors, and other government funds; (2) goods and tangible property received; and (3) programs for which no current service performance is required such as annuities, insurance claims, benefit payments, loans, etc. (Per USSGL TFM Part 2, Section II, Accounts and Definitions.) This account does not close at year-end.  (Per USSGL TFM Part 2, Section II, Accounts and Definitions.)",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
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                "@type": "vcard:Contact",
                "fn": "Brian Webb"
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            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Obligations",
                "Program Object Class"
            ],
            "modified": "2020-08-05",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "2191f01c-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Gross Outlay Amount By Program Object Class CPE",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Section 20 of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below.\n\nPayments made to liquidate an obligation (other than the repayment of debt principal or other disbursements that are \u201cmeans of financing\u201d transactions). Outlays generally are equal to cash disbursements but also are recorded for cash-equivalent transactions, such as the issuance of debentures to pay insurance claims, and in a few cases are recorded on an accrual basis such as interest on public issues of the public debt. Outlays are the measure of Government spending. \n\n",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Obligations",
                "Program Object Class"
            ],
            "modified": "2020-08-05",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "2191f756-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Gross Outlay Amount By Program Object Class FYB",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Section 20 of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below.\n\nPayments made to liquidate an obligation (other than the repayment of debt principal or other disbursements that are \u201cmeans of financing\u201d transactions). Outlays generally are equal to cash disbursements but also are recorded for cash-equivalent transactions, such as the issuance of debentures to pay insurance claims, and in a few cases are recorded on an accrual basis such as interest on public issues of the public debt. Outlays are the measure of Government spending. \n\n",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Obligations",
                "Program Object Class"
            ],
            "modified": "2020-08-05",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "2191fe04-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Deobligations Recoveries Refunds Of Prior Year By Program Object Class CPE",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The amount of downward adjustments to obligations and outlays incurred resulting from deobligations, recoveries, or refunds collected, at the TAS / Program Activity / Object Class level. The adjustments are to the obligations and outlays which were made in a prior year.",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Deobligations",
                "Recoveries",
                "Refunds"
            ],
            "modified": "2020-08-05",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "219228fc-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-14",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "USSGL487200 Downward Adjustments Of Prior Year Prepaid Advanced Undelivered Orders Obligations Refunds Collected CPE",
            "spatial": "USA",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The amount of cash refunds during the current fiscal year resulting from downward adjustments to obligations that were originally recorded in a prior fiscal year in USSGL account 480200, \"Undelivered Orders - Obligations, Prepaid/Advanced.\"  (Per USSGL TFM Part 2, Section II, Accounts and Definitions.)",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Deobligations",
                "Recoveries",
                "Refunds"
            ],
            "modified": "2020-08-05",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21923b8a-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-21",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Total Budgetary Resources CPE",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "Budgetary resources mean amounts available to incur obligations in a given year. Budgetary resources consist of new budget authority and unobligated balances of budget authority provided in previous years.",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "budgetary resources",
                "budgetary reporting",
                "current period financial reporting"
            ],
            "modified": "2018-07-31",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21925912-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-22",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Budget Authority Appropriated Amount_CPE",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Section 20 of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below.\n\nAppropriation means a provision of law (not necessarily in an appropriations act) authorizing the expenditure of funds for a given purpose. Usually, but not always, an appropriation provides budget authority.",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "budget authority appropriated",
                "budgetary reporting",
                "current period financial reporting",
                "A-11",
                "OMB Circular A-11"
            ],
            "modified": "2018-07-31",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21925be2-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-23",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Budget Authority Unobligated Balance Brought Forward_FYB",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Appendix F of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below.\n\nFor unexpired accounts: Amount of unobligated balance of appropriations or other budgetary resources carried forward from the preceding year and available for obligation without new action by Congress. For expired accounts: Amount of expired unobligated balances available for upward adjustments of obligations. ",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "fiscal year beginning financial reports",
                "budget authority unobligated balance brought forward",
                "budget authority",
                "A-11",
                "OMB Circular A-11"
            ],
            "modified": "2018-07-31",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "219261dc-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-24",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Adjustments To Unobligated Balance Brought Forward_CPE",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Appendix F of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below.\n\nChanges to unpaid obligations that occurred in a prior fiscal year and that were not recorded in the unpaid obligations as of October 1 of the current fiscal year. \n\n",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "adjustments to unobligated balances brought forward",
                "budgetary reporting",
                "current period financial reporting",
                "A-11",
                "OMB Circular A-11"
            ],
            "modified": "2018-07-31",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "2192643e-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-25",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Other Budgetary Resources Amount_CPE",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Section 20 of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below.\n\nNew borrowing authority, contract authority, and spending authority from offsetting collections provided by Congress in an appropriations act or other legislation, or unobligated balances of budgetary resources made available in previous legislation, to incur obligations and to make outlays.\n",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "other budgetary resources",
                "budgetary reporting",
                "current period financial reporting",
                "A-11",
                "OMB Circular A-11"
            ],
            "modified": "2018-07-31",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "219266b4-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-26",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Contract Authority Amount Total_CPE",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Section 20 of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below.\n\nContract authority is a type of budget authority that permits you to incur obligations in advance of an appropriation, offsetting collections, or receipts to make outlays to liquidate the obligations. Typically, the Congress provides contract authority in an authorizing statute to allow you to incur obligations in anticipation of the collection of receipts or offsetting collections that will be used to liquidate the obligations. ",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "contract authority",
                "budgetary reporting",
                "current period financial reporting",
                "A-11",
                "OMB Circular A-11"
            ],
            "modified": "2018-07-31",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21926902-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-27",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Borrowing Authority Amount Total_CPE",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Section 20 of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below.\n\nBorrowing authority is a type of budget authority that permits obligations and outlays to be financed by borrowing. \n\n\n",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Borrowing authority amount",
                "budgetary reporting",
                "current period financial reporting",
                "A-11",
                "OMB Circular A-11"
            ],
            "modified": "2018-07-31",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21926b64-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-28",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Spending Authority From Offsetting Collections Amount Total_CPE",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Section 20 of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below.\n\nSpending authority from offsetting collections is a type of budget authority that permits obligations and outlays to be financed by offsetting collections.\n\nOffsetting collections mean payments to the Government that, by law, are credited directly to expenditure accounts and deducted from gross budget authority and outlays of the expenditure account, rather than added to receipts. Usually, they are authorized to be spent for the purposes of the account without further action by Congress. They usually result from business-like transactions with the public, including payments from the public in exchange for goods and services, reimbursements for damages, and gifts or donations of money to the Government and from intragovernmental transactions with other Government accounts. The authority to spend offsetting collections is a form of budget authority.\n\n\n",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Spending Authority From Offsetting Collections Amount",
                "budgetary reporting",
                "current period financial reporting",
                "A-11",
                "OMB Circular A-11"
            ],
            "modified": "2018-07-31",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21926dc6-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-29",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Status Of Budgetary Resources Total_CPE",
            "": 43281,
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "This element addresses the status of budgetary resources and includes the total of obligated and unobligated balances, at the reported date. The value should equal the Budget Authority Available Amount Total for the TAS at Current Period End.",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Status of Budgetary Resources",
                "Financial Statements",
                "budgetary reporting",
                "current period financial reporting",
                "A-11",
                "OMB Circular A-11"
            ],
            "modified": "2018-07-31",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "219274e2-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-30",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Obligations Incurred Total By TAS_CPE",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Appendix F of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below.\n\nFor unexpired accounts:\nAmount of obligations incurred from the beginning of the current fiscal year to the end of the reporting period, net of refunds received that pertain to obligations incurred in the current year. Include upward adjustments of prior obligations. \n\nFor expired accounts:\nAmount of upward adjustments of obligations previously incurred. Upward adjustments are limited by the amount available for adjustments. No new obligations may be incurred against expired or canceled accounts.\n\n\n\n",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Obligations Incurred Total by TAS",
                "budgetary reporting",
                "current period financial reporting",
                "A-11",
                "OMB Circular A-11"
            ],
            "modified": "2018-07-31",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "219277c6-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-08-31",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Gross Outlay Amount By TAS_CPE",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Section 20 of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below.\n\nPayments made to liquidate an obligation (other than the repayment of debt principal or other disbursements that are \u201cmeans of financing\u201d transactions). Outlays generally are equal to cash disbursements but also are recorded for cash-equivalent transactions, such as the issuance of debentures to pay insurance claims, and in a few cases are recorded on an accrual basis such as interest on public issues of the public debt. Outlays are the measure of Government spending. \n\n",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "language": [
                "en-US"
            ],
            "keyword": [
                "Gross outlay amount",
                "budgetary reporting",
                "current period financial reporting",
                "A-11",
                "OMB Circular A-11"
            ],
            "modified": "2018-07-31",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21927a5a-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-09-01",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Unobligated Balance CPE",
            "describedBy": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "description": "The definition for this element appears in Section 20 of OMB Circular A-11 issued June 2015; a brief summary from A-11 appears below.\n\nUnobligated balance means the cumulative amount of budget authority that remains available for obligation under law in unexpired accounts. The term \u201cexpired balances available for adjustment only\u201d refers to unobligated amounts in expired accounts.\n \n\n",
            "programCode": [
                "020:028"
            ],
            "bureauCode": [
                "020:00"
            ],
            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Brian Webb"
            },
            "accessLevel": "public",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
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            "language": [
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            ],
            "keyword": [
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                "budgetary reporting",
                "current period financial reporting",
                "A-11",
                "OMB Circular A-11"
            ],
            "modified": "2018-07-31",
            "accrualPeriodicity": "R/P3M",
            "dataQuality": true,
            "distribution": [
                {
                    "accessURL": "https://api.usaspending.gov",
                    "description": "USAspending.gov is the official source for spending data for the U.S. Government. Its mission is to show the American public what the federal government spends every year and how it spends the money. You can follow the money from the Congressional appropriations to the federal agencies and down to local communities and businesses",
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                    "title": "usaspending.gov"
                },
                {
                    "accessURL": "https://www.usaspending.gov/agency/environmental-protection-agency",
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                    "@type": "dcat:Distribution",
                    "title": "usaspending.gov"
                },
                {
                    "description": "EPA File A submission to comply with the DATA Act.",
                    "title": "Raw Quarterly DATA Act Files - Environmental Protection Agency (EPA) / File A, Appropriations",
                    "format": "text/csv",
                    "mediaType": "text/csv",
                    "downloadURL": "https://www.usaspending.gov/download_center/award_data_archive",
                    "@type": "dcat:Distribution"
                }
            ],
            "identifier": "21927cc6-a583-11e8-98d0-529269fb1459",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCFO",
            "sourcetitle": "EPA Office of the Chief Financial Officer",
            "sourcefile": "https://edg.epa.gov/data/public/OCFO/metadata/DataAct.json"
        },
        {
            "conformsTo": "https://www.fiscal.treasury.gov/fsservices/gov/data-trans/dt-daims.htm",
            "issued": "2018-09-02",
            "license": "https://edg.epa.gov/epa_data_license.html",
            "title": "Deobligations Recoveries Refunds By TAS_CPE",
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            "description": "The amount of downward adjustments to obligations and outlays resulting from deobligations, recoveries, or refunds collected, summarized at the TAS level. The adjustments are to the obligations and outlays which were made in a prior year.",
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            "contactPoint": {
                "hasEmail": "mailto:webb.brian@epa.gov",
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            "publisher": {
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                "name": "U.S. Environmental Protection Agency"
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            "language": [
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            "keyword": [
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            "identifier": "21927f28-a583-11e8-98d0-529269fb1459",
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        {
            "title": "List N- Disinfectants for Use Against SARS-CoV-2 (COVID-19)",
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            "dataQuality": true,
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            "keyword": [
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        {
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                "Alabama",
                "Arizona",
                "Arkansas",
                "California",
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                "Iowa",
                "Kansas",
                "Kentucky",
                "Louisiana",
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                "Maryland",
                "Massachusetts",
                "Michigan",
                "Minnesota",
                "Mississippi",
                "Missouri",
                "Montana",
                "Nebraska",
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                "New Mexico",
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                "Rhode Island",
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            "holdren": "No",
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        {
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                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pesticide Programs (OPP)"
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            "accessLevel": "public",
            "description": "The Chemical Search Web Utility is an intuitive web application that allows the public to easily find the chemical that they are interested in using, and which provides a broad array of simple to advanced search options.",
            "keyword": [
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                "buffer zone calculator",
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            },
            "identifier": "77B9868D-A0A9-4F79-83CF-FCFF63CA0DE1",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
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        },
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                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pesticide Programs (OPP)"
            },
            "accessLevel": "public",
            "description": "The Pesticide Product Label System (PPLS) provides a collection of pesticide product labels (Adobe PDF format) that have been approved by EPA under Section 3 of the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA). New labels were added to PPLS on November 21, 2014. Pesticide product labels provide critical information about how to safely handle and use registered pesticide products. An approved pesticide product label represents the full content of EPAs registration decision regarding that product. Pesticide labels contain detailed information on the use, storage, and handling of a product. This information will be found on EPA stamped-approved labels and, in some cases, in subsequent related correspondence, which is also included in PPLS. You may need to review several PDF files for a single product to determine the complete current terms of registration.",
            "keyword": [
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                "product label",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "Pesticide Product Label System",
            "distribution": [
                {
                    "accessURL": "https://iaspub.epa.gov/apex/pesticides/f?p=PPLS:1",
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            ],
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            },
            "identifier": "F4E8281C-2AD5-4817-BBE5-6EBA55C8DF18",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pesticide Programs",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPP/metadata/OCSPP-OPP.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pesticide Programs (OPP)"
            },
            "accessLevel": "public",
            "description": "PRISM provides an integrated, web portal for all pesticide related data, communications, registrations and transactions for OPP and its stakeholders, partners and customers. PRISM supports Strategic Goal 4 by automating pesticide registration processes.",
            "keyword": [
                "documentum",
                "endangered species",
                "endocrine disruptors",
                "luis",
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                "ssts",
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                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "Pesticide Registration Information System",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/pesticide-registration",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:Schultz.Robert@epa.gov",
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            },
            "identifier": "4B03A4C6-94B4-4BE0-89BF-1BA2BDBB1BBD",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pesticide Programs",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPP/metadata/OCSPP-OPP.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pesticide Programs (OPP)"
            },
            "accessLevel": "public",
            "description": "The Pesticide Product Information System contains information concerning all pesticide products registered in the United States. It includes registrant name and address, chemical ingredients, toxicity category, product names, distributor brand names, site/pest uses, pesticidal type, formulation code, and registration status.",
            "keyword": [
                "data finder",
                "substances",
                "pesticides",
                "environment",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "Pesticide Product Information System (PPIS)",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/ingredients-used-pesticide-products/pesticide-product-information-system-ppis",
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                }
            ],
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            },
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            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pesticide Programs",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPP/metadata/OCSPP-OPP.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Federal Insecticide, Fungicide, and Rodenticide Act Section 18 Database",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/enforcement/federal-insecticide-fungicide-and-rodenticide-act-fifra-and-federal-facilities",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
                }
            ],
            "description": "Section 18 of Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) authorizes EPA to allow an unregistered use of a pesticide for a limited time if EPA determines that an emergency condition exists. This database provides information about these emergency exemptions.",
            "keyword": [
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                "water",
                "environment",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
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            },
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            },
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            "accessLevel": "public",
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            ],
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            "programCode": [
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pesticide Programs",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPP/metadata/OCSPP-OPP.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Aquatic Life Benchmarks",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/aquatic-life-benchmarks-pesticide-registration",
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            ],
            "description": "The Aquatic Life Benchmarks is an EPA-developed set of criteria for freshwater species. These benchmarks are based on toxicity values reviewed by EPA and used in the Agency's risk assessments developed as part of the decision-making process for pesticide registration.",
            "keyword": [
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                "water",
                "water pollution",
                "non-point sources of water pollution",
                "environment",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Michelle Thawley, U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP)",
                "hasEmail": "mailto:thawley.michelle@epa.gov"
            },
            "identifier": "DC8A097C-3206-4717-B20D-55D2BAD74900",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BDC8A097C-3206-4717-B20D-55D2BAD74900%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7BDC8A097C-3206-4717-B20D-55D2BAD74900%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pesticide Programs",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPP/metadata/OCSPP-OPP.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "accessLevel": "public",
            "description": "The Electronics Environmental Benefits Calculator (EEBC) was developed to assist organizations in estimating the environmental benefits of greening their purchase,  use and disposal of electronics. The EEBC estimates the environmental and economic benefits of: Purchasing Electronic Product Environmental Assessment Tool (EPEAT)-registered products; Enabling power management features on computers and monitors above default percentages;  Extending the life of equipment beyond baseline values;  Reusing computers,  monitors and cell phones; and Recycling computers,  monitors,  cell phones and loads of mixed electronic products. The EEBC may be downloaded as a Microsoft Excel spreadsheet.\nSee https://www.federalelectronicschallenge.net/resources/bencalc.htm for more details.",
            "keyword": [
                "environment",
                "energy",
                "environment",
                "environment",
                "united states",
                "economy"
            ],
            "title": "Electronics Environmental Benefits Calculator",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/fec/publications-and-resources#acquisition",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
                }
            ],
            "issued": "2014-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
                "020:00"
            ],
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7BB359142D-11A3-4E20-BBCC-DE17E413C699%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BB359142D-11A3-4E20-BBCC-DE17E413C699%7D"
            ],
            "accrualPeriodicity": "irregular",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:Guthrie.Christina@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Christina Guthrie, U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "identifier": "B359142D-11A3-4E20-BBCC-DE17E413C699",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPPT/metadata/OCSPP-OPPT.json"
        },
        {
            "title": "Initial Entry Search System",
            "description": "Dataset contains high-level use information used for new chemical review under TSCA.",
            "modified": "2021",
            "publisher": {
                "@type": "org:Organization",
                "name": "Office of Chemical Safety and Pollution Prevention"
            },
            "contactPoint": {
                "fn": "Franklyn Hall",
                "hasEmail": "mailto:hall.franklyn@epa.gov",
                "@type": "vcard:Contact"
            },
            "identifier": "39350f95-de40-406d-9b81-e24462b4aeac",
            "accessLevel": "non-public",
            "rights": "EPA Category: Confidential Business Information, NARA Category: Proprietary-Manufacturer",
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "bureauCode": [
                "020:00"
            ],
            "temporal": "1999-01-01/2030-01-01",
            "issued": "1999-01-01",
            "language": [
                "en",
                "en-us"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "format": "C Source File (.c)",
                    "title": "Not Applicable",
                    "description": "Dataset contains high-level use information used for new chemical review under TSCA.",
                    "mediaType": "text/x-c"
                }
            ],
            "keyword": [
                "Chemicals",
                "Air",
                "Drinking Water",
                "environment",
                "exposure",
                "Facilities",
                "Ground Water",
                "Human",
                "Land",
                "Toxics",
                "Surface Water",
                "Sites",
                "Water",
                "United States",
                "use",
                "releases"
            ],
            "programCode": [
                "020:072"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPPT/metadata/OCSPP-OPPT.json"
        },
        {
            "title": "Inventory Update Rule ",
            "description": "Information on chemicals manufactured or imported into the United States and listed on the TSCA Chemical Substances Inventory was collected periodically by the EPA as part of the Inventory Update Rule (IUR). This collection began in 1986 and was changed to the Chemical Data Reporting (CDR) rule in 2012.",
            "bureauCode": [
                "020:00"
            ],
            "dataQuality": false,
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA- Office Of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention (OPPT)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Jeff Santacroce",
                "hasEmail": "mailto:santacroce.jeffrey@epa.gov"
            },
            "keyword": [
                "Chemicals",
                "environment",
                "Exposure",
                "Facilities",
                "health",
                "Human",
                "Regulatory",
                "Sites",
                "Toxics",
                "United States",
                "Alaska",
                "Hawaii",
                "Washington DC",
                "American Samoa",
                "Puerto Rico",
                "Virgin Islands",
                "Alabama",
                "Arizona",
                "Arkansas",
                "California",
                "Colorado",
                "Connecticut",
                "Delaware",
                "Florida",
                "Georgia",
                "Idaho",
                "Illinois",
                "Indiana",
                "Iowa",
                "Kansas",
                "Kentucky",
                "Louisiana",
                "Maine",
                "Maryland",
                "Massachusetts",
                "Michigan",
                "Minnesota",
                "Mississippi",
                "Missouri",
                "Montana",
                "Nebraska",
                "Nevada",
                "New Hampshire",
                "New Jersey",
                "New Mexico",
                "New York",
                "North Carolina",
                "North Dakota",
                "Ohio",
                "Oklahoma",
                "Oregon",
                "Pennsylvania",
                "Rhode Island",
                "South Carolina",
                "South Dakota",
                "Tennessee",
                "Texas",
                "Utah",
                "Vermont",
                "Virginia",
                "Washington",
                "West Virginia",
                "Wisconsin",
                "Wyoming",
                "economy",
                "location",
                "Use",
                "Production Volume",
                "Recycling",
                "Physical Form",
                "Company",
                "Manufacturer",
                "TSCA"
            ],
            "modified": "2009",
            "identifier": "567dfc76-1bae-43c0-bc6c-a17f99df7979",
            "accessLevel": "public",
            "rights": "Only TSCA CBI cleared individuals will be able to access the data asserted as CBI.",
            "license": "https://www.epa.gov/chemical-data-reporting/access-cdr-data#2006",
            "temporal": "2005/2006",
            "issued": "2009-03-09",
            "language": [
                "en-us"
            ],
            "landingPage": "https://www.epa.gov/chemical-data-reporting/access-cdr-data#2006",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/chemical-data-reporting/access-cdr-data#2006",
                    "title": "IUR datasets",
                    "description": "The full IUR data sets are stored on the TSCA CBI LAN.  A public version of the 2006 IUR data is available on the Internet.",
                    "format": " 2006IUR.zip contains 4 DBF files and an IUR_2006_Readme.doc file. The DBF files store the non-confidential IUR records for 2006."
                }
            ],
            "programCode": [
                "020:072"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPPT/metadata/OCSPP-OPPT.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Federal Lead-Based Paint Program (FLPP) Database",
            "description": "The FLPP Database system supports the application process for the accreditation of training providers and the certification of firms and individuals who performs lead based abatements and renovation and repair activities in the United States.",
            "bureauCode": [
                "020:00"
            ],
            "dataQuality": true,
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT) - Existing Chemicals Risk Management Division (ECRMD)"
            },
            "contactPoint": {
                "fn": "Robert Wright",
                "hasEmail": "mailto:wright.robert@epa.gov",
                "@type": "vcard:Contact"
            },
            "keyword": [
                "Environment",
                "Regulatory",
                "Toxics",
                "United States",
                "FLPP Firm Search",
                "FLPP Trainer Search",
                "FLPP Application Process"
            ],
            "modified": "2021-11-05",
            "identifier": "020-000014003",
            "accessLevel": "restricted public",
            "rights": "EPA Category: Personally Identifiable Information (PII), NARA Category: Privacy",
            "license": "http://www.usa.gov/publicdomain/label/1.0/",
            "temporal": "2006-06-03/2025-12-31",
            "issued": "2021-11-05",
            "accrualPeriodicity": "R/P1M",
            "language": [
                "en-us"
            ],
            "conformsTo": "https://resources.data.gov/",
            "describedBy": "https://project-open-data.cio.gov/v1.1/schema/catalog.json",
            "describedByType": "application/javascript",
            "landingPage": "https://javaauth.epa.gov/flpp/",
            "references": [
                "https://www.epa.gov/lead"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://javaauth.epa.gov/flpp/",
                    "title": "FLPP Database",
                    "description": "The FLPP Database system supports the application process for the accreditation of training providers and the certification of firms and individuals who performs lead based abatements and renovation and repair activities in the United States.",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://cfpub.epa.gov/flpp/pub/index.cfm?do=main.firmSearch",
                    "title": "Find RRP Firms",
                    "description": "Public search tool to locate certified RRP Firms",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://cfpub.epa.gov/flpp/search.cfm?Applicant_Type=firm",
                    "title": "Find Abatement Firms",
                    "description": "Public search tool to locate certified Abatement firms",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://cdxapps.epa.gov/ocspp-oppt-leadhub/training-search?do=main.trainingSearch",
                    "title": "Find RRP Trainers",
                    "description": "Public search tool to locate accredited RRP Training Providers",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://cfpub.epa.gov/flpp/pub/index.cfm?do=main.trainingSearchAbatement",
                    "title": "Find Abatement Trainers",
                    "description": "Public search tool to locate certified Abatement Training Providers",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://cfpub.epa.gov/flpp/pub/index.cfm?do=main.individualSearch",
                    "title": "Search for Individual Applicants to locate their information for certification",
                    "description": "Public search tool link to apply for Individual Lead certifications ",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/lead/lead-renovationabatement-firm-certification-application-or-update",
                    "title": "Search for Firm Application Process",
                    "description": "Public search tool link to locate their information for Firm certification",
                    "format": "API"
                }
            ],
            "programCode": [
                "020:013"
            ],
            "systemofrecords": "http://www2.epa.gov/privacy/privacy-act-system-records-federal-lead-based-paint-program-system-records-epa-5",
            "primaryitinvestmentuii": "020-000014003",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPPT/metadata/OCSPP-OPPT.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "accessLevel": "public",
            "description": "This data extraction tool contains the non confidential identities of chemical substances submitted under the Toxic Substances Control Act (TSCA). TSCA was enacted to ensure that chemicals manufactured,  imported,  processed,  or distributed in commerce,  or used or disposed of in the United States do not pose any unreasonable risks to human health or the environment. EPA adds chemical substances to the TSCA Inventory following EPAs receipt of a Notice of Commencement (NOC) signaling the manufacturers intent to produce a chemical substance that EPA has previously reviewed and approved. Since EPA published the final TSCA Inventory Reporting Rule on December 23,  1977,  the TSCA Inventory has grown to include the identities of over 83, 000 chemical substances.",
            "keyword": [
                "substance inventory",
                "chemical substance inventory",
                "new chemicals",
                "toxic chemicals",
                "chemical list",
                "existing chemicals",
                "manufactured chemicals",
                "tsca inventory",
                "industrial chemicals",
                "commercial chemicals",
                "toxic substances control act",
                "notice of commencement",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "TSCA Inventory Data Extraction Tool",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/tsca-inventory",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
                }
            ],
            "issued": "2014-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
                "020:00"
            ],
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B4D49A8F7-9B38-44B0-966D-41D7A31856F8%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B4D49A8F7-9B38-44B0-966D-41D7A31856F8%7D"
            ],
            "accrualPeriodicity": "R/P6M",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:saxton.dion@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Dion Saxton, U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "identifier": "4D49A8F7-9B38-44B0-966D-41D7A31856F8",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPPT/metadata/OCSPP-OPPT.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "accessLevel": "public",
            "description": "The E3 initiative is designed to help you thrive in a new business era focused on sustainability and,  working together,  to promote sustainable manufacturing and economic growth throughout the United States. Within the E3 framework,  we can: - Drive Innovation - Increase Manufacturing Productivity - Boost Local Economies - Reduce Environmental Impacts - Foster Development - Conserve Energy and Resources This website provides information and tools for E3,  including fact sheets,  contacts,  and calculators.",
            "keyword": [
                "economy",
                "economics",
                "energy",
                "environment",
                "sustainability",
                "resources",
                "best practices",
                "productivity",
                "development",
                "communities",
                "innovation",
                "tools",
                "calculators",
                "environment",
                "environment",
                "united states",
                "economy"
            ],
            "title": "E3: Economy - Energy - Environment; Supporting Manufacturing Leadership through Sustainability",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/e3/about-e3-economy-energy-environment",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
                }
            ],
            "issued": "2010-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
                "020:00"
            ],
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B7BECF83A-CE57-48E3-9650-B155DD48A8DF%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B7BECF83A-CE57-48E3-9650-B155DD48A8DF%7D"
            ],
            "accrualPeriodicity": "irregular",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:Guthrie.Christina@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Christina Guthrie, U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "identifier": "7BECF83A-CE57-48E3-9650-B155DD48A8DF",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPPT/metadata/OCSPP-OPPT.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "accessLevel": "public",
            "description": "This tool is intended to aid individuals interested in learning more about chemicals that are manufactured or imported into the United States. Health and safety information on these chemicals,  primarily in the form of paper documents,  are routinely submitted by industry (manufacturers or importers of chemicals) to EPA under the Toxic Substances Control Act (TSCA).  EPA is in the process of converting these documents into electronic form and making non-confidential versions of these documents accessible through this tool.  The tool enables users to conduct both full text and metadata searches of these documents,  and presents these as .pdf for viewing or downloading.  The tool also queries existing EPA legacy database sources of chemical information and presents these data in a consistent format.",
            "keyword": [
                "chemicals",
                "chemical companies",
                "manufacturers",
                "toxic chemicals",
                "hpvis",
                "imported",
                "cas number",
                "tscats",
                "database",
                "8e",
                "health and safety studies",
                "tsca",
                "pollution",
                "pollutant",
                "compound",
                "toxicity",
                "chemical data access",
                "chemical search tool",
                "chemical access tool",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "Chemical Data Access Tool",
            "distribution": [
                {
                    "accessURL": "https://java.epa.gov/oppt_chemical_search/",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
                }
            ],
            "issued": "2010-01-22",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
                "020:00"
            ],
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B2D73C764-6919-404D-8C9B-61869B3330D6%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B2D73C764-6919-404D-8C9B-61869B3330D6%7D"
            ],
            "accrualPeriodicity": "R/PT1S",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:saxton.dion@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Dion Saxton, U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "identifier": "2D73C764-6919-404D-8C9B-61869B3330D6",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPPT/metadata/OCSPP-OPPT.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "accessLevel": "public",
            "description": "This dataset contains information on chemicals that company's produce domestically or import into the United States during the principal reporting year. For the 2012 submission period, reporters provided 2011 manufacturing, processing, and use data and 2010 production volume data for their reportable chemical substances.",
            "keyword": [
                "substance inventory",
                "chemical substance inventory",
                "tsca",
                "new chemical",
                "toxic",
                "manufacture.process",
                "use",
                "chemical reporting",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "Chemical Data Reporting rule (CDR)",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/chemical-data-reporting",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
                }
            ],
            "issued": "2009-12-21",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
                "020:00"
            ],
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B91CAEB15-8E6B-48D4-A223-3E2D9B4D4847%7D",
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            "contactPoint": {
                "hasEmail": "mailto:Sirmons.Chandler@epa.gov",
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            "identifier": "91CAEB15-8E6B-48D4-A223-3E2D9B4D4847",
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            "geo": "No",
            "holdren": "No",
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            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPPT/metadata/OCSPP-OPPT.json"
        },
        {
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            "accessLevel": "public",
            "description": "Search tool developed to provide stakeholders access to various TSCA chemicals, and health and safety information. The tool also provides EPA assessments and actions on Chemicals.",
            "keyword": [
                "health and safety data",
                "tsca chemicals",
                "assessments",
                "actions",
                "test rules",
                "significant new use",
                "hazard characterizations",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "ChemView",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/assessing-and-managing-chemicals-under-tsca/introduction-chemview",
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                }
            ],
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                "https://edg.epa.gov/metadata/rest/document?id=%7BFE8CC3EA-5D45-43D4-BDBE-4D55C4DFB66A%7D",
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            ],
            "accrualPeriodicity": "R/PT1S",
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:santacroce.jeffrey@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Jeff Santacroce, U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "identifier": "FE8CC3EA-5D45-43D4-BDBE-4D55C4DFB66A",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPPT/metadata/OCSPP-OPPT.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "accessLevel": "public",
            "description": "This dataset contains a list of products that carry the Design for the Environment (DfE) label. This mark enables consumers to quickly identify and choose products that can help protect the environment and are safer for families. When you see the DfE logo on a product it means that the DfE scientific review team has screened each ingredient for potential human health and environmental effects and that-based on currently available information,  EPA predictive models,  and expert judgment-the product contains only those ingredients that pose the least concern among chemicals in their class. Product manufacturers who become DfE partners,  and earn the right to display the DfE logo on recognized products,  have invested heavily in research,  development and reformulation to ensure that their ingredients and finished product line up on the green end of the health and environmental spectrum while maintaining or improving product performance. EPA's Design for the Environment Program (DfE) has allowed use of their logo on over 2500 products. These products are formulated from the safest possible ingredients and have reduced the use of \"chemicals of concern\" by hundreds of millions of pounds.",
            "keyword": [
                "dfe",
                "safer product labeling program",
                "office of pollution prevention and toxics",
                "oppt",
                "list",
                "environmental considerations",
                "design",
                "environmental impacts",
                "redesign",
                "products",
                "voluntary partnerships",
                "industry",
                "chemical safety",
                "household chemicals",
                "design for environment",
                "safe chemical alternatives",
                "pollution prevention",
                "toxic substances control act",
                "tsca",
                "design for the environment",
                "cleaning products",
                "household products",
                "green chemistry",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "Design for the Environment Products (Online Search)",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/saferchoice/design-environment-programs-initiatives-and-projects",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
                }
            ],
            "issued": "1997-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
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            ],
            "references": [
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            "spatial": "-180.0,18.0,-66.0,72.0",
            "programCode": [
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:saxton.dion@epa.gov",
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                "fn": "Dion Saxton, U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "identifier": "D060AB34-66E2-4BDF-8BC6-6415F55498EF",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
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        {
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                "@type": "org:Organization",
                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "accessLevel": "public",
            "description": "This dataset contains a list of products that carry the Design for the Environment (DfE) label. This mark enables consumers to quickly identify and choose products that can help protect the environment and are safer for families. When you see the DfE logo on a product it means that the DfE scientific review team has screened each ingredient for potential human health and environmental effects and that-based on currently available information,  EPA predictive models,  and expert judgment-the product contains only those ingredients that pose the least concern among chemicals in their class. Product manufacturers who become DfE partners,  and earn the right to display the DfE logo on recognized products,  have invested heavily in research,  development and reformulation to ensure that their ingredients and finished product line up on the green end of the health and environmental spectrum while maintaining or improving product performance. EPA's Design for the Environment Program (DfE) has allowed use of their logo on over 2500 products. These products are formulated from the safest possible ingredients and have reduced the use of \"chemicals of concern\" by hundreds of millions of pounds. A Spanish version of this dataset is available for download at https://www.epa.gov/dfe/pubs/products/list_of_labeled_products.html",
            "keyword": [
                "dfe",
                "safer product labeling program",
                "office of pollution prevention and toxics",
                "oppt",
                "list",
                "environmental considerations",
                "design",
                "environmental impacts",
                "redesign",
                "products",
                "voluntary partnerships",
                "industry",
                "chemical safety",
                "household chemicals",
                "design for environment",
                "safe chemical alternatives",
                "pollution prevention",
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                "cleaning products",
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                "green chemistry",
                "environment",
                "environment",
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            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPPT/metadata/OCSPP-OPPT.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "accessLevel": "public",
            "description": "The High Production Volume Information System (HPVIS) provides access to select health and environmental effect information on chemicals that are manufactured in exceptionally large amounts.",
            "keyword": [
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                "substances",
                "chemicals",
                "human health",
                "health risks",
                "exposure",
                "environment",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "High Production Volume Information System (HPVIS)",
            "distribution": [
                {
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                    "@type": "dcat:Distribution",
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
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            },
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            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
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            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
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                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP) - Office of Pollution Prevention and Toxics (OPPT)"
            },
            "accessLevel": "public",
            "description": "This dataset consists of the non confidential identities of chemical substances submitted under the Toxic Substances Control Act (TSCA).  TSCA was enacted to ensure that chemicals manufactured,  imported,  processed,  or distributed in commerce,  or used or disposed of in the United States do not pose any unreasonable risks to human health or the environment.  EPA adds chemical substances to the TSCA Inventory following EPAs receipt of a Notice of Commencement (NOC) signaling the manufacturers intent to produce a chemical substance that EPA has previously reviewed and approved. Since EPA published the final TSCA Inventory Reporting Rule on December 23,  1977,  the TSCA Inventory has grown to include the identities of over 83, 000 chemical substances.",
            "keyword": [
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                "chemical substance inventory",
                "new chemicals",
                "toxic chemicals",
                "chemical list",
                "existing chemicals",
                "manufactured chemicals",
                "tsca inventory",
                "industrial chemicals",
                "commercial chemicals",
                "toxic substances control act",
                "notice of commencement",
                "environment",
                "environment",
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            "title": "TSCA Inventory",
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            "geo": "No",
            "holdren": "No",
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            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
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        },
        {
            "@type": "dcat:Dataset",
            "title": "Toxic Substances Control Act (TSCA) 8(e) Notices and FYI Submissions",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/assessing-and-managing-chemicals-under-tsca",
                    "@type": "dcat:Distribution",
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            ],
            "description": "Section 8(e) of the Toxic Substances Control Act (TSCA) requires U.S. chemical manufacturers, importers, processors and distributors to notify EPA within 30 calendar days of new, unpublished information on their chemicals that may lead to a conclusion of substantial risk to human health or to the environment. This data source collects these Section 8(e) notices as well as voluntary submissions (FYI submissions) and organizes them by date.",
            "keyword": [
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                "pollutants & contaminants",
                "water pollutants",
                "environmental media topics",
                "water",
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                "human health",
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            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
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            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPPT/metadata/OCSPP-OPPT.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Results of Section 4 Chemical Testing",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/assessing-and-managing-chemicals-under-tsca",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
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            ],
            "description": "The Toxic Substances Control Act (TSCA) requires that data be developed on the effect of chemical substances and mixtures on health and the environment. This data source collects the applicable test information on these chemicals submitted by external parties.",
            "keyword": [
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                "air",
                "air pollution",
                "air quality",
                "substances",
                "pollutants & contaminants",
                "air pollutants",
                "criteria air pollutants",
                "environment",
                "environment",
                "environment",
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            "modified": "2014-01-01",
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            },
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                "fn": "Mark Seltzer, U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP)",
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            "references": [
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                "https://edg.epa.gov/metadata/rest/document?id=%7B1CE2B1B7-34E6-49C4-8B13-C7FB8A7C9B1D%7D"
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
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            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPPT/metadata/OCSPP-OPPT.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Acute Exposure Guideline Levels Chemical Listing",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/aegl",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
                }
            ],
            "description": "The Acute Exposure Guideline Levels Chemical Listing provides a complete listing of risk exposure guidelines from rare exposure to certain chemicals.",
            "keyword": [
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                "human health",
                "health risks",
                "exposure",
                "acute exposure",
                "substances",
                "chemicals",
                "environment",
                "environment",
                "environment",
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            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
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                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP)"
            },
            "contactPoint": {
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                "fn": "Ernest Falke, U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP)",
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            },
            "identifier": "BC3DF16C-9287-454B-92A8-FF7F7788D43D",
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            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OCSPP",
            "sourcetitle": "EPA Office of Chemical Safety and Pollution Prevention, Office of Pollution Prevention and Toxics",
            "sourcefile": "https://edg.epa.gov/data/public/OCSPP/OPPT/metadata/OCSPP-OPPT.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Enforcement and Compliance Assurance (OECA)"
            },
            "accessLevel": "public",
            "description": "The Criminal Case Reporting System is designed to record and track criminal case activity.",
            "keyword": [
                "enforcement",
                "criminal",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "Criminal Case Reporting System",
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                {
                    "accessURL": "https://www.epa.gov/enforcement/criminal-enforcement",
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                    "mediaType": "text/csv"
                }
            ],
            "issued": "2006-03-06",
            "modified": "2014-01-01",
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            ],
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            "programCode": [
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:Johnson.Pam@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Pamela Johnson, U.S. EPA Office of Enforcement and Compliance Assurance (OECA)"
            },
            "identifier": "1A2BFDAC-A613-4E4F-9B8D-26AC4DA9F686",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OECA",
            "sourcetitle": "EPA Office of Enforcement and Compliance Assurance",
            "sourcefile": "https://edg.epa.gov/data/public/OECA/metadata/OECA.json"
        },
        {
            "title": "Integrated Compliance Information System (ICIS)",
            "description": "The purpose of ICIS is to meet evolving Enforcement and Compliance business needs for EPA and State users by integrating information into a single integrated data system that supports both management and programmatic requirements of the Enforcement and Compliance programs.",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Enforcement and Compliance Assurance (OECA)"
            },
            "keyword": [
                "environment",
                "United States",
                "icis",
                "pcs modernization",
                "afs modernization"
            ],
            "dataQuality": false,
            "bureauCode": [
                "020:00"
            ],
            "spatial": "-180.0,18.0,-66.0,72.0",
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "ICIS User Support, U.S. EPA Office of Enforcement and Compliance Assurance (OECA)",
                "hasEmail": "mailto:icis_production@epa.gov"
            },
            "@type": "dcat:Dataset",
            "identifier": "E95156F3-39BE-4734-9999-0DFAEE036BA6",
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "temporal": "2002-06-24/2025-02-05",
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            "modified": "2025-02-05",
            "accrualPeriodicity": "irregular",
            "references": [
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            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://enviro.epa.gov/envirofacts/icis-air/search",
                    "format": "HyperText Markup Language (HTML) (.html)",
                    "title": "ICIS-Air Search in Envirofacts",
                    "mediaType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://enviro.epa.gov/envirofacts/icis-npdes/search",
                    "title": "ICIS-NPDES Search in Envirofacts"
                }
            ],
            "programCode": [
                "020:072",
                "020:034"
            ],
            "primaryitinvestmentuii": "020-000015010",
            "geo": "No",
            "holdren": "No",
            "ORG": "OECA",
            "sourcetitle": "EPA Office of Enforcement and Compliance Assurance",
            "sourcefile": "https://edg.epa.gov/data/public/OECA/metadata/OECA.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Enforcement and Compliance Information Center - ECIC",
            "description": "Enforcement and Compliance Information Center - ECIC is a repository of external policy and guidance documents, links to cases and settlements, civil and criminal complaints that are reviewed by HQ and Regional staff.",
            "bureauCode": [
                "020:00"
            ],
            "dataQuality": false,
            "publisher": {
                "@type": "org:Organization",
                "name": "Office of Civil Enforcement (OCE); Office of Criminal Enforcement, Forensics and Training (OCEFT); Office of Site Remediation Enforcement (OSRE); Office of Compliance (OC); Office of Administration and Policy (OAP); Federal Facilities Enforcement Office (FFEO)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Munsel Norris",
                "hasEmail": "mailto:norris.munsel@epa.gov"
            },
            "keyword": [
                "Agriculture",
                "Air",
                "Chemicals",
                "Cleanup",
                "Climate",
                "Compliance",
                "Contaminant",
                "Disaster",
                "Drinking Water",
                "Emergency Response",
                "Energy",
                "Enforcement",
                "environment",
                "Environmental Justice",
                "Facilities",
                "Ground Water",
                "Hazards",
                "health",
                "Human",
                "Indoor Air",
                "Inspections",
                "Land",
                "Marine",
                "Modeling",
                "Monitoring",
                "Natural Resources",
                "Permits",
                "Pesticides",
                "Radiation",
                "Regulated Facilities",
                "Risk",
                "Sites",
                "Spills",
                "Surface Water",
                "Toxics",
                "transportation",
                "Waste",
                "Water",
                "United States",
                "Washington DC",
                "Alabama",
                "Arkansas",
                "Colorado",
                "Delaware",
                "Florida",
                "Georgia",
                "Iowa",
                "Kentucky",
                "Louisiana",
                "Maine",
                "Maryland",
                "Minnesota",
                "Mississippi",
                "New Hampshire",
                "New Mexico",
                "New York",
                "North Carolina",
                "Ohio",
                "Oklahoma",
                "Rhode Island",
                "South Dakota",
                "Texas",
                "Vermont",
                "Virginia",
                "Wisconsin",
                "Chesapeake Bay",
                "Great Lakes",
                "Gulf of Mexico",
                "boundaries",
                "economy",
                "imageryBaseMapsEarthCover",
                "location",
                "civil",
                "orse",
                "ffeo",
                "cases and settlements",
                "policy",
                "criminal",
                "orders",
                "hurricanes",
                "compliants",
                "superfund",
                "guidance",
                "documents",
                "ecic",
                "ioic",
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                "offices"
            ],
            "modified": "2021",
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            "accessLevel": "public",
            "license": "https://wamssoprd.epa.gov/oam/server/obrareq.cgi?encquery%3DltFBGfd0IFrI%2FiDWE1to9AZRep8fZ0Lj9o82zoaehx5AxOMlQ%2Fy7pxD%2FFpTYEgvC4BlfnOsrTIiEi9GffFdXobe6oB0SkxpItFSBs7roNikWdfd1A1hmkPi81uEavo4RozB%2F%2FEbCslSyMW87LQGcxIV%2F0LqWE3WVXX%2F3DPbM83CexdVVMmea6mlE2OWErEsDgf2%2B1pQ75DeovuGpkSPUzWZVdfhJwlLPQ7NXrqTAvsJrY8nAYC5%2BB%2F1mGvUTcnwi8nb5BGgLt1hrqYrRR1DSuIW5MiiI%2BUU%2Fwnp8C5T6yfCDJfYpAXAZTpi5gDQr%2BQVl%20agentid%3DWebgateEPADomain%20ver%3D1%20crmethod%3D2%26cksum%3Df416c6edf0829fa7f6213bb120f486a9fd42a836",
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            "programCode": [
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            "primaryitinvestmentuii": "020-000030304",
            "geo": "No",
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            "ORG": "OECA",
            "sourcetitle": "EPA Office of Enforcement and Compliance Assurance",
            "sourcefile": "https://edg.epa.gov/data/public/OECA/metadata/OECA.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "State Review Framework Manager Database",
            "description": "The State Review Framework is a primary means by which EPA conducts oversight of three core federal statutes: Clean Air Act, Clean Water Act, and Resource Conservation and Recovery Act. The routine, nationwide review provides a consistent process for evaluating the performance of state, local and EPA compliance and enforcement programs. The overarching goal of the reviews is to ensure fair and consistent enforcement necessary to protect human health and the environment.",
            "modified": "2021",
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            "contactPoint": {
                "fn": "Jibri Mayo",
                "hasEmail": "mailto:mayo.jibri@epa.gov",
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            },
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            "accessLevel": "non-public",
            "rights": "EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure",
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "bureauCode": [
                "020:00"
            ],
            "temporal": "2021-10-01/2022-09-30",
            "dataQuality": false,
            "programCode": [
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            ],
            "keyword": [
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                "Enforcement",
                "United States",
                "environment",
                "state oversight",
                "state framework"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OECA",
            "sourcetitle": "EPA Office of Enforcement and Compliance Assurance",
            "sourcefile": "https://edg.epa.gov/data/public/OECA/metadata/OECA.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Enforcement and Compliance Assurance (OECA)"
            },
            "accessLevel": "public",
            "description": "This dataset contains selected cases involving EPA's Regional Judicial Officers (RJOs) from 2005 to present. EPA's Regional Judicial Officers (RJOs) perform adjudicatory functions and act as Agency neutrals in administrative cases. EPA's RJOs are senior attorneys with backgrounds in EPA enforcement, general law, or both.",
            "keyword": [
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                "oeca",
                "rjo",
                "consolidated rules of practice",
                "40 cfr part 22",
                "hearings on interim status corrective action orders",
                "40 cfr part 24",
                "administrative procedure act",
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                "law",
                "legal",
                "record",
                "docket",
                "administrative enforcement",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "Selected Regional Judicial Officer Cases, 2005 - Present",
            "issued": "2014-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
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            ],
            "references": [
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:simpson.moshay@epa.gov",
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            },
            "identifier": "55B4937C-5B14-48B1-BEF7-D248D99F3196",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OECA",
            "sourcetitle": "EPA Office of Enforcement and Compliance Assurance",
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                "@type": "org:Organization",
                "name": "U.S. EPA Office of Enforcement and Compliance Assurance (OECA)"
            },
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            "description": "The Environmental Protection Agency's Enforcement and Compliance History Online (ECHO) website provides customizable and downloadable information about environmental inspections, violations, and enforcement actions for EPA-regulated facilities, like power plants and factories. ECHO advances public information by sharing data related to facility compliance with and regulatory agency activity related to air, hazardous waste, clean water, and drinking water regulations. ECHO offers many user-friendly options to explore data, including:\n1. Facility Search (https://echo.epa.gov/facilities/facility-search?mediaSelected=all): ECHO information is searchable by varied criteria, including location, facility type, and compliance status related to the Clean Air Act, Clean Water Act, Resource Conservation and Recovery Act, and Safe Drinking Water Act. Search results are customizable and downloadable.\n2. Comparative Maps (https://echo.epa.gov/maps/state-comparative-maps) and State Dashboards (https://echo.epa.gov/trends/comparative-maps-dashboards/state-air-dashboard): These tools offer aggregated information about facility compliance status and regulatory agency compliance monitoring and enforcement activity at the national and state level.\n3. Bulk Data Downloads (https://echo.epa.gov/resources/echo-data/data-downloads): One of ECHO's most popular features is the ability to work offline by downloading large data sets. Users can take advantage of the ECHO Exporter, which provides summary information about each facility in a comma-separated format. Additionally, data sets by program also are available as zip files. These are updated weekly as part of the ECHO data refresh.",
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                "echo",
                "enforcement",
                "compliance",
                "oeca",
                "compliance history",
                "violations",
                "detailed facility report",
                "inspections",
                "environmental performance",
                "permit",
                "enforcement actions",
                "penalties",
                "clean air act",
                "caa",
                "clean water act",
                "cwa",
                "resource conservation and recovery act",
                "rcra",
                "emergency planning and community right-to-know act",
                "epcra",
                "safe drinking water act",
                "sdwa",
                "state review framework",
                "state dashboards",
                "epa data download",
                "comparative maps",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "Civil Penalty Policies",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/enforcement/policy-guidance-publications",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
                }
            ],
            "issued": "2014-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
                "020:00"
            ],
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7BBF52D6F1-0816-49A1-8F86-C04923D9FBF2%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BBF52D6F1-0816-49A1-8F86-C04923D9FBF2%7D"
            ],
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            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:Norris.Munsel@epa.gov",
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            },
            "identifier": "BF52D6F1-0816-49A1-8F86-C04923D9FBF2",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OECA",
            "sourcetitle": "EPA Office of Enforcement and Compliance Assurance",
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        },
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                "name": "U.S. EPA Office of Enforcement and Compliance Assurance (OECA)"
            },
            "accessLevel": "public",
            "description": "EPAs Office of Enforcement and Compliance Assurance (OECA)  cases and settlements webpage contains links to selected settlements resolving civil enforcement cases and, in some cases, complaints filed initiating civil judicial and administrative enforcement actions.  Typically, the links are to settlements about which we have issued a press release.  This is not a complete repository of all enforcement actions taken by or on behalf of EPA.  Rather, it represents a subset of enforcement cases, taken civil judicially or administratively, which may be of national interest.  Most of the settlements are civil judicial consent decrees resolving alleged violations of environmental laws (e.g., the Clean Air Act, the Clean Water Act).  In some instances, the website includes significant enforcement actions resolved by the Environmental Appeals Board (EAB). In addition, please note that the cases and settlements webpage does not include:Most administrative enforcement actions; Most civil judicial cases resolving liability under CERCLA; Criminal enforcement matters.",
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                "office of enforcement and compliance assurance",
                "oeca",
                "cases",
                "settlements",
                "regulations",
                "statutes",
                "policy documents",
                "clean air act",
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                "clean water act",
                "cwa",
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                "resource conservation and recovery act",
                "rcra",
                "safe water drinking act",
                "swda",
                "toxic substance control act",
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                "press releases",
                "settlement information sheets",
                "consent decrees",
                "environment",
                "environment",
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            ],
            "title": "Consent Decrees",
            "distribution": [
                {
                    "accessURL": "https://cfpub.epa.gov/enforcement/cases/",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
                }
            ],
            "issued": "2014-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
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            "references": [
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            ],
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
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            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OECA",
            "sourcetitle": "EPA Office of Enforcement and Compliance Assurance",
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        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Enforcement and Compliance Assurance (OECA)"
            },
            "accessLevel": "public",
            "description": "The EPA Administrative Enforcement Dockets database contains the electronic dockets for administrative penalty cases filed by EPA Regions and Headquarters. Visitors can browse the dockets by year, by statute, EPA region, or a via a free text search. It should be noted that in some cases, particularly prior to 2008, dockets have not yet been published electronically. For users looking for information not included on the website, please contact the Regional Hearing Clerk where the case was filed.",
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                "enforcement",
                "decisions",
                "case filings",
                "orders and decisions",
                "legal",
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                "law",
                "administrative penalty cases",
                "initial decisions",
                "remand orders",
                "enforcement",
                "records",
                "compliance",
                "administrative procedure act",
                "eab",
                "decisions and orders",
                "environmental appeals board",
                "permit",
                "fifra section 6",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "EPA Administrative Enforcement Dockets",
            "distribution": [
                {
                    "accessURL": "https://yosemite.epa.gov/OA/rhc/EPAAdmin.nsf",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
                }
            ],
            "issued": "2014-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
                "020:00"
            ],
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BEC25FE3F-183E-41E1-AFCD-62A2417EBB5C%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7BEC25FE3F-183E-41E1-AFCD-62A2417EBB5C%7D"
            ],
            "accrualPeriodicity": "irregular",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "programCode": [
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            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:Hanson.Michael@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Mike Hanson, U.S. EPA Office of Enforcement and Compliance Assurance (OECA)"
            },
            "identifier": "EC25FE3F-183E-41E1-AFCD-62A2417EBB5C",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OECA",
            "sourcetitle": "EPA Office of Enforcement and Compliance Assurance",
            "sourcefile": "https://edg.epa.gov/data/public/OECA/metadata/OECA.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Enforcement and Compliance Assurance (OECA)"
            },
            "accessLevel": "public",
            "description": "This dataset contains Decisions and Orders originating from EPAs Office of Administrative Law Judges (OALJ), which is an independent office in the Office of the Administrator of the EPA. The Administrative Law Judges conduct hearings and render decisions in proceedings between the EPA and persons, businesses, government entities, and other organizations which are or are alleged to be regulated under environmental laws. Administrative Law Judges preside in enforcement and permit proceedings in accordance with the Administrative Procedure Act. Most enforcement actions initiated by the EPA are for the assessment of civil penalties. The Decisions and Orders are organized into three categories: (1) alphabetical listing by the respondent involved, (2) reverse chronological listing by date, and (3) Decisions and Orders under FIFRA Section 6. This dataset includes Decisions and Orders dating back to 1989 in the Reverse Chronological list, Decisions and Orders dating back to 1997 in the Alphabetical list, and a few Decisions and Orders dating back to 1974 under FIFRA Section 6.",
            "keyword": [
                "office of administrative law judges",
                "oalj",
                "office of the administrator",
                "decisions and orders",
                "fifra section 6",
                "enforcement",
                "permit",
                "compliance",
                "administrative procedure act",
                "environmental appeals board",
                "eab",
                "docket",
                "law",
                "legal",
                "record",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "EPA Administrative Law Judge Legal Documents",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/alj",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
                }
            ],
            "issued": "2014-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
                "020:00"
            ],
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B61D37827-1470-453A-BCCD-AB1F32A45B97%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B61D37827-1470-453A-BCCD-AB1F32A45B97%7D"
            ],
            "accrualPeriodicity": "irregular",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:knight.lisa@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Lisa Knight, U.S. EPA Office of Enforcement and Compliance Assurance (OECA)"
            },
            "identifier": "61D37827-1470-453A-BCCD-AB1F32A45B97",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OECA",
            "sourcetitle": "EPA Office of Enforcement and Compliance Assurance",
            "sourcefile": "https://edg.epa.gov/data/public/OECA/metadata/OECA.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Permit Compliance System (PCS)",
            "distribution": [
                {
                    "accessURL": "https://www3.epa.gov/enviro/facts/pcs-icis/search.html",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
                }
            ],
            "description": "The Permit Compliance System (PCS) provides information on companies which have been issued permits to discharge waste water into rivers.",
            "keyword": [
                "datafinder",
                "regulatory & industrial topics",
                "regulated facilities",
                "environmental media topics",
                "water",
                "surface water",
                "rivers",
                "substances",
                "wastes",
                "liquid waste",
                "environment",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Enforcement and Compliance Assurance (OECA)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Kathy Dockery, U.S. EPA Office of Enforcement and Compliance Assurance (OECA)",
                "hasEmail": "mailto:Dockery.Kathy@epa.gov"
            },
            "identifier": "{E2533854-DAF0-4774-909F-6554F74E4BFD}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7BE2533854-DAF0-4774-909F-6554F74E4BFD%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BE2533854-DAF0-4774-909F-6554F74E4BFD%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BE2533854-DAF0-4774-909F-6554F74E4BFD%7D",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OECA",
            "sourcetitle": "EPA Office of Enforcement and Compliance Assurance",
            "sourcefile": "https://edg.epa.gov/data/public/OECA/metadata/OECA.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "EPA iComplaints",
            "description": "The iComplaints system is an enterprise-level COTS (Commercial Off-The-Shelf) product that provides all of the funtionality required to collect, track, manage, process and report on information regarding internal EEO complaints in accordance with several civil rights laws and regulations, to include but not limited to, Title VII of the Civil Rights Act.",
            "keyword": [
                "sample",
                "eeo",
                "complaints",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Environmental Information (OEI)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Renee Clark, U.S. EPA Office of Environmental Information (OEI)",
                "hasEmail": "mailto:Clark.Renee@epa.gov"
            },
            "identifier": "51E75568-7D4B-4731-A35F-444CFCFE10C5",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B51E75568-7D4B-4731-A35F-444CFCFE10C5%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B51E75568-7D4B-4731-A35F-444CFCFE10C5%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B51E75568-7D4B-4731-A35F-444CFCFE10C5%7D",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "COMPLY Grantee Compliance Database",
            "description": "The Grantee Compliance Database Comply App is a comprehensive database for summarizing a wide range of grant recipient related activities. In addition to providing an overview of award information related to each grantee recipient, this database also stores historical information related to the recipient's training activities, indirect cost rate negotiations, pre-award certifications, post award monitoring plans, as well as on-site review, off-site review, and technical assistance activities. All advanced monitoring activities must be recorded in the system with an attached report to count as part of the Grantee Compliance Assistance Initiative as outlined in EPA Order 5700.6. The database tracks information on planned and actual On-Site Evaluative, off-Site Evaluative and/or On-Site Technical Assistance Visits conducted by each Grants Management and Program Office in the Agency. The primary objective of this database is to provide accurate information to EPA staff in Headquarters, Regional Program, and Grants Management Offices regarding compliance activities that each Program and Grants Management Office performs or plans to perform during any given calendar year.",
            "publisher": {
                "@type": "org:Organization",
                "name": "Office of Grants and Debarment (OMS/OGD)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "William Etheredge",
                "hasEmail": "mailto:etheredge.william@epa.gov"
            },
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "dataQuality": false,
            "keyword": [
                "Compliance",
                "environment",
                "grants",
                "United States",
                "Washington DC",
                "economy",
                "Financial",
                "Business Data"
            ],
            "modified": "2022-01-10",
            "identifier": "f06f7a30-f5e5-4ded-bc3e-767e4c2f6504",
            "accessLevel": "non-public",
            "rights": "EPA Category: Personally Identifiable Information (PII), NARA Category: Privacy",
            "license": "https://usepa-7291dac51b2899.sharepoint.com/sites/OARM/comply/comply-sp/#/home",
            "temporal": "2015-10-01/2022-01-10",
            "issued": "2021-06-01",
            "accrualPeriodicity": "R/P1D",
            "language": [
                "en-us"
            ],
            "landingPage": "https://usepa-7291dac51b2899.sharepoint.com/sites/OARM/comply/comply-sp/#/home",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://usepa-7291dac51b2899.sharepoint.com/sites/OARM/comply/comply-sp/#/home",
                    "title": "COMPLY Application URL",
                    "description": "Overview of award information related to each grantee recipient, this database also stores historical information related to the recipient's\ntraining activities, indirect cost rate negotiations, pre-award certifications, post award monitoring plans, as well as on-site review, off-site review, and technical assistance activities. All advanced monitoring activities must be recorded in the system with an attached report to count as part of the Grantee\nCompliance Assistance Initiative as outlined in EPA Order 5700.6. The database tracks information on planned and actual On-Site Evaluative, off-Site Evaluative and/or On-Site Technical Assistance Visits conducted by each Grants Management and Program Office in the Agency.",
                    "format": "SharePoint App"
                }
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Environmental Protection Agency Acquisition System",
            "description": "Automated contract writing and management system with configurable workflow.  EAS is built using a Commercial Off The Shelf Product (PRISM)that also includes the purchase request form and workflow.",
            "bureauCode": [
                "020:00"
            ],
            "dataQuality": true,
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office Of Mission Support (OMS) - Office of Acquisition Solutions (OAS)"
            },
            "contactPoint": {
                "fn": "Richard Belles",
                "hasEmail": "mailto:belles.richard@epa.gov",
                "@type": "vcard:Contact"
            },
            "keyword": [
                "Cleanup",
                "Emergency Response",
                "Facilities",
                "Management",
                "Regulatory",
                "Remediation",
                "Response",
                "Spills",
                "Washington DC",
                "North Carolina",
                "economy",
                "Acquisition",
                "buy",
                "contract",
                "purchase request",
                "requisition"
            ],
            "modified": "2021-11-24",
            "identifier": "e4a720e3-1ce2-4cc3-82cf-646f633a5b3e",
            "accessLevel": "public",
            "license": "https://easinfo.epa.gov/",
            "temporal": "2010-03/2021-12",
            "programCode": [
                "020:001"
            ],
            "primaryitinvestmentuii": "020-000016231",
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Cross-Media Electronic Reporting Rule",
            "description": "This system centralizes all data and reporting functions associated with applicants seeking to obtain Cross Media Electronic Reporting Rule CROMERR) certification for systems submitting data to EPA which require an electronic signature , facilitates agency review of those applications, increases accessibility to program information, and increases transparency in program management. This system is implemented as a workflow within the EPA\u2019s Business Application Platform (BAP) and exclusively uses its native capabilities.",
            "modified": "2021-12-17",
            "publisher": {
                "@type": "org:Organization",
                "name": "EPA-OMS-OIM-IEPB"
            },
            "contactPoint": {
                "fn": "Shirley Miller",
                "hasEmail": "mailto:miller.shirley@epa.gov",
                "@type": "vcard:Contact"
            },
            "identifier": "75f41ff9-881c-4b42-bafa-204357bb2799",
            "accessLevel": "public",
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "bureauCode": [
                "020:00"
            ],
            "temporal": "2005-10-13/2021-12-17",
            "dataQuality": false,
            "programCode": [
                "020:072"
            ],
            "keyword": [
                "Regulatory",
                "Permits",
                "Monitoring",
                "United States",
                "environment",
                "CROMERR",
                "Cross-Media Electronic Reporting Rule",
                "Electronic Reporting"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "EPA Acquisition Forecast Database",
            "description": "The EPA Acquisition Forecast Database was developed and is used to post the Agency's anticipated requirements and applicable acquisition strategies. ",
            "bureauCode": [
                "020:00"
            ],
            "dataQuality": true,
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office Of Mission Support (OMS) - Office of Acquisition Solutions (OAS)"
            },
            "contactPoint": {
                "fn": "Richard Belles",
                "hasEmail": "mailto:belles.richard@epa.gov",
                "@type": "vcard:Contact"
            },
            "keyword": [
                "Cleanup",
                "Emergency Response",
                "Facilities",
                "Management",
                "Regulatory",
                "Remediation",
                "Response",
                "Spills",
                "Washington DC",
                "North Carolina",
                "economy",
                "Acquisition",
                "forecast",
                "database",
                "procurement",
                "planning",
                "contracts"
            ],
            "modified": "2021-12-15",
            "identifier": "74b6f85f-2d8a-41f6-8fb9-10f66f2f0353",
            "accessLevel": "non-public",
            "rights": "EPA Category: Source Selection Information, NARA Category: Proprietary-Source Selection",
            "license": "https://ofmpub.epa.gov/apex/forecast/f?p=forecast",
            "temporal": "2017-06/2021-12",
            "programCode": [
                "020:001"
            ],
            "primaryitinvestmentuii": "020-000000088",
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "National Advanced Utility Metering",
            "description": "The National Advanced Utility Metering (NAUM) system is used to monitor utility consumption of EPA managed facilities required by the Energy Policy Act of 2005 (EPAct 2005), the Energy Independence and Security Act of 2007 (EISA 2007) and Executive Order 13514, along with other Presidential Memorandums that have established the need for additional water and utility metering.",
            "publisher": {
                "@type": "org:Organization",
                "name": "OMS/OA"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Mr. Jackie Brown",
                "hasEmail": "mailto:brown.jackie@epa.gov"
            },
            "bureauCode": [
                "020:00"
            ],
            "dataQuality": false,
            "keyword": [
                "Air",
                "Energy",
                "Water",
                "United States",
                "utilitiesCommunication",
                "Electric",
                "GAS"
            ],
            "modified": "2021-11-16",
            "identifier": "fc56c95c-e68d-41b6-8686-61cc6796b9cd",
            "accessLevel": "non-public",
            "rights": "EPA Category: Confidential Business Information, NARA Category: Proprietary-Manufacturer",
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "temporal": "2020-11-16/2022-11-16",
            "issued": "2020-11-16",
            "accrualPeriodicity": "R/P1D",
            "language": [
                "en"
            ],
            "conformsTo": "https://project-open-data.cio.gov/v1.1/schema/",
            "describedByType": "text/html",
            "landingPage": "https://v18h1n-naum033.aa.ad.epa.gov/Web/Auth?ReturnUrl=/Web/",
            "references": [
                "https://v18h1n-naum033.aa.ad.epa.gov/Web/Auth?ReturnUrl=/Web/"
            ],
            "programCode": [
                "020:000"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Tribal Consultation Tracking System",
            "description": "The Tribal Consultation Opportunities Tracking System (TCOTS) publicizes upcoming and current EPA consultation opportunities for tribal governments and Alaska Native Corporations. The goal of TCOTS is to provide early notification and transparency on EPA consultations.",
            "keyword": [
                "tcots",
                "tribal consultation",
                "tribal",
                "environment",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2001-07-25",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of International and Tribal Affairs"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Elias Abunassar, U.S. EPA Office of International and Tribal Affairs",
                "hasEmail": "mailto:abunassar.elias@epa.gov"
            },
            "identifier": "6B8E6259-95FF-4CFD-AD43-3FBD9E6D0A6C",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://www.epa.gov/aboutepa/about-office-international-and-tribal-affairs-oita"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://tcots.epa.gov",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://tcots.epa.gov",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI.json"
        },
        {
            "title": "State Grant Information Technology Application (SGITA)",
            "description": "The State Grant IT Application (SGITA) was created in response to Grants Policy Issuance (GPI) 11-03, State Grant Workplans and Progress Reports. The policy was developed by the State Grant Workplan Workgroup and was designed 1) enhance accountability for achieving grant performance objectives; 2) ensure that State grants are aligned with the Agency 2019 Strategic Plan; and 3) provide for more consistent performance reporting. To achieve those objectives, the GPI requires that workplans and associated progress reports prominently display three Essential Elements the EPA Strategic Plan Goal; the EPA Strategic Plan Objective; and Workplan Commitments plus time frame. The GPI applies to the fourteen State grant programs previously subject to the State Grant Performance Measures Template. It supplements, but in no way supersedes, existing workplan requirements in 40 C.F.R. Part 35 Subpart A. The effective date of the GPI is October 1, 2012. Awards made under Program Code for State and Tribal Underground Storage Tanks Program utilizing STAG funds are required to submit workplans and progress reports in SGITA. Those awards funded using LUST funds are not applicable to GPI 11-03. If an award has both STAG and LUST funds, those workplans and progress reports must be entered into SGITA. SGITA was developed from a requirement in the GPI stating that an application needed to be created to electronically store workplans and progress reports for the applicable programs. EPA Project Officers are to enter the information into SGITA as frequently as workplans and progress reports are required per the terms and conditions of the grant award. The application is accessible to EPA Personnel, OMB, and State users.",
            "bureauCode": [
                "020:00"
            ],
            "dataQuality": true,
            "publisher": {
                "@type": "org:Organization",
                "name": "Office of Mission Support\u202f(OMS)  -- Office of Grants and Debarment"
            },
            "contactPoint": {
                "fn": "Olayori Oluwo",
                "hasEmail": "mailto:oluwo.olayori@epa.gov",
                "@type": "vcard:Contact"
            },
            "keyword": [
                "environment",
                "Washington DC",
                "Progress Reports",
                "Workplans",
                "Grants Policy Issuance (GPI) 11-03",
                "EPA Project Officers",
                "EPA Personnel",
                "State users"
            ],
            "modified": "2021-08-14",
            "identifier": "fd45d11c-b236-455a-8ff6-380cc4ff5664",
            "accessLevel": "public",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "license": "https://sgita.epa.gov/ords/sgitapub/f?p=SGITAPUB:Home:",
            "temporal": "2020-10-01/2021-10-01",
            "accrualPeriodicity": "R/P4M",
            "landingPage": "https://sgita.epa.gov/ords/sgitapub/f?p=SGITAPUB:Home:",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://sgita.epa.gov/ords/sgitapub/f?p=SGITAPUB:Home:",
                    "title": "SGITA Home",
                    "description": "The State Grant IT Application (SGITA) was created in response to Grants Policy Issuance (GPI) 11-03, State Grant Workplans and Progress Reports. The policy was developed by the State Grant Workplan Workgroup and was designed 1) enhance accountability for achieving grant performance objectives; 2) ensure that State grants are aligned with the Agency 2019 Strategic Plan; and 3) provide for more consistent performance reporting. To achieve those objectives, the GPI requires that workplans and associated progress reports prominently display three Essential Elements: the EPA Strategic Plan Goal; the EPA Strategic Plan Objective; and Workplan Commitments plus time frame. The GPI applies to the fourteen State grant programs previously subject to the State Grant Performance Measures Template. It supplements, but in no way supersedes, existing workplan requirements in 40 C.F.R. Part 35 Subpart A. The effective date of the GPI is October 1, 2012. Awards made under Program Code for State and Tribal Underground Storage Tanks Program utilizing STAG funds are required to submit workplans and progress reports in SGITA. Those awards funded using LUST funds are not applicable to GPI 11-03. If an award has both STAG and LUST funds, those workplans and progress reports must be entered into SGITA\n\nSGITA was developed from a requirement in the GPI stating that an application needed to be created to electronically store workplans and progress reports for the applicable programs. EPA Project Officers are to enter the information into SGITA as frequently as workplans and progress reports are required per the terms and conditions of the grant award. The application is accessible to EPA Personnel, OMB, and State users."
                }
            ],
            "programCode": [
                "020:072"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI.json"
        },
        {
            "title": "Laws and Regulations Services (LRS)",
            "description": "LRS is a catalog of laws relevant to EPA, the regulations that implement those laws, and the EPA programs that oversee those regulations",
            "modified": "2021",
            "publisher": {
                "@type": "org:Organization",
                "name": "United States Environmental Protection Agency (EPA)"
            },
            "contactPoint": {
                "fn": "Justin Mattison",
                "hasEmail": "mailto:mattison.justin@epa.gov",
                "@type": "vcard:Contact"
            },
            "identifier": "0d18d90b-a358-4948-8fb5-2b72a728b061",
            "accessLevel": "public",
            "rights": "LRS is available to the public via web services ",
            "license": "https://sor-lrs-api.epa.gov/lrswebservices/swaggerV2",
            "bureauCode": [
                "020:00"
            ],
            "temporal": "2021/2025",
            "issued": "2015",
            "accrualPeriodicity": "R/P1W",
            "language": [
                "en-us"
            ],
            "dataQuality": false,
            "conformsTo": "https://sor.epa.gov/sor_internet/registry/lawsreg/home/overview/home.jsp",
            "describedBy": "https://sor-lrs-api.epa.gov/lrswebservices/swaggerV2",
            "describedByType": "text/html",
            "landingPage": "https://sor.epa.gov/sor_internet/registry/lawsreg/home/overview/home.jsp",
            "references": [
                "https://sor.epa.gov/sor_internet/registry/lawsreg/home/overview/home.jsp"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://sor-lrs-api.epa.gov/lrswebservices/swaggerV2",
                    "title": "LRS Web Services",
                    "description": "The LRS Web Services provide an interface to the System of Registries' Laws and Regulations Registry (LRS). LRS is a catalog of laws relevant to EPA, the regulations that implement those laws, and the EPA programs that oversee those regulations.The statutory and regulatory information is gleaned from the Code of Federal Regulations (CFR), published annually by the Government Publishing Office (GPO).",
                    "format": "API",
                    "describedBy": "https://sor-lrs-api.epa.gov/lrswebservices/swaggerV2",
                    "describedByType": "text/html",
                    "conformsTo": "https://sor-lrs-api.epa.gov/lrswebservices/swaggerV2"
                }
            ],
            "programCode": [
                "020:072"
            ],
            "keyword": [
                "Chemicals",
                "Pesticides",
                "regulatory",
                "Toxics",
                "United States",
                "environment",
                "law",
                "laws",
                "regulation",
                "regulations",
                "service",
                "services",
                "environmental",
                "code of federal regulations",
                "CFR",
                "government publishing office",
                "GPO"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI.json"
        },
        {
            "title": "Reference Data for Analytics",
            "description": "Collection of reference datasets for analytics applications.  These are lookup tables, crosswalks, and other useful datasets for connecting tables for analytics",
            "modified": "2021-01-28",
            "publisher": {
                "@type": "org:Organization",
                "name": "OMS-EI/OIM/IAASD"
            },
            "contactPoint": {
                "fn": "David G. Smith",
                "hasEmail": "mailto:smith.davidg@epa.gov",
                "@type": "vcard:Contact"
            },
            "identifier": "3e6f9173-790f-44a1-93e6-662662bcf67d",
            "accessLevel": "public",
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "bureauCode": [
                "020:00"
            ],
            "temporal": "2020/2021",
            "issued": "2021-01-28",
            "language": [
                "en-us"
            ],
            "dataQuality": false,
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://edap-oms-data-commons.s3.amazonaws.com/analytics-refdata/ACE-Ports.csv",
                    "format": "C Source File (.c)",
                    "title": "Data Commons",
                    "description": "Data Commons Reference Datasets",
                    "mediaType": "text/x-c"
                }
            ],
            "programCode": [
                "020:053"
            ],
            "keyword": [
                "Boundaries and Base Data",
                "United States",
                "biota",
                "economy",
                "imageryBaseMapsEarthCover",
                "location",
                "society",
                "structure",
                "transportation",
                "Ports",
                "Codesets",
                "reference"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Superfund Query",
            "description": "The Superfund Query allows users to retrieve data from the Comprehensive Environmental Response, Compensation, and Liability Information System (CERCLIS) database.",
            "keyword": [
                "datafinder",
                "emergencies and cleanup topics",
                "cleanup",
                "cleanup sites",
                "superfund",
                "environment",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Mission Support (OMS)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Shane Knipschild, U.S. EPA Office of Mission Support (OMS)",
                "hasEmail": "mailto:knipschild.shane@epa.gov"
            },
            "identifier": "F26474DB-5364-4173-89CB-3561096F8D9E",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7BF26474DB-5364-4173-89CB-3561096F8D9E%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BF26474DB-5364-4173-89CB-3561096F8D9E%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BF26474DB-5364-4173-89CB-3561096F8D9E%7D",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Analysis and Access",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIAA.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Toxics Release Inventory Chemical Hazard Information Profiles (TRI-CHIP) Dataset",
            "description": "The Toxics Release Inventory (TRI) Chemical Hazard Information Profiles (TRI-CHIP) dataset contains hazard information about the chemicals reported in TRI. Users can use this XML-format dataset to create their own databases and hazard analyses of TRI chemicals. The hazard information is compiled from a series of authoritative sources including the Integrated Risk Information System (IRIS). The dataset is provided as a downloadable .zip file that when extracted provides XML files and schemas for the hazard information tables.",
            "keyword": [
                "sample",
                "chemical",
                "compound",
                "pollution",
                "pollutant",
                "release",
                "inventory",
                "community",
                "right-to-know",
                "epcra",
                "hazard",
                "risk",
                "iris",
                "tri",
                "tri-chip",
                "toxicity",
                "human health",
                "toxics",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "David Turk, U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP)",
                "hasEmail": "mailto:Turk.David@epa.gov"
            },
            "identifier": "2DA57844-7EC1-4BAC-B521-3017862A1E70",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B2DA57844-7EC1-4BAC-B521-3017862A1E70%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B2DA57844-7EC1-4BAC-B521-3017862A1E70%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.htm",
            "landingPage": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B2DA57844-7EC1-4BAC-B521-3017862A1E70%7D",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/toxics-release-inventory-tri-program/tri-chip-download-page",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/toxics-release-inventory-tri-program/tri-chemical-hazard-information-profiles",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/toxics-release-inventory-tri-program/tri-chemical-hazard-information-profiles",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Analysis and Access",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIAA.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "ACRES - Brownfields Properties",
            "description": "Brownfields are real property, the expansion, redevelopment, or reuse of which may be complicated by the presence or potential presence of a hazardous substance, pollutant or contaminant.  This dataset shows the locations of sites, facilities and properties that have been contaminated by hazardous materials and are being, or have been, cleaned up under EPA Brownfields cleanup programs.",
            "keyword": [
                "sample",
                "epa",
                "brownfields",
                "assessment grant",
                "hazardous substance",
                "property redevelopment",
                "public health",
                "environment",
                "federal data download",
                "regulated sites",
                "hazardous",
                "contaminated",
                "polluted",
                "federal datasets",
                "land revitalization",
                "land redevelopment",
                "land reuse",
                "real property",
                "kmz",
                "xml",
                "shapefile",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Finance and Administration"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "FRS Support",
                "hasEmail": "mailto:FRS_Support@epa.gov"
            },
            "identifier": "681ECFBA-5BB4-421F-85F9-4F5CA963F8A3",
            "accessLevel": "public",
            "references": [
                "https://www.epa.gov/frs"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://www.epa.gov/frs",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/enviro/geospatial-data-download-service",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/brownfields/brownfields-grantee-reporting-assessment-cleanup-and-redevelopment-exchange-system-acres",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/brownfields/brownfields-grantee-reporting-assessment-cleanup-and-redevelopment-exchange-system-acres",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Complete 2010 Greenhouse Gas Data",
            "description": "These files contain the publicly available data from the GHG Reporting Program for 2010. This data includes non-confidential data reported by facilities that directly emit GHGs. The files also contain non-confidential information reported by suppliers of fossil fuels and industrial gases.  The files include data in both HTML (human readable) and XML format.   For more information on the GHG Reporting Program and this data, please visit http://epa.gov/ghgreporting",
            "keyword": [
                "sample",
                "epa",
                "oar",
                "oap",
                "e-ggrt",
                "electronic greenhouse gas reporting tool",
                "greenhouse gases",
                "ghg",
                "40 cfr part 98",
                "consolidated appropriations act 2008",
                "mandatory reporting of greenhouse gases rule",
                "office of air and radiation",
                "office of atmospheric programs",
                "environmental protection agency",
                "climate change",
                "global warming",
                "facilities",
                "power plants",
                "refineries",
                "chemicals",
                "landfills",
                "metals",
                "minerals",
                "pulp",
                "paper",
                "direct emitters",
                "suppliers",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Air and Radiation (OAR)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Kong Chiu, U.S. EPA Office of Air and Radiation (OAR)",
                "hasEmail": "mailto:Chiu.Kong@epa.gov"
            },
            "identifier": "907B4527-3C65-4782-B438-9402B6AA4012",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B907B4527-3C65-4782-B438-9402B6AA4012%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B907B4527-3C65-4782-B438-9402B6AA4012%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://www.epa.gov/ghgreporting/ghg-reporting-program-data-sets",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/ghgreporting/ghg-reporting-program-data-sets",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/ghgreporting/ghg-reporting-program-data-sets",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Envirofacts Data Warehouse",
            "description": "The Envirofacts Data Warehouse contains information from select EPA Environmental program office databases and provides access about environmental activities that may affect air, water, and land anywhere in the United States. The Envirofacts Warehouse supports its own web enabled tools as well as a host of other EPA applications.",
            "keyword": [
                "sample",
                "datafinder",
                "environmental media topics",
                "air",
                "water",
                "soils & land",
                "substances",
                "wastes",
                "airs",
                "bms",
                "brs",
                "cerclis",
                "erams",
                "gics",
                "igd",
                "oei",
                "pcs",
                "radnet",
                "rcrainfo",
                "rmp",
                "sdwis",
                "tri",
                "tri explorer",
                "tsca",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Finance and Administration (OFA)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Marty Martinez, U.S. EPA Office of Finance and Administration (OFA)",
                "hasEmail": "mailto:martinez.michael@epa.gov"
            },
            "identifier": "715D19E9-E38B-4C55-B250-E0E92E297D42",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B715D19E9-E38B-4C55-B250-E0E92E297D42%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B715D19E9-E38B-4C55-B250-E0E92E297D42%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://enviro.epa.gov/",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://enviro.epa.gov/",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://enviro.epa.gov/",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://enviro.epa.gov/",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "EPA Web Taxonomy",
            "description": "EPA's Web Taxonomy is a faceted hierarchical vocabulary used to tag web pages with terms from a controlled vocabulary. Tagging enables search and discovery of EPA's Web based information assests. EPA's Web Taxonomy is being provided in Simple Knowledge Organization System (SKOS) format. SKOS is a standard for sharing and linking knowledge organization systems that promises to make Federal terminology resources more interoperable.",
            "keyword": [
                "sample",
                "regulatory",
                "regulations",
                "legal",
                "enforcement",
                "compliance",
                "executive orders",
                "laws",
                "law enforcement",
                "regulatory compliance and enforcement",
                "legislative relations",
                "regulatory development",
                "community involvement",
                "community awareness",
                "environmental justice",
                "community assistance",
                "statutes",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Finance and Administration (OFA)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Michael Hessling, U.S. EPA Office of Finance and Administration (OFA)",
                "hasEmail": "mailto:Hessling.Michael@epa.gov"
            },
            "identifier": "9FC56CC1-2532-455A-9FA9-A58B0B35D304",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B9FC56CC1-2532-455A-9FA9-A58B0B35D304%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B9FC56CC1-2532-455A-9FA9-A58B0B35D304%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://www.epa.gov/webguide/epas-information-architecture-and-web-taxonomy",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/webguide/epas-information-architecture-and-web-taxonomy",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://sor.epa.gov/sor_internet/registry/termreg/searchandretrieve/taxonomies/search.do",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Grand Traverse Overall Supply Air Monitoring",
            "description": "EPA is conducting soil remediation: contaminated soils are being excavated and hauled offsite to an approved landfill. During soil excavation and backfill activities, we will collect air samples each day to monitor the ambient air for volatile organic compounds (VOCs). At the end of each day, the four summa canisters that have been taking readings will be sent to a lab for analysis. We are measuring approximately 30 different VOCs using the standard lab method TO-15. Results will be compared to the Michigan ambient air standards. Acronyms: AA: Ambient Air EA: Excavation Area PN: Perimeter North PNW: Perimeter Northwest PS: Perimeter South PSW: Perimeter Southwest ppb: Parts per billion RPD: Relative Percent Difference RL: Reporting Limit MDL: Method Detection Limit Qualifier definitions: *: Recovery or RPD exceeds control limits B: Compound was found in the blank and sample. J: Result is less than the RL but greater than or equal to the MDL and the concentration is an approximate value. U: Indicates the analyte was analyzed for but not detected.",
            "keyword": [
                "superfund",
                "grand traverse",
                "gtos",
                "greilickville",
                "air monitoring data",
                "soil excavation",
                "vocs",
                "interactive",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Mission Support (OMS)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Zach Scott, U.S. EPA Office of Mission Support (OMS)",
                "hasEmail": "mailto:Scott.Zachary@epa.gov"
            },
            "identifier": "F5B83FA8-3382-417B-A0D7-FFE38C37CFD2",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7BF5B83FA8-3382-417B-A0D7-FFE38C37CFD2%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BF5B83FA8-3382-417B-A0D7-FFE38C37CFD2%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BF5B83FA8-3382-417B-A0D7-FFE38C37CFD2%7D",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Information Collection Rule Federal Database",
            "description": "The Information Collection Rule (ICR) Federal database includes research data from an 18-month study of disinfection byproducts and microbial contaminants.",
            "keyword": [
                "sample",
                "substances",
                "pollutants & contaminants",
                "water pollutants",
                "drinking water contaminants",
                "environmental media topics",
                "water",
                "drinking water",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Water Resources Center, U.S. EPA Office of Water (OW)",
                "hasEmail": "mailto:center.water-resources@epa.gov"
            },
            "identifier": "8F6A6113-925B-405A-BC73-392CB7BFF0B6",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B8F6A6113-925B-405A-BC73-392CB7BFF0B6%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B8F6A6113-925B-405A-BC73-392CB7BFF0B6%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://archive.epa.gov/enviro/html/icr/web/html/index.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://archive.epa.gov/enviro/html/icr/web/html/index.html",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://archive.epa.gov/enviro/html/icr/web/html/index.html",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Error Tracking System",
            "description": "Error Tracking System is a database used to store & track error notifications sent by users of EPA's web site. ETS is managed by OIC/OEI. OECA's ECHO & OEI Envirofacts use it. Error notifications from EPA's home Page under \"Contact Us\" also uses it.",
            "keyword": [
                "sample",
                "error notifications",
                "error tracker",
                "integrated error correction process",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Finance and Administration (OFA)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "FRS , U.S. EPA Office of Finance and Administration (OFA)",
                "hasEmail": "mailto:FRS_Support@epa.gov"
            },
            "identifier": "2A9E5357-B564-42E8-AB2A-0DD75DCE4D4F",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B2A9E5357-B564-42E8-AB2A-0DD75DCE4D4F%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B2A9E5357-B564-42E8-AB2A-0DD75DCE4D4F%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://oaspub.epa.gov/enviro/ets_grab_error.smart_form",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://echo.epa.gov/help/how-to-report-error",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://echo.epa.gov/help/how-to-report-error",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://echo.epa.gov/help/how-to-report-error",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Substance Identification Information from EPA's Substance Registry",
            "description": "The Substance Registry Services (SRS) is the authoritative resource for basic information about substances of interest to the U.S. EPA and its state and tribal partners.  Substances, particularly chemicals, can have many valid synonyms.  For example, toluene, methyl benzene, and phenyl methane, are commonly used names for the same chemical.  EPA programs collect environmental data for this chemical using each of these names, plus others.  This diversity leads to problems when a user is looking for programmatic data for toluene but is unaware that the data is stored under the synonym methyl benzene.  For each substance, the SRS identifies the statutes, EPA programs, as well as organization external to EPA, that track or regulate that substance and the synonym used by that statute, EPA program or external organization.  Besides standardized information for each chemical, such as the Chemical Abstracts Services name and the Chemical Abstracts Number and the EPA Registry Name (the EPA standard name), the SRS also includes additional information, such as molecular weight and molecular formula.  Additionally, an SRS Internal Tracking Number uniquely identifies each substance, enabling cross-walking between synonyms. \n\nEPA is providing a large .ZIP file providing the SRS data in CSV format, and a separate small metadata file in XML containing the field names and definitions.",
            "keyword": [
                "sample",
                "biological",
                "cas",
                "chemical abstracts service",
                "business objects",
                "chemical",
                "chemical identification",
                "chemical id",
                "chemical nomenclature",
                "code set",
                "itis",
                "integrated taxonomic information system",
                "molecular formula",
                "molecular weight",
                "parameter",
                "physical",
                "registry",
                "registrar",
                "register",
                "registration",
                "sor",
                "standard",
                "substance",
                "substance classification",
                "substance identification",
                "substance lists",
                "substance registry system",
                "substance registry services",
                "srs",
                "synonym",
                "system of registries",
                "taxonomic serial number",
                "tsn",
                "virus",
                "web service",
                "epa",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Mission Support (OMS)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Phineas Lunger, U.S. EPA Office of Mission Support (OMS)",
                "hasEmail": "mailto:lunger.phineas@epa.gov"
            },
            "identifier": "0AEA7FA5-98C2-4175-AE3E-E70947456E86",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B0AEA7FA5-98C2-4175-AE3E-E70947456E86%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B0AEA7FA5-98C2-4175-AE3E-E70947456E86%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://iaspub.epa.gov/sor_internet/registry/substreg/home/overview/home.do",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://iaspub.epa.gov/sor_internet/registry/substreg/home/overview/home.do",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://iaspub.epa.gov/sor_internet/registry/substreg/home/overview/home.do",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Summary 2010 Greenhouse Gas Data",
            "description": "This file contains a summary of the publicly available data from the GHG Reporting Program for 2010. This data includes non-confidential data reported by facilities that directly emit GHGs. The files also contain non-confidential information reported by suppliers of fossil fuels and industrial gases. This excel file contains the same information available in the Data Publication Tool. The file contains the most important, high-level information reported by direct emitters and suppliers and can be easily sorted to respond to many common queries.  Please visit https://www.epa.gov/ghgreporting for more information on the data.",
            "keyword": [
                "sample",
                "epa",
                "oar",
                "oap",
                "e-ggrt",
                "electronic greenhouse gas reporting tool",
                "greenhouse gases",
                "ghg",
                "40 cfr part 98",
                "consolidated appropriations act 2008",
                "mandatory reporting of greenhouse gases rule",
                "office of air and radiation",
                "office of atmospheric programs",
                "environmental protection agency",
                "climate change",
                "global warming",
                "facilities",
                "power plants",
                "refineries",
                "chemicals",
                "landfills",
                "metals",
                "minerals",
                "pulp",
                "paper",
                "direct emitters",
                "suppliers",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Air and Radiation (OAR)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Kong Chiu, U.S. EPA Office of Air and Radiation (OAR)",
                "hasEmail": "mailto:Chiu.Kong@epa.gov"
            },
            "identifier": "59A02659-36C4-4B19-B5F5-2E0852C0F929",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B59A02659-36C4-4B19-B5F5-2E0852C0F929%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B59A02659-36C4-4B19-B5F5-2E0852C0F929%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B59A02659-36C4-4B19-B5F5-2E0852C0F929%7D",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/sites/production/files/2015-10/ghgp_data_2010_10_7_15.xlsx",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/ghgreporting/ghgrp-reported-data",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/ghgreporting/ghgrp-reported-data",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Materials Discarded in the U.S. Municipal Waste Stream, 1960 to 2009 (in tons)",
            "description": "The U.S. Environmental Protection Agency (EPA) has collected and reported data on the generation and disposal of waste in the United States for more than 30 years. We use this information to measure the success of waste reduction and recycling programs across the country. Our trash, or municipal solid waste (MSW), is made up of the things we commonly use and then throw away. These materials include items such as packaging, food scraps, grass clippings, sofas, computers, tires, and refrigerators. MSW does not include industrial, hazardous, or construction waste. The data on Materials Discarded in the Municipal Waste Stream, 1960 to 2009, provides estimated data in thousands of tons discarded after recycling and compost recovery for the years 1960, 1970, 1980, 1990, 2000, 2005, 2007, 2008, and 2009. In this data set, discards include combustion with energy recovery. This data table does not include construction & demolition debris, industrial process wastes, or certain other wastes. The \"Other\" category includes electrolytes in batteries and fluff pulp, feces, and urine in disposable diapers. Details may not add to totals due to rounding.",
            "keyword": [
                "sample",
                "materials generation",
                "waste generation",
                "recycling rate",
                "landfill disposal",
                "recycling data",
                "waste characterization",
                "durable goods",
                "plastic recycling",
                "plastic bag recycling",
                "municipal solid waste disposal",
                "msw characterization",
                "paper recycling",
                "metals recycling",
                "composting data",
                "composting rate",
                "food recovery",
                "recycling tons",
                "amount recycled",
                "amount landfilled",
                "amount composted",
                "interactive",
                "epa",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Land and Emergency Management (OLEM)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Zach Scott, U.S. EPA Office of Land and Emergency Management (OLEM)",
                "hasEmail": "mailto:Scott.Zachary@epa.gov"
            },
            "identifier": "E5DE559C-4258-496E-AA1D-71FCBA48161F",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BE5DE559C-4258-496E-AA1D-71FCBA48161F%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7BE5DE559C-4258-496E-AA1D-71FCBA48161F%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://www.epa.gov/transforming-waste-tool",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/transforming-waste-tool",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/transforming-waste-tool",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Greenhouse Gas Data Publication Tool",
            "description": "This tool to gives you access to greenhouse gas data reported to EPA by large facilities and suppliers in the United States through EPA's Greenhouse Gas Reporting Program. The tool allows you to view data in several formats including maps, tables, charts and graphs for individual facilities or groups of facilities. You can search the data set for individual facilities by name or location or filter the data set by state or county, industry sectors and sub-sectors, annual facility emission thresholds, and greenhouse gas type.  For more information on the GHG Reporting Program and this data, please visit https://www.epa.gov/ghgreporting",
            "keyword": [
                "sample",
                "epa",
                "oar",
                "oap",
                "e-ggrt",
                "electronic greenhouse gas reporting tool",
                "greenhouse gases",
                "ghg",
                "40 cfr part 98",
                "consolidated appropriations act 2008",
                "mandatory reporting of greenhouse gases rule",
                "office of air and radiation",
                "office of atmospheric programs",
                "environmental protection agency",
                "climate change",
                "global warming",
                "facilities",
                "power plants",
                "refineries",
                "chemicals",
                "landfills",
                "metals",
                "minerals",
                "pulp",
                "paper",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Air and Radiation (OAR)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Kong Chiu, U.S. EPA Office of Air and Radiation (OAR)",
                "hasEmail": "mailto:Chiu.Kong@epa.gov"
            },
            "identifier": "FE489855-C43D-493B-BF08-6CE2B5E69330",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BFE489855-C43D-493B-BF08-6CE2B5E69330%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7BFE489855-C43D-493B-BF08-6CE2B5E69330%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BFE489855-C43D-493B-BF08-6CE2B5E69330%7D",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://ghgdata.epa.gov/ghgp/main.do",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/ghgreporting",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/ghgreporting",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Substance Registry Services (SRS)",
            "description": "The Substance Registry System (SRS) is EPA's central system for information about regulated and monitored substances.",
            "keyword": [
                "sample",
                "datafinder",
                "substances",
                "chemicals",
                "pollutants & contaminants",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Finance and Administration (OFA)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Phineas Lunger, U.S. EPA Office of Finance and Administration (OFA)",
                "hasEmail": "mailto:lunger.phineas@epa.gov"
            },
            "identifier": "6786D3DA-E9A5-43BD-A5E9-2EEC2E75E78E",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B6786D3DA-E9A5-43BD-A5E9-2EEC2E75E78E%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B6786D3DA-E9A5-43BD-A5E9-2EEC2E75E78E%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B6786D3DA-E9A5-43BD-A5E9-2EEC2E75E78E%7D",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://ofmpub.epa.gov/sor_internet/registry/substreg/home/overview/home.do",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://ofmpub.epa.gov/sor_internet/registry/substreg/LandingPage.do",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://ofmpub.epa.gov/sor_internet/registry/substreg/LandingPage.do",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "EPA Envirofacts API",
            "description": "Envirofacts integrates information from a variety of EPA's environmental databases. Each of these databases contains information about facilities that are required to report activity to a state or federal system. Using this API, you can retrieve information.",
            "keyword": [
                "sample",
                "envirofacts",
                "epa",
                "air",
                "water",
                "land",
                "toxic",
                "pollution",
                "data",
                "warehouse",
                "api",
                "environment",
                "facility",
                "facilities",
                "emission",
                "tri",
                "xml",
                "csv",
                "json",
                "xls",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Finance and Administration (OFA)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Marty Martinez, U.S. EPA Office of Finance and Administration (OFA)",
                "hasEmail": "mailto:martinez.michael@epa.gov"
            },
            "identifier": "A4EBFA50-EC19-4F00-9866-C09D01B951E0",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7BA4EBFA50-EC19-4F00-9866-C09D01B951E0%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BA4EBFA50-EC19-4F00-9866-C09D01B951E0%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://enviro.epa.gov/",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/enviro/web-services",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/enviro/envirofacts-data-service-api",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/enviro/envirofacts-data-service-api",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Terminology Services",
            "description": "Terminology Services provides tools and services that enable vocabulary development, maintenance and provisioning for the enterprise.",
            "keyword": [
                "sample",
                "etss",
                "semantic web",
                "ts",
                "terminology services",
                "glossary",
                "ontology",
                "registry",
                "taxonomy",
                "term",
                "terminology",
                "thesaurus",
                "trs",
                "vocabulary",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Finance and Administration (OFA)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Phineas Lunger, U.S. EPA Office of Finance and Administration (OFA)",
                "hasEmail": "mailto:lunger.phineas@epa.gov"
            },
            "identifier": "F180B542-3D54-4CBA-BD71-47EC423ECE65",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BF180B542-3D54-4CBA-BD71-47EC423ECE65%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7BF180B542-3D54-4CBA-BD71-47EC423ECE65%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BF180B542-3D54-4CBA-BD71-47EC423ECE65%7D",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://iaspub.epa.gov/sor_internet/registry/termreg/searchandretrieve/termsandacronyms/search.do",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://iaspub.epa.gov/sor_internet/registry/termreg/home/whatisterminology/",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://iaspub.epa.gov/sor_internet/registry/termreg/searchandretrieve/termsandacronyms/search.do",
                    "mediaType": "application/octet-stream"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://iaspub.epa.gov/sor_internet/registry/termreg/home/whatisterminology/",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Registry of EPA Applications, Models, and Databases",
            "description": "READ is EPA's authoritative source for information about Agency information resources, including applications/systems, datasets and models. READ is one component of the System of Registries (SoR).",
            "keyword": [
                "sample",
                "it system",
                "omb a11",
                "omb a130",
                "registry of epa applications",
                "models",
                "and databases",
                "dataset",
                "information resource",
                "model",
                "system inventory",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Finance and Administration (OFA)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Kim Balassiano, U.S. EPA Office of Finance and Administration (OFA)",
                "hasEmail": "mailto:balassiano.kim@epa.gov"
            },
            "identifier": "101513F0-7F51-4CAB-966B-15E7794EA775",
            "accessLevel": "public",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B101513F0-7F51-4CAB-966B-15E7794EA775%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B101513F0-7F51-4CAB-966B-15E7794EA775%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://ofmpub.epa.gov/sor_internet/registry/systmreg/searchandretrieve/basic/search.do",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://ofmpub.epa.gov/sor_internet/registry/systmreg/searchandretrieve/basic/search.do",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/read/",
                    "mediaType": "application/octet-stream",
                    "format": "API"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/read/",
                    "mediaType": "application/octet-stream"
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Facility Registry Service (FRS)",
            "description": "The Facility Registry Service (FRS) provides an integrated source of comprehensive (air, water, and waste) environmental information about facilities across EPA, states, tribes and other \"places\" of environmental interest such as schools and landfills.",
            "keyword": [
                "datafinder",
                "environmental media topics",
                "air",
                "environmental media topics",
                "water",
                "substances",
                "wastes",
                "regulatory & industrial topics",
                "regulated facilities",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2013-09-24",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "US Environmental Protection Agency"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "FRS Support",
                "hasEmail": "mailto:FRS_Support@epa.gov"
            },
            "identifier": "B158161D-F639-4A93-BF7C-D454C80F7C92",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BB158161D-F639-4A93-BF7C-D454C80F7C92%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7BB158161D-F639-4A93-BF7C-D454C80F7C92%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.htm",
            "landingPage": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BB158161D-F639-4A93-BF7C-D454C80F7C92%7D",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/frs",
                    "title": "FRS Home Page"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/frs/frs-data-resources",
                    "title": "FRS Data Resources Page",
                    "description": "Links to FRS data available as Web Services, Prepackaged Downloads, and Custom Downloads."
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/frs/frs-documentation",
                    "title": "FRS Documentation Page",
                    "description": "Information about data sources, flows, schemas, dictionaries, and standards."
                }
            ],
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "title": "Federally Recognized Tribes",
            "description": "This dataset provides authoritative names for federally recognized tribes as defined by the Bureau of Indian Affairs.  EPA maintains this data (1978 - Present) and makes it available via the TRIBES Names Services",
            "publisher": {
                "@type": "org:Organization",
                "name": "EPA Office of Mission Support "
            },
            "contactPoint": {
                "fn": "Justin Mattison",
                "hasEmail": "mailto:mattison.justin@epa.gov",
                "@type": "vcard:Contact"
            },
            "keyword": [
                "Human",
                "Management",
                "Environmental Justice",
                "United States",
                "society",
                "Native American",
                "tribes",
                "indian"
            ],
            "modified": "2021-02-11",
            "identifier": "3f4bd197-b312-4a0c-b179-6ea798f52ac4",
            "accessLevel": "public",
            "license": "https://edg.epa.gov/EPA_Data_License.htm",
            "bureauCode": [
                "020:00"
            ],
            "temporal": "1978-01-01/2021-04-13",
            "issued": "2021-01-28",
            "accrualPeriodicity": "R/P1Y",
            "language": [
                "en-us"
            ],
            "dataQuality": true,
            "landingPage": "https://www.epa.gov/data-standards/tribes-services-tribal-identifier-data-standard#file-150427",
            "references": [
                "http://www.exchangenetwork.net/data-exchange/epa-tribal-identification-tribes/"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/sites/production/files/2021-03/tribe_entity_mapping_2021-03-04.xlsx",
                    "format": "This is a link to a spreadsheet that contains the BIA Tribe Names, BIA tribe codes, and EPA internal identifiers for each tribe.  Tribe names are tracked from 1978 - present.",
                    "title": "Tribe Entity Mapping",
                    "description": "List of BIA tribe names, BIA codes (where we have them), and EPA identifiers",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
                    "describedBy": "https://www.epa.gov/sites/production/files/2015-06/documents/tribalidenversion2.2a_10_02_14.pdf",
                    "describedByType": "application/pdf"
                }
            ],
            "programCode": [
                "020:042"
            ],
            "primaryitinvestmentuii": "020-000016006",
            "geo": "No",
            "holdren": "No",
            "ORG": "OMS",
            "sourcetitle": "EPA Office of Environmental Information, Office of Information Collection",
            "sourcefile": "https://edg.epa.gov/data/public/OEI/metadata/OEI-OIC.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of General Counsel (OGC)"
            },
            "accessLevel": "public",
            "description": "The Office of General Counsel (OGC) has an ongoing business process engineering and business process automation initiative which has helped the office reduce administrative labor costs while increasing employee effectiveness. Supporting this effort is a system of automated routines accessible through a \"portal' interface called \"OGC Dashboard.\" The dashboard helps OGC track work progress, legal case load, written work products such as legal briefs and advice, and scheduling processes such as employee leave plans (via calendar) and travel compensatory time off.",
            "keyword": [
                "legal",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "OGC Dashboard",
            "issued": "2014-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
                "020:00"
            ],
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B836352F6-A37C-4FDD-9C98-F7501C454273%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B836352F6-A37C-4FDD-9C98-F7501C454273%7D"
            ],
            "accrualPeriodicity": "irregular",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:salzman.andrew@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Andrew Salzman, U.S. EPA Office of General Counsel (OGC)"
            },
            "identifier": "836352F6-A37C-4FDD-9C98-F7501C454273",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OGC",
            "sourcetitle": "EPA Office of General Counsel",
            "sourcefile": "https://edg.epa.gov/data/public/OGC/metadata/OGC.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of General Counsel (OGC)"
            },
            "accessLevel": "public",
            "description": "Case and Administrative Support Tools (CAST) is the secure portion of the Office of General Counsel (OGC) Dashboard business process automation tool used to help reduce office administrative labor costs while increasing employee effectiveness. CAST supports business functions which rely on and store Privacy Act sensitive data (PII). Specific business processes included in CAST (and respective PII) are: -Civil Rights Cast Tracking (name, partial medical history, summary of case, and case correspondance). -Employment Law Case Tracking (name, summary of case). -Federal Tort Claims Act Incident Tracking (name, summary of incidents). -Ethics Program Support Tools and Tracking (name, partial financial history). -Summer Honors Application Tracking (name, home address, telephone number, employment history). -Workforce Flexibility Initiative Support Tools (name, alternative workplace phone number). -Resource and Personnel Management Support Tools (name, partial employment and financial history).",
            "keyword": [
                "legal",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "Case and Administrative Support Tools",
            "issued": "2014-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
                "020:00"
            ],
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B4296E18F-AC00-4F64-929A-34173D146387%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B4296E18F-AC00-4F64-929A-34173D146387%7D"
            ],
            "accrualPeriodicity": "irregular",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:Murphy.MichaelP@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Michael P Murphy, U.S. EPA Office of General Counsel (OGC)"
            },
            "identifier": "4296E18F-AC00-4F64-929A-34173D146387",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "OGC",
            "sourcetitle": "EPA Office of General Counsel",
            "sourcefile": "https://edg.epa.gov/data/public/OGC/metadata/OGC.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Toxicity Reference Database",
            "description": "The Toxicity Reference Database (ToxRefDB) contains approximately 30 years and $2 billion worth of animal studies. ToxRefDB allows scientists and the interested public to search and download thousands of animal toxicity testing results for hundreds of chemicals that were previously found only in paper documents. Currently, there are 474 chemicals in ToxRefDB, primarily the data rich pesticide active ingredients, but the number will continue to expand.",
            "keyword": [
                "datafinder",
                "substances",
                "chemicals",
                "human health",
                "health risks",
                "exposure",
                "environment",
                "environment",
                "united states",
                "health"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Research and Development (ORD) - National Center for Computational Toxicology (NCCT)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Matt Martin, U.S. EPA Office of Research and Development (ORD) - National Center for Computational Toxicology (NCCT)",
                "hasEmail": "mailto:martin.matt@epa.gov"
            },
            "identifier": "8D1F4382-424A-492E-8D2E-ADC046140BBB",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B8D1F4382-424A-492E-8D2E-ADC046140BBB%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B8D1F4382-424A-492E-8D2E-ADC046140BBB%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "ORD",
            "sourcetitle": "EPA Office of Research and Development",
            "sourcefile": "https://edg.epa.gov/data/public/ORD/metadata/ORD.json"
        },
        {
            "title": "Characterization Factors for Construction Material EPD Indicators (ISO21930-LCIA-US) v0.1",
            "description": "This dataset contains characterization factors (CFs) for the five mandatory life cycle impact assessment (LCIA) categories required in ISO 21930:2017: \n1.\tGreenhouse gases (GHG), which is incorrectly named \u2018GWP\u2019 in the standard,\n2.\tOzone Depletion Potential (ODP),\n3.\tEutrophication Potential (EP),\n4.\tAcidification Potential (AP), and\n5.\tPhotochemical Ozone Formation Potential (POCP)\nThese CFs are appropriate for use with life cycle inventory data for activities occurring within the United States. \nThe short name for the dataset is ISO21930-LCIA-US v0.1.\nThe characterization factors, with the exception of GHGs, are identical to the those currently in TRACI v2.1 for the corresponding impact categories. The four TRACI v2.1 impact categories have the same names as ISO 21930:2017 with the exception of POCP, which is called \u201csmog formation\u201d in TRACI v2.1. The characterization factors for GHGs are the 100-year (GWP-100) GWPs from the International Panel for Climate Change (IPCC)\u2019s 5th Assessment Report (AR5) report. \nThe names for the chemicals, release contexts, units and IDs are from the Federal LCA Elementary Flow List (FEDEFL) v1.2. These datasets were created using the LCIA Formatter v1.1.2 (https://github.com/USEPA/LCIAformatter).\nFormats\nDatasets are provided in simple tables in Excel, in the openLCA JSON-LD format using Federal LCA Commons standards, and in Apache parquet format.  The fields in the Excel and identical parquet versions use the LCIAmethod format fields: https://github.com/USEPA/LCIAformatter/blob/master/format%20specs/LCIAmethod.md\n1.\tZip archives of JSON files in the JSON-LD schema: a file type associated with the openLCA schema. Two JSON-LD versions are provided. \na.\t\u201cISO21930-LCIA-USv0.1_noflows_json-ld.zip\u201d is without flow objects. \nb.\t\u201cISO21930-LCIA-USv0.1_wprefflows_json-ld.zip\u201d is with flow objects of preferred flows from the FEDEFL.\nSee usage notes below. \n2.\tExcel and parquet: tabular format according to schema from the LCIA formatter, with additional fields added:\no\t\u201csource_method\u201d: indicates the original method source for the indicator (e.g., TRACI 2.1 or IPCC)\no\t\u201csource_indicator\u201d: indicates the name of the indicator in its original form (e.g. Smog Formation)\no\t\u201ccategory\u201d: indicates the desired parent folder name for the impact category (shown as \u201cEPA EPD in Figure 1)\nUsage\nGenerally, in all formats, the CFs can be multiplied by kg (or unit specified in the denominator) of the relevant chemical emitted to calculate the potential impact value for a given impact category for that relevant chemical. If no CF exists for a chemical in a given impact category, it is not considered to have an impact in that category.\nThe parquet format is most efficient for import into applications or scripts using languages like Python and R.\nThe Zip archives of JSON-LD files can be loaded into openLCA or other LCA or EPD software supporting that format. When loaded into openLCA (via JSON-LD), the method shows as a separate impact assessment method. Individual indicators are categorized within the EPA EPD category.\nFor introduction to importing a dataset into openLCA we recommend this training video from the National Renewable Energy Laboratory. https://youtu.be/YLao5jC5b_0?si=H0SNZ_ufOwInkgCF&t=48\nThe version with no flows is designed to import in a database that already has FEDEFL elementary flows or no more modeling is to be done that would use any new flows. It will only create the LCIA method.\nThe version with flows can be imported into a new \u2018empty\u2019 database and it will create not just the LCIA method but all associated flows and more basic objects like units and flow properties. It can be used when no process data that you wish to model has been created yet and/or if you want to have a full import of all relevant elementary flows.\n",
            "bureauCode": [
                "020:00"
            ],
            "dataQuality": true,
            "publisher": {
                "@type": "org:Organization",
                "name": "Office of Chemical Safety and Pollution Prevention"
            },
            "contactPoint": {
                "fn": "Low Embodied Carbon Team",
                "hasEmail": "mailto:embodiedcarbon@epa.gov",
                "@type": "vcard:Contact"
            },
            "keyword": [
                "Air",
                "Water",
                "Impact",
                "United States",
                "environment",
                "LCIA",
                "Environmental product declarations",
                "Low embodied carbon",
                "carbon label"
            ],
            "modified": "2024-04-26",
            "identifier": "9bf03ab6-dd13-4d5a-a92e-b33f9d77a100",
            "accessLevel": "public",
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "temporal": "2000-01-01/2030-01-01",
            "issued": "2024-04",
            "accrualPeriodicity": "R/P6M",
            "language": [
                "en-us"
            ],
            "conformsTo": "https://greendelta.github.io/olca-schema/",
            "describedBy": "https://github.com/USEPA/LCIAformatter/blob/master/format%20specs/LCIAmethod.md",
            "landingPage": "https://www.epa.gov/greenerproducts/tools-resources",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://dmap-data-commons-ord.s3.amazonaws.com/lciafmt/ISO21930-LCIA-US/ISO21930-LCIA-USv0.1.xlsx",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://dmap-data-commons-ord.s3.amazonaws.com/lciafmt/ISO21930-LCIA-US/ISO21930-LCIA-USv0.1_v1.1.2_e7c9269.parquet",
                    "mediaType": "application/octet-stream"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://dmap-data-commons-ord.s3.amazonaws.com/lciafmt/ISO21930-LCIA-US/ISO21930-LCIA-USv0.1_noflows_json-ld.zip",
                    "mediaType": "application/zip"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://dmap-data-commons-ord.s3.amazonaws.com/lciafmt/ISO21930-LCIA-US/ISO21930-LCIA-USv0.1_wprefflows_json-ld.zip",
                    "mediaType": "application/zip"
                }
            ],
            "references": [
                "https://downloads.regulations.gov/EPA-HQ-OPPT-2024-0075-0002/content.pdf"
            ],
            "programCode": [
                "020:085"
            ],
            "primaryitinvestmentuii": "020-000030304",
            "geo": "No",
            "holdren": "No",
            "ORG": "ORD",
            "sourcetitle": "EPA Office of Research and Development",
            "sourcefile": "https://edg.epa.gov/data/public/ORD/metadata/ORD.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Research and Development"
            },
            "accessLevel": "public",
            "description": "The Environmental Monitoring and Assessment Program (EMAP) was a national research program run by EPA\u2019s Office of Research and Development from 1990 to 2008 to develop the tools necessary to monitor and assess the status and trends of national ecological resources. Initially, resources included estuaries and coastal waters, wadeable streams, lakes, wetlands, forests, agroecosystems, arid areas, and landscape ecology. Later, this was narrowed down to just the aquatic resources. EMAP collected field data from 1990 to 2006. EMAP's goal was to develop the scientific understanding for translating environmental monitoring data from multiple spatial and temporal scales into assessments of current ecological condition and forecasts of future risks to our natural resources. EMAP aimed to advance the science of ecological monitoring and ecological risk assessment, guide national monitoring with improved scientific understanding of ecosystem integrity and dynamics, and demonstrate multi-agency monitoring through large regional projects. EMAP developed indicators to monitor the condition of ecological resources. EMAP also investigated designs that addressed the acquisition, aggregation, and analysis of multiscale and multitier data. Monitoring of the nation\u2019s aquatic resources is now being routinely conducted by the National Aquatic Resource Surveys, run by EPA\u2019s Office of Water.",
            "keyword": [
                "environmental monitoring",
                "environmental assessment",
                "estuaries",
                "coastal waters",
                "streams",
                "lakes",
                "wetlands",
                "U.S."
            ],
            "title": "Environmental Monitoring and Assessment Program (EMAP)",
            "language": [
                "en-US"
            ],
            "distribution": [
                {
                    "description": "Data from the US EPA's Environmental Monitoring and Assessment Program, 1990-2006",
                    "title": "EMAP_archive1990-2006",
                    "format": "text/csv",
                    "mediaType": "application/zip",
                    "downloadURL": "https://edg.epa.gov/data/PUBLIC/ORD/NHEERL/EMAP_archive1990-2006.zip",
                    "@type": "dcat:Distribution"
                }
            ],
            "temporal": "1990/2006",
            "describedByType": "text/csv",
            "modified": "2008-06-30",
            "dataQuality": true,
            "theme": [
                "monitoring",
                "estuaries",
                " coastal waters",
                " streams",
                " lakes",
                " wetlands"
            ],
            "bureauCode": [
                "020:00"
            ],
            "issued": "2006-12-31",
            "references": [
                "https://archive.epa.gov/emap/archive-emap/web/html/index.html"
            ],
            "spatial": "USA",
            "programCode": [
                "020:079"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:Harwell.linda@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Linda Harwell"
            },
            "identifier": "40C37FCC-7D79-4FD6-BDBF-29127BD9B606",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "ORD",
            "sourcetitle": "EPA Office of Research and Development",
            "sourcefile": "https://edg.epa.gov/data/public/ORD/metadata/ORD.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Surplus Precipitation",
            "description": "Surplus Precipitation (mm): precipitation minus potential evaporation within catchment",
            "publisher": {
                "@type": "org:Organization",
                "name": "US Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory (NHEERL)"
            },
            "contactPoint": {
                "fn": "Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov",
                "@type": "vcard:Contact"
            },
            "keyword": [
                "Ecosystem",
                "environment",
                "Surface Water",
                "Modeling",
                "Monitoring",
                "Natural Resources",
                "United States",
                "Alaska",
                "Hawaii",
                "Alabama",
                "Arizona",
                "Arkansas",
                "California",
                "Colorado",
                "Connecticut",
                "Delaware",
                "Florida",
                "Georgia",
                "Idaho",
                "Illinois",
                "Indiana",
                "Iowa",
                "Kansas",
                "Kentucky",
                "Louisiana",
                "Maine",
                "Maryland",
                "Massachusetts",
                "Michigan",
                "Minnesota",
                "Mississippi",
                "Missouri",
                "Montana",
                "Nebraska",
                "Nevada",
                "New Hampshire",
                "New Jersey",
                "New York",
                "North Carolina",
                "North Dakota",
                "Ohio",
                "Oklahoma",
                "Oregon",
                "Pennsylvania",
                "Rhode Island",
                "South Carolina",
                "South Dakota",
                "Tennessee",
                "Texas",
                "Utah",
                "Vermont",
                "Virginia",
                "Washington",
                "West Virginia",
                "Wisconsin",
                "Wyoming",
                "Water",
                "NHDPlus V21",
                "Precipitation"
            ],
            "bureauCode": [
                "020:00"
            ],
            "dataQuality": true,
            "modified": "2021",
            "identifier": "04760b79-3aae-407a-a830-f0dd04c90739",
            "accessLevel": "public",
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "temporal": "2021-09-09/2021-09-09",
            "programCode": [
                "020:096"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "ORD",
            "sourcetitle": "EPA Office of Research and Development",
            "sourcefile": "https://edg.epa.gov/data/public/ORD/metadata/ORD.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "ToxCast Phase I",
            "description": "Background: Chemical toxicity testing is being transformed by advances in biology and computer modeling,  concerns over animal use and the thousands of environmental chemicals lacking toxicity data. EPA's ToxCast program aims to address these concerns by screening and prioritizing chemicals for potential human toxicity using in vitro assays and in silico approaches. Objectives: This project aims to evaluate the use of in vitro assays for understanding the types of molecular and pathway perturbations caused by environmental chemicals and to build initial prioritization models of in vivo toxicity. Methods: We tested 309 mostly pesticide active chemicals in 467 assays across 9 technologies,  including high-throughput cell-free assays and cell-based assays in multiple human primary cells and cell lines,  plus rat primary hepatocytes. Both individual and composite scores for effects on genes and pathways were analyzed. Results: Chemicals display a broad spectrum of activity at the molecular and pathway levels. Many expected interactions are seen,  including endocrine and xenobiotic metabolism enzyme activity. Chemicals range in promiscuity across pathways,  from no activity to affecting dozens of pathways. We find a statistically significant inverse association between the number of pathways perturbed by a chemical at low in vitro concentrations and the lowest in vivo dose at which a chemical causes toxicity. We also find associations between a small set in vitro assays and rodent liver lesion formation. Conclusions: This approach promises to provide meaningful data on the thousands of untested environmental chemicals,  and to guide targeted testing of environmental contaminants.",
            "keyword": [
                "chemical safety",
                "chemical safety research",
                "chemicals",
                "chemical testing",
                "innovative chemical testing",
                "computational toxicology",
                "chemical screening",
                "toxcast",
                "tox21",
                "epa research",
                "chemical science",
                "chemical health effects",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Research and Development (ORD) - National Center for Computational Toxicology (NCCT)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Richard Judson, U.S. EPA Office of Research and Development (ORD) - National Center for Computational Toxicology (NCCT)",
                "hasEmail": "mailto:judson.richard@epa.gov"
            },
            "identifier": "227B16A3-AEE1-4724-A91B-D4119F5A2C1B",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B227B16A3-AEE1-4724-A91B-D4119F5A2C1B%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B227B16A3-AEE1-4724-A91B-D4119F5A2C1B%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "ORD",
            "sourcetitle": "EPA Office of Research and Development",
            "sourcefile": "https://edg.epa.gov/data/public/ORD/metadata/ORD.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Interactive Chemical Safety for Sustainablity Toxicity Forecaster Dashboard",
            "description": "EPA researchers have been using advances in computational toxicology to address lack of data on the thousands of chemicals. EPA released chemical data on 1,800 chemicals. The 1,800 chemicals were screened in more than 800 rapid, automated tests (called high-throughput screening assays) to determine potential human health effects.  The data is available through the interactive Chemical Safety for Sustainability Dashboards (iCSS dashboard) and the complete data sets are also available for download.",
            "keyword": [
                "chemical safety",
                "chemical safety research",
                "chemicals",
                "chemical testing",
                "innovative chemical testing",
                "computational toxicology",
                "chemical screening",
                "toxcast",
                "actor",
                "chemical health effects",
                "chemical science",
                "epa research",
                "high-throughput data",
                "in vitro data",
                "tox21",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Research and Development (ORD) - National Center for Computational Toxicology (NCCT)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Matt Martin, U.S. EPA Office of Research and Development (ORD) - National Center for Computational Toxicology (NCCT)",
                "hasEmail": "mailto:martin.matt@epa.gov"
            },
            "identifier": "9E05E004-0752-4881-B1EF-27456E0EE6CA",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B9E05E004-0752-4881-B1EF-27456E0EE6CA%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B9E05E004-0752-4881-B1EF-27456E0EE6CA%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "ORD",
            "sourcetitle": "EPA Office of Research and Development",
            "sourcefile": "https://edg.epa.gov/data/public/ORD/metadata/ORD.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Exposure Forecaster",
            "description": "The Exposure Forecaster Database (ExpoCastDB) is EPA's database for aggregating chemical exposure information and can be used to help with chemical exposure predictions. The database currently includes biomonitoring exposure data from three studies: the American Healthy Homes Survey, the First National Environmental Health Survey of Child Care Centers and the Children's Total Exposure to Persistent Pesticides and Other Persistent Organic Pollutants study. Data include the amounts of chemicals found in food, drinking water, air, dust indoor surfaces and urine. The database will eventually include high-throughput exposure predictions for thousands of chemicals based on manufacture and use information. EPA researchers developed high-throughput exposure models to predict exposures for 1,763 chemicals using production volume, environmental fate and transport models, and a simple indicator of consumer product use.The model is being improved by adding more refined indoor and consumer use information since these are also large determinants of exposure. As these models are refined and more exposure data is collected, it will be added to ExpoCastDB.",
            "keyword": [
                "chemical safety",
                "chemical safety research",
                "chemicals",
                "chemical testing",
                "innovative chemical testing",
                "computational toxicology",
                "chemical screening",
                "toxcast",
                "tox21",
                "epa research",
                "chemical health effects",
                "consumer product",
                "consumer product database",
                "chemical exposure",
                "expocast",
                "high-throughput exposure prediction",
                "wal-mart data",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Research and Development (ORD) - National Center for Computational Toxicology (NCCT)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "John Wambaugh, U.S. EPA Office of Research and Development (ORD) - National Center for Computational Toxicology (NCCT)",
                "hasEmail": "mailto:wambaugh.john@epa.gov"
            },
            "identifier": "33778226-2C82-4EFE-A310-1225F2911A07",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B33778226-2C82-4EFE-A310-1225F2911A07%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B33778226-2C82-4EFE-A310-1225F2911A07%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "ORD",
            "sourcetitle": "EPA Office of Research and Development",
            "sourcefile": "https://edg.epa.gov/data/public/ORD/metadata/ORD.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Distributed Structure Searchable Toxicity",
            "description": "The Distributed Structure Searchable Toxicity (DSSTox) online resource provides high quality chemical structures and annotations in association with toxicity data. It helps to build a data foundation for improved structure-activity relationships and predictive toxicology. DSSTox publishes summarized chemical activity representations for structure-activity modeling and provides a structure browser. This tool also houses the chemical inventories for the ToxCast and Tox21 projects.",
            "keyword": [
                "chemical safety",
                "chemical safety research",
                "chemicals",
                "chemical testing",
                "innovative chemical testing",
                "computational toxicology",
                "chemical screening",
                "toxcast",
                "tox21",
                "epa research",
                "chemical health effects",
                "animal toxicity data",
                "animal toxicity",
                "animal studies",
                "chemical structure",
                "chemical annotations",
                "structure activity",
                "qsar",
                "dsstox",
                "distributed structure searchable toxicity",
                "epa",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Research and Development (ORD) - National Center for Computational Toxicology (NCCT)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Tony Williams, U.S. EPA Office of Research and Development (ORD) - National Center for Computational Toxicology (NCCT)",
                "hasEmail": "mailto:williams.antony@epa.gov"
            },
            "identifier": "0E749283-2A82-489B-A90D-067686928631",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B0E749283-2A82-489B-A90D-067686928631%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B0E749283-2A82-489B-A90D-067686928631%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "ORD",
            "sourcetitle": "EPA Office of Research and Development",
            "sourcefile": "https://edg.epa.gov/data/public/ORD/metadata/ORD.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Consumer Product Category Database",
            "description": "The Chemical and Product Categories database (CPCat) catalogs the use of over 40,000 chemicals and their presence in different consumer products. The chemical use information is compiled from multiple sources while product information is gathered from publicly available Material Safety Data Sheets (MSDS). EPA researchers are evaluating the possibility of expanding the database with additional product and use information.",
            "keyword": [
                "sample",
                "chemical safety",
                "chemical safety research",
                "chemicals",
                "chemical testing",
                "innovative chemical testing",
                "computational toxicology",
                "chemical screening",
                "toxcast",
                "tox21",
                "epa research",
                "chemical science",
                "chemical health effects",
                "consumer product",
                "consumer product database",
                "chemical exposure",
                "expocast",
                "high-throughput exposure prediction",
                "wal-mart data",
                "epa",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Research and Development (ORD) - National Center for Computational Toxicology (NCCT)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Richard Judson, U.S. EPA Office of Research and Development (ORD) - National Center for Computational Toxicology (NCCT)",
                "hasEmail": "mailto:judson.richard@epa.gov"
            },
            "identifier": "90CDFB11-E94E-4E84-942C-5B3D2B5ED0CD",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B90CDFB11-E94E-4E84-942C-5B3D2B5ED0CD%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B90CDFB11-E94E-4E84-942C-5B3D2B5ED0CD%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "ORD",
            "sourcetitle": "EPA Office of Research and Development",
            "sourcefile": "https://edg.epa.gov/data/public/ORD/metadata/ORD.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Aggregated Computational Toxicology Online Resource",
            "description": "Aggregated Computational Toxicology Online Resource (AcTOR) is EPA's online aggregator of all the public sources of chemical toxicity data. ACToR aggregates data from over 1,000 public sources on over 500,000 chemicals and is searchable by chemical name, other identifiers and by chemical structure. It can be used to query a specific chemical and find all publicly available hazard, exposure and risk assessment data. It also provides access to EPA's ToxCast, ToxRefDB, DSSTox, Dashboard and DSSTox data.",
            "keyword": [
                "chemical safety",
                "chemical safety research",
                "chemicals",
                "chemical testing",
                "innovative chemical testing",
                "computational toxicology",
                "chemical screening",
                "toxcast",
                "tox21",
                "epa research",
                "chemical science",
                "chemical health effects",
                "animal toxicity",
                "animal toxicity data",
                "animal studies",
                "in vitro data",
                "epa",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Research and Development (ORD) - National Center for Computational Toxicology (NCCT)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Richard Judson, U.S. EPA Office of Research and Development (ORD) - National Center for Computational Toxicology (NCCT)",
                "hasEmail": "mailto:judson.richard@epa.gov"
            },
            "identifier": "46942636-82FB-46BD-B044-52EFEC632D00",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B46942636-82FB-46BD-B044-52EFEC632D00%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B46942636-82FB-46BD-B044-52EFEC632D00%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "ORD",
            "sourcetitle": "EPA Office of Research and Development",
            "sourcefile": "https://edg.epa.gov/data/public/ORD/metadata/ORD.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Ecotoxicology Database (ECOTOX)",
            "description": "The Ecotoxicology Database (ECOTOX) provides information on effects of single chemicals to ecologically-relevant species.",
            "keyword": [
                "datafinder",
                "substances",
                "chemicals",
                "environmental media topics",
                "species",
                "substances",
                "pesticides",
                "environment",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Research and Development (ORD)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Jennifer Olker, ORD-CCTE-GLTED-TTB",
                "hasEmail": "mailto:olker.jennifer@epa.gov"
            },
            "identifier": "B68D31D1-D035-4678-8B0C-324CC433DBD4",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7BB68D31D1-D035-4678-8B0C-324CC433DBD4%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BB68D31D1-D035-4678-8B0C-324CC433DBD4%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "landingPage": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BB68D31D1-D035-4678-8B0C-324CC433DBD4%7D",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "ORD",
            "sourcetitle": "EPA Office of Research and Development",
            "sourcefile": "https://edg.epa.gov/data/public/ORD/metadata/ORD.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "ToxCast/ToxRefDB",
            "distribution": [
                {
                    "accessURL": "https://www.epa.gov/comptox-tools/exploring-toxcast-data",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/csv"
                }
            ],
            "description": "ToxCast is used as a cost-effective approach for efficiently prioritizing the toxicity testing of thousands of chemicals. It uses data from state-of-the-art high throughput screening (HTS) bioassay and builds computational models to forecast potential chemical toxicity in humans. ToxRefDB stores data related to ToxCast.",
            "keyword": [
                "substances",
                "chemicals",
                "human health",
                "health risks",
                "exposure",
                "human health",
                "health risks",
                "toxicity",
                "threshold level",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Chemical Safety and Pollution Prevention (OCSPP)"
            },
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        },
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                    "format": "API",
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                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/node/276204",
                    "format": "Comma-Separated Values (.csv)",
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            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
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            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Canal Density",
            "description": "This dataset represents canal density within individual, local and accumulated upstream catchments for NHDPlusV2 Waterbodies.  Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. This data set is derived from NHDPlusV2 line features classified as canal, ditch, or pipeline in the conterminous United States. Canal density describes how many kilometers of canal exist in a square kilometer. A raster was produced using the ArcGIS Line Density Tool to form the landscape layer for analysis. The (kilometer of canal/square kilometer) was summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.",
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                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
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                "montana",
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                "nevada",
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                "new mexico",
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                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "identifier": "e0398045-0643-492e-960c-d882b6519585",
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            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
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                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Dam Density and Storage Volume",
            "description": "This dataset represents the dam density and storage volumes within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Inventory of Dams (NID). Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. The NID database contains information about the dam2019s location, size, purpose, type, last inspection, regulatory facts, and other technical data. Structures on streams reduce the longitudinal and lateral hydrologic connectivity of the system. For example, impoundments above dams slow stream flow, cause deposition of sediment and reduce peak flows. Dams change both the discharge and sediment supply of streams, causing channel incision and bed coarsening downstream. Downstream areas are often sediment deprived, resulting in degradation, i.e., erosion of the stream bed and stream banks. This database was improved upon by locations verified by work from the USGS National Map (Jeff Simley Group). It was observed that some dams, some of them major and which do exist, were not part of the 2009 NID, but were represented in the USGS National Map dataset, and had been in the 2006 NID.  Approximately 1,100 such dams were added, based on the USGS National Map lat/long and the 2006 NID attributes (dam height, storage, etc.) Finally, as clean-up, a) about 600 records with duplicate NIDID were removed, and b) about 300 records were removed which represented the same location of the same dam but with a different NIDID, for the largest dams (did visual check of dams with storage above 5000 acre feet and are likely duplicated - about the 10,000 largest dams).   The (dams/catchment) and (dam_storage/catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type.",
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                "colorado",
                "connecticut",
                "delaware",
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                "florida",
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                "louisiana",
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                "minnesota",
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                "missouri",
                "montana",
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                "nevada",
                "new hampshire",
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                "north carolina",
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                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
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                "texas",
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                "vermont",
                "virginia",
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                "west virginia",
                "wisconsin",
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                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
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            ],
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            ],
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        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Facility Registry Services (FRS) : Toxic Release Inventory (TRI) , National Pollutant Discharge Elimination System (NPDES) , and Superfund Sites",
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                "new jersey",
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                "new york",
                "north carolina",
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                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
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                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
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            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
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            },
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            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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                    "description": "LakeCat currently contains over 300 metrics that include local catchment (Cat), watershed (Ws), and special metrics. See Geospatial Framework and Terms in the ReadMe for definitions of the terms \u2018catchment\u2019 and \u2018watershed\u2019 as used with the LakeCat Dataset. An additional metric, inStreamCat, indicates whether the variable was pulled from the StreamCat Dataset or calculated with a geospatial framework that was developed for LakeCat.\n\nThese metrics are available for 378,088 lakes and their associated catchments across the conterminous US. LakeCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
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                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/node/276204",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "Facility Registry Services (FRS) : Toxic Release Inventory (TRI) , National Pollutant Discharge Elimination System (NPDES) , and Superfund Sites",
                    "description": "This dataset represents the estimated density of georeferenced sites within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the EPA's Facility Registry Services (FRS) geodatabase. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. The FRS geodatabase is a collection of point locations of facilities or sites subject to environmental regulation. TRI, NPDES, and Superfund sites were extracted individually to summarize for each in the resulting . Csv. The (site locations / catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a points data type (see Data Structure and Attribute Information for a description of each metric).",
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            ],
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            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Forest Loss By Year 2001 to 2013",
            "description": "This dataset represents the characterization of global forest extent and change by year from 2001 through 2013 within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the Global Forest Change 2000, 2013, 2013. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. These data are based on global tree cover loss for the period from 2001 to 2013 at a spatial resolution of 30m. The analysis used to create the landscape layer is based on Landsat data. Forest loss was defined as a stand-replacement disturbance or the complete removal of tree cover canopy at the Landsat pixel scale. This landscape layer is a disaggregation of total forest loss to annual time scales. Encoded as either 0 (no loss) or else a value in the range 1, 201313, representing loss detected primarily in the year 2001, 2013, 2013, respectively. The forest loss by year characteristics (%) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
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                "arizona",
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                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
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                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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                    "description": "LakeCat currently contains over 300 metrics that include local catchment (Cat), watershed (Ws), and special metrics. See Geospatial Framework and Terms in the ReadMe for definitions of the terms \u2018catchment\u2019 and \u2018watershed\u2019 as used with the LakeCat Dataset. An additional metric, inStreamCat, indicates whether the variable was pulled from the StreamCat Dataset or calculated with a geospatial framework that was developed for LakeCat.\n\nThese metrics are available for 378,088 lakes and their associated catchments across the conterminous US. LakeCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/node/276204",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "Forest Loss By Year 2001 to 2013",
                    "description": "This dataset represents the characterization of global forest extent and change by year from 2001 through 2013 within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the Global Forest Change 2000, 2013, 2013. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. These data are based on global tree cover loss for the period from 2001 to 2013 at a spatial resolution of 30m. The analysis used to create the landscape layer is based on Landsat data. Forest loss was defined as a stand-replacement disturbance or the complete removal of tree cover canopy at the Landsat pixel scale. This landscape layer is a disaggregation of total forest loss to annual time scales. Encoded as either 0 (no loss) or else a value in the range 1, 201313, representing loss detected primarily in the year 2001, 2013, 2013, respectively. The forest loss by year characteristics (%) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
            "describedByType": "text/html",
            "issued": "2015-04-23",
            "language": [
                "en-US"
            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
            "references": [
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            ],
            "theme": [
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            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (LakeCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: GeoChemPhys",
            "description": "This dataset represents geochemical or geophysical attributes in surface or near surface geology within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. For information regarding how the Landscape layers were created see https://www.sciencebase.gov/catalog/item/53481333e4b06f6ce034aae7. Landscape Layers are partitioned into 4 tables based on the location of no-data cells within their rasters to correctly reflect the PctFull attributes within each table.",
            "keyword": [
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                "monitoring",
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                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
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                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "identifier": "DC063B04-19B9-4172-9D07-37B118DB935A",
            "accessLevel": "public",
            "bureauCode": [
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            "programCode": [
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
                    "title": "LakeCat Dataset",
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                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/node/276204",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "GeoChemPhys",
                    "description": "This dataset represents geochemical or geophysical attributes in surface or near surface geology within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. For information regarding how the Landscape layers were created see https://www.sciencebase.gov/catalog/item/53481333e4b06f6ce034aae7. Landscape Layers are partitioned into 4 tables based on the location of no-data cells within their rasters to correctly reflect the PctFull attributes within each table.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
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            ],
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            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
            "describedByType": "text/html",
            "issued": "2015-04-23",
            "language": [
                "en-US"
            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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            ],
            "theme": [
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            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (LakeCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Mine Density: Active Mines and Mineral Plants in the US",
            "description": "This dataset represents mine density within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on mine plants and operations monitored by the USGS National Minerals Information Center. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table.  The National Minerals Information Center canvasses the nonfuel mining and mineral-processing industry in the United States for data on mineral production, consumption, recycling, stocks, and shipments. Mine plants and operations for commodities are expressed as points in a shapefile that was downloaded from the USGS directly. The (mines / catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type.",
            "keyword": [
                "inlandwaters",
                "ecosystem",
                "environment",
                "monitoring",
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                "usa",
                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
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            },
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            "temporal": "2015/2030",
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                    "@type": "dcat:Distribution",
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                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
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                    "format": "Comma-Separated Values (.csv)",
                    "title": "Mine Density: Active Mines and Mineral Plants in the US",
                    "description": "This dataset represents mine density within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on mine plants and operations monitored by the USGS National Minerals Information Center. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table.  The National Minerals Information Center canvasses the nonfuel mining and mineral-processing industry in the United States for data on mineral production, consumption, recycling, stocks, and shipments. Mine plants and operations for commodities are expressed as points in a shapefile that was downloaded from the USGS directly. The (mines / catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
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            ],
            "theme": [
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            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (LakeCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: National Anthropogenic Barrier Dataset",
            "description": "This dataset represents the dam density and storage volumes within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Anthropogenic Barrier Dataset (NABD). Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. The main objective of this project was to develop a dataset of large, anthropogenic barriers that are spatially linked to the National Hydrography Dataset Plus Version 1 (NHDPlusV1) for the conterminous U.S. to facilitate GIS analyses based on the NHDPlusV1/NHD and NID datasets. To meet this objective, Michigan State University conducted a spatial linkage of the point dataset of the 2009 National Inventory of Dams (NID) created by the U.S. Army Corps of Engineers (USACE) to the NHDPlusV1/NHD. The pool of dam data included were modified based on 1) dam removals that occurred after development of the 2009 NID and 2) the identification of duplicate dam records along state boundaries (cases where more than one state reported the same dam). The US Geological Survey (USGS) Aquatic GAP Program supported this work. The (dams/catchment) and (dam_storage/catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type.",
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                "usa",
                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
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                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "identifier": "8A4F8423-0D37-4F28-938A-E5522BFEAA96",
            "accessLevel": "public",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
                    "title": "LakeCat Dataset",
                    "description": "LakeCat currently contains over 300 metrics that include local catchment (Cat), watershed (Ws), and special metrics. See Geospatial Framework and Terms in the ReadMe for definitions of the terms \u2018catchment\u2019 and \u2018watershed\u2019 as used with the LakeCat Dataset. An additional metric, inStreamCat, indicates whether the variable was pulled from the StreamCat Dataset or calculated with a geospatial framework that was developed for LakeCat.\n\nThese metrics are available for 378,088 lakes and their associated catchments across the conterminous US. LakeCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/node/276204",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "National Anthropogenic Barrier Dataset",
                    "description": "This dataset represents the dam density and storage volumes within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Anthropogenic Barrier Dataset (NABD). Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. The main objective of this project was to develop a dataset of large, anthropogenic barriers that are spatially linked to the National Hydrography Dataset Plus Version 1 (NHDPlusV1) for the conterminous U.S. to facilitate GIS analyses based on the NHDPlusV1/NHD and NID datasets. To meet this objective, Michigan State University conducted a spatial linkage of the point dataset of the 2009 National Inventory of Dams (NID) created by the U.S. Army Corps of Engineers (USACE) to the NHDPlusV1/NHD. The pool of dam data included were modified based on 1) dam removals that occurred after development of the 2009 NID and 2) the identification of duplicate dam records along state boundaries (cases where more than one state reported the same dam). The US Geological Survey (USGS) Aquatic GAP Program supported this work. The (dams/catchment) and (dam_storage/catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
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            "issued": "2015-04-23",
            "language": [
                "en-US"
            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
            "references": [
                "https://www.epa.gov/node/276204",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=8A4F8423-0D37-4F28-938A-E5522BFEAA96"
            ],
            "theme": [
                "environment"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (LakeCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: National Atmospheric Deposition Program National Trends Network - Nitrogen Deposition",
            "description": "This dataset represents deposition estimates of nutrients within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Atmospheric Deposition Program. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. The National Trends Network provides long-term records of precipitation chemistry across the United States. Individual rasters describe ammonium, nitrate, inorganic nitrogen, and average sulfur/nitrogen deposition per year. See Source Info for links to NADP. The nitrogen and sulfur characteristics (kg N/ha/yr) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
            "keyword": [
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                "environment",
                "monitoring",
                "natural resources",
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                "united states",
                "usa",
                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "identifier": "49DA91A5-0D29-41E4-96BD-93987FF85979",
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                "020:00"
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            "programCode": [
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
                    "title": "LakeCat Dataset",
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                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/node/276204",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "National Atmospheric Deposition Program National Trends Network - Nitrogen Deposition",
                    "description": "This dataset represents deposition estimates of nutrients within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Atmospheric Deposition Program. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. The National Trends Network provides long-term records of precipitation chemistry across the United States. Individual rasters describe ammonium, nitrate, inorganic nitrogen, and average sulfur/nitrogen deposition per year. See Source Info for links to NADP. The nitrogen and sulfur characteristics (kg N/ha/yr) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
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            "dataQuality": true,
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            "theme": [
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            "geo": "No",
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            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (LakeCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: National Coal Resource Dataset System",
            "description": "This dataset represents coal mine density and storage volumes within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Coal Resource Dataset System (NCRDS). Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. The National Coal Resources Data System (NCRDS) began as a cooperative venture between the USGS and State geological agencies in 1975 and focused on the stratigraphy and chemistry of coal. Web pages have been developed to query data within both the USCOAL database and a subset of the USCHEM database. The USTRAT database, due to its size and complexity, was first made available in 2011 for direct query through web pages. The (coal mine sites/AreaSqKm) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type.",
            "keyword": [
                "inlandwaters",
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                "environment",
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                "california",
                "colorado",
                "connecticut",
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                "district of columbia",
                "florida",
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                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
                "@type": "vcard:Contact",
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            },
            "identifier": "a440e12b-9875-4b88-b7af-f095c79f891b",
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                "020:00"
            ],
            "programCode": [
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            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
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                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/node/276204",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "National Coal Resource Dataset System",
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                    "mediaType": "text/csv",
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                    "describedByType": "text/html"
                }
            ],
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            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
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            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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            "geo": "No",
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            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (LakeCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: National Elevation Dataset",
            "description": "This dataset represents the elevation values within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Elevation Dataset. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. NHDPlusV2 records NED snapshot dates as follows: August 2010 - VPU04 February 2011 - VPUs 05, 06 June 2011 - VPU 17 August 2011 - VPUs 07, 10L, 10U, 11, 18 December 2011 - VPUs 01, 02, 03N, 03S, 03W, 08, 09, 12, 13, 14, 15, 16 The elevation characteristics were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
            "keyword": [
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                "colorado",
                "connecticut",
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                "illinois",
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                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
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                "nebraska",
                "nevada",
                "new hampshire",
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                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
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            "programCode": [
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
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                },
                {
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                    "format": "Comma-Separated Values (.csv)",
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                    "description": "This dataset represents the elevation values within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Elevation Dataset. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. NHDPlusV2 records NED snapshot dates as follows: August 2010 - VPU04 February 2011 - VPUs 05, 06 June 2011 - VPU 17 August 2011 - VPUs 07, 10L, 10U, 11, 18 December 2011 - VPUs 01, 02, 03N, 03S, 03W, 08, 09, 12, 13, 14, 15, 16 The elevation characteristics were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
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                }
            ],
            "accrualPeriodicity": "R/P3Y",
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            "geo": "No",
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            "sourcetitle": "EPA Office of Water (LakeCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: National Land Cover Database",
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                "delaware",
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                "kansas",
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                "louisiana",
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                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
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                "missouri",
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                "nebraska",
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                "new hampshire",
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                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
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                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
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            ],
            "modified": "2023-11-13",
            "publisher": {
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            },
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                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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                    "description": "LakeCat currently contains over 300 metrics that include local catchment (Cat), watershed (Ws), and special metrics. See Geospatial Framework and Terms in the ReadMe for definitions of the terms \u2018catchment\u2019 and \u2018watershed\u2019 as used with the LakeCat Dataset. An additional metric, inStreamCat, indicates whether the variable was pulled from the StreamCat Dataset or calculated with a geospatial framework that was developed for LakeCat.\n\nThese metrics are available for 378,088 lakes and their associated catchments across the conterminous US. LakeCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/node/276204",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "National Land Cover Database",
                    "description": "This dataset represents the land cover data within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the NLCD. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. This data set is derived from the NLCD raster composed of 16 land cover classes (categorical data type) for the conterminous USA. Four classes of the NLCD were excluded as they were specific to Alaska land covers.  This raster was produced based on a decision-tree classification of 2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019 Landsat satellite data. This dataset will include additional years as they become available. ",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
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            "issued": "2015-04-23",
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        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: National Land Cover Database - Impervious Surfaces",
            "description": "This dataset represents the impervious surface coefficients within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the National Land Cover Data. AOI boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-AOI boundaries and then links them through an off-network flow table. This data set is derived from the NLCD Impervious Surfaces raster which describes percent imperviousness (continuous data type). Values indicate the degree to which the area is composed of impervious anthropogenic materials (e.g., parking surfaces, roads, building roofs). This raster was produced based on a decision-tree classification of 2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019 Landsat satellite data. This dataset will include additional years as they become available. ",
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                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
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                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
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            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
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            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Nonnative LANDFIRE Vegetation",
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        },
        {
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                "florida",
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                "idaho",
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                "iowa",
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                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
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                "vermont",
                "virginia",
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                "west virginia",
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            "accessLevel": "public",
            "bureauCode": [
                "020:00"
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            "programCode": [
                "020:072"
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
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                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
                    "title": "LakeCat Dataset",
                    "description": "LakeCat currently contains over 300 metrics that include local catchment (Cat), watershed (Ws), and special metrics. See Geospatial Framework and Terms in the ReadMe for definitions of the terms \u2018catchment\u2019 and \u2018watershed\u2019 as used with the LakeCat Dataset. An additional metric, inStreamCat, indicates whether the variable was pulled from the StreamCat Dataset or calculated with a geospatial framework that was developed for LakeCat.\n\nThese metrics are available for 378,088 lakes and their associated catchments across the conterminous US. LakeCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
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                    "format": "Comma-Separated Values (.csv)",
                    "title": "Pesticide",
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            "theme": [
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            ],
            "geo": "No",
            "holdren": "No",
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            "sourcetitle": "EPA Office of Water (LakeCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
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            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: PRISM Normals Data",
            "description": "This dataset represents climate observations within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the PRISM Climate Group. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. PRISM is a set of monthly, yearly, and single-event gridded data products of mean temperature and precipitation, max/min temperatures, and dewpoints, primarily for the United States. In-situ point measurements are ingested into the PRISM (Parameter elevation Regression on Independent Slopes Model) statistical mapping system. The PRISM products use a weighted regression scheme to account for complex climate regimes associated with orography, rain shadows, temperature inversions, slope aspect, coastal proximity, and other factors. These data are summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.",
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                "massachusetts",
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                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
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                "texas",
                "utah",
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                "wisconsin",
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            "modified": "2023-11-13",
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            },
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                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "identifier": "C1AED92E-568B-47C6-9B51-272462155A76",
            "accessLevel": "public",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
                    "title": "LakeCat Dataset",
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                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/node/276204",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "PRISM Normals Data",
                    "description": "This dataset represents climate observations within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the PRISM Climate Group. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. PRISM is a set of monthly, yearly, and single-event gridded data products of mean temperature and precipitation, max/min temperatures, and dewpoints, primarily for the United States. In-situ point measurements are ingested into the PRISM (Parameter elevation Regression on Independent Slopes Model) statistical mapping system. The PRISM products use a weighted regression scheme to account for complex climate regimes associated with orography, rain shadows, temperature inversions, slope aspect, coastal proximity, and other factors. These data are summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
            "describedByType": "text/html",
            "issued": "2015-04-23",
            "language": [
                "en-US"
            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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            ],
            "theme": [
                "environment"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (LakeCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Road and Stream Intersections",
            "description": "This dataset represents the density of road and stream crossings within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. The landscape layer (raster) was developed by James Falcone of the USGS. US Census TIGER 2000 line files of roads and the NHDPlusV1 line files of all streams were converted to 30-meter grids where the presence of a street or stream was a 1 and everything else a 0.  These were intersected and anything that was a 1 in both grids is the result. The density of road and stream crossings (crossings / square kilometer) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
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                "alabama",
                "arizona",
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                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "identifier": "BFB01111-7676-4E96-B9BD-7DC4E5A3168B",
            "accessLevel": "public",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
                    "title": "LakeCat Dataset",
                    "description": "LakeCat currently contains over 300 metrics that include local catchment (Cat), watershed (Ws), and special metrics. See Geospatial Framework and Terms in the ReadMe for definitions of the terms \u2018catchment\u2019 and \u2018watershed\u2019 as used with the LakeCat Dataset. An additional metric, inStreamCat, indicates whether the variable was pulled from the StreamCat Dataset or calculated with a geospatial framework that was developed for LakeCat.\n\nThese metrics are available for 378,088 lakes and their associated catchments across the conterminous US. LakeCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/node/276204",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "Road and Stream Intersections",
                    "description": "This dataset represents the density of road and stream crossings within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. The landscape layer (raster) was developed by James Falcone of the USGS. US Census TIGER 2000 line files of roads and the NHDPlusV1 line files of all streams were converted to 30-meter grids where the presence of a street or stream was a 1 and everything else a 0.  These were intersected and anything that was a 1 in both grids is the result. The density of road and stream crossings (crossings / square kilometer) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
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            ],
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            "dataQuality": true,
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            "issued": "2015-04-23",
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                "en-US"
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            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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            "theme": [
                "environment"
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            "holdren": "No",
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            "sourcetitle": "EPA Office of Water (LakeCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Runoff",
            "description": "This dataset represents the estimated surface water runoff within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. The landscape layer (raster) was developed with a water-balance model developed by Dave Wolock of the USGS and is detailed further in the paper \"Independent effects of temperature and precipitation on modeled runoff in the conterminous United States\". McCabe and Wolock[2011] Runoff is defined as the flow per unit area delivered to streams and rivers in units of millimeters per month.   The runoff estimates were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
            "keyword": [
                "inlandwaters",
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                "environment",
                "monitoring",
                "natural resources",
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                "alabama",
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                "colorado",
                "connecticut",
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                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
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                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
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            },
            "identifier": "15669D84-E7E5-4E53-9FC3-0E022B6F40C0",
            "accessLevel": "public",
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                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
                    "title": "LakeCat Dataset",
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                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/node/276204",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "Runoff",
                    "description": "This dataset represents the estimated surface water runoff within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. The landscape layer (raster) was developed with a water-balance model developed by Dave Wolock of the USGS and is detailed further in the paper \"Independent effects of temperature and precipitation on modeled runoff in the conterminous United States\". McCabe and Wolock[2011] Runoff is defined as the flow per unit area delivered to streams and rivers in units of millimeters per month.   The runoff estimates were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
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            ],
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            "language": [
                "en-US"
            ],
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            ],
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                "environment"
            ],
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            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (LakeCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: State Soil Geographic Database (STATSGO) (KKACT)",
            "description": "This dataset represents the soil characteristics within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the STATSGO landscape rasters. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. This data set is derived from the STATSGO landscape rasters for the conterminous USA. Individual rasters (Landscape Layers) of depth to bedrock (rckdep), organic material (om), percent clay (clay), percent sand (sand), permeability (perm), soil erodibility (KFFACT/KFACT), and water table depth (wtdep) were used to calculate soil characteristics for each NHDPlusV2 catchment.  The soil characteristics were summarized to produce local catchment-level and watershed-level metrics as a continuous data type. The STATSGO data are distributed in two sets, STATSGO_Set1 and STATSGO_Set2, based on common NoData locations in each set of soil GIS layers.",
            "keyword": [
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                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
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                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
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            },
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            "accessLevel": "public",
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                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
                    "title": "LakeCat Dataset",
                    "description": "LakeCat currently contains over 300 metrics that include local catchment (Cat), watershed (Ws), and special metrics. See Geospatial Framework and Terms in the ReadMe for definitions of the terms \u2018catchment\u2019 and \u2018watershed\u2019 as used with the LakeCat Dataset. An additional metric, inStreamCat, indicates whether the variable was pulled from the StreamCat Dataset or calculated with a geospatial framework that was developed for LakeCat.\n\nThese metrics are available for 378,088 lakes and their associated catchments across the conterminous US. LakeCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/node/276204",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "State Soil Geographic Database (STATSGO) (KFFACT)",
                    "description": "This dataset represents the soil characteristics within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies based on the STATSGO landscape rasters. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. This data set is derived from the STATSGO landscape rasters for the conterminous USA. Individual rasters (Landscape Layers) of depth to bedrock (rckdep), organic material (om), percent clay (clay), percent sand (sand), permeability (perm), soil erodibility (KFFACT/KFACT), and water table depth (wtdep) were used to calculate soil characteristics for each NHDPlusV2 catchment.  The soil characteristics were summarized to produce local catchment-level and watershed-level metrics as a continuous data type. The STATSGO data are distributed in two sets, STATSGO_Set1 and STATSGO_Set2, based on common NoData locations in each set of soil GIS layers.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
            "describedByType": "text/html",
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            "language": [
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            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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            ],
            "theme": [
                "environment"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (LakeCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Surficial Lithology in Watershed",
            "description": "This dataset represents the density of 18 USGS lithology classes within individual local and accumulated upstream catchments for NHDPlusV2 Waterbodies. Catchment boundaries in LakeCat are defined in one of two ways, on-network or off-network. The on-network catchment boundaries follow the catchments provided in the NHDPlusV2 and the metrics for these lakes mirror metrics from StreamCat, but will substitute the COMID of the NHDWaterbody for that of the NHDFlowline. The off-network catchment framework uses the NHDPlusV2 flow direction rasters to define non-overlapping lake-catchment boundaries and then links them through an off-network flow table. This data set is derived from the USGS raster map of 18 lithology classes (categorical data type) for the conterminous USA. The map was produced based on texture, internal structure, thickness, and environment of deposition or formation of materials. These 18 lithology classes were summarized by local catchment and by watershed to produce 18 local catchment-level and watershed-level metrics as a categorical data type.",
            "keyword": [
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                "ecosystem",
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                "monitoring",
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                "united states",
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                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
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                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
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                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
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            ],
            "modified": "2023-11-13",
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        },
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                "massachusetts",
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                "massachusetts",
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                "minnesota",
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                "missouri",
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        },
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                    "format": "Comma-Separated Values (.csv)",
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                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
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                "virginia",
                "washington",
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                "wisconsin",
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            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
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            "spatial": "-125.0,24.5,-66.5,49.5",
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                {
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                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
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                },
                {
                    "@type": "dcat:Distribution",
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                    "format": "Comma-Separated Values (.csv)",
                    "title": "Wildfire Burn Severity Class 1984-2018 (MTBS)",
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            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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            ],
            "theme": [
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            "geo": "No",
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            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/LakeCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The LakeCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Wildland Fire Perimeters By Year 2000 - 2010",
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                "massachusetts",
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                "mississippi",
                "missouri",
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                "nevada",
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                "new jersey",
                "new mexico",
                "new york",
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                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
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                "tennessee",
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                "vermont",
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                "washington",
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                "wisconsin",
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                "name": "U.S. Environmental Protection Agency, Office of Water, "
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
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                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
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                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
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                    "format": "Comma-Separated Values (.csv)",
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            ],
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        },
        {
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            "keyword": [
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                "connecticut",
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                "indiana",
                "iowa",
                "kansas",
                "kentucky",
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                "michigan",
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                "oregon",
                "pennsylvania",
                "rhode island",
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                "utah",
                "vermont",
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                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
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            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
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                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
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                    "description": "This dataset represents the population and housing unit density within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on 2010 US Census data. Densities are calculated for every block group and watershed averages are calculated for every local NHDPlusV2 catchment. This data set is derived from The TIGER/Line Files and related database (.dbf) files for the conterminous USA. It was downloaded as Block Group-Level Census 2010 SF1 Data in File Geodatabase Format (ArcGIS version 10.0). The landscape raster (LR) was produced based on the data compiled from the questions asked of all people and about every housing unit. The (block-group population / block group area) and (block-group housing units / block group area) were summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.",
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                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
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            ],
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        },
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            "@type": "dcat:Dataset",
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                "rhode island",
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                "virginia",
                "washington",
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                "wisconsin",
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            "modified": "2023-11-13",
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            "spatial": "-125.0,24.5,-66.5,49.5",
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                    "@type": "dcat:Distribution",
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                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
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                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "2010 US Census Road Density",
                    "description": "This dataset represents the road density within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. This data set is derived from TIGER/Line Files of roads in the conterminous United States. Road density describes how many kilometers of road exist in a square kilometer. A raster was produced using the ArcGIS Line Density Tool to form the landscape layer for analysis. The (kilometer of road/square kilometer) was summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.",
                    "mediaType": "text/csv",
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            ],
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            ],
            "theme": [
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            "geo": "No",
            "holdren": "No",
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            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Agricultural Drainage",
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                "oklahoma",
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                "tennessee",
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                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
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            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Anthropogenic Nitrogen per AOI within AOI",
            "description": "This dataset represents net anthropogenic Nitrogen within individual,  local NHDPlusV2 catchments and upstream, contributing watersheds.",
            "keyword": [
                "inlandwaters",
                "ecosystem",
                "environment",
                "monitoring",
                "natural resources",
                "surface water",
                "modeling",
                "united states of america",
                "united states",
                "usa",
                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "identifier": "63669882-c84b-43d5-bd21-7143ce486ab6",
            "accessLevel": "public",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
                    "title": "StreamCat Dataset",
                    "description": "StreamCat currently contains over 600 metrics that include local catchment (Cat), watershed (Ws), and special metrics. The special metrics were derived through modeling or by combining other StreamCat metrics. These variables include predicted water temperature, predicted biological condition, and the indexes of catchment and watershed integrity. See Geospatial Framework and Terms below for definitions of catchment and watershed as used with the StreamCat Dataset.\n\nThese metrics are available for ~2.65 million stream segments and their associated catchments across the conterminous US. StreamCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "Anthropogenic Nitrogen per AOI within AOI",
                    "description": "This dataset represents net anthropogenic Nitrogen within individual,  local NHDPlusV2 catchments and upstream, contributing watersheds.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
            "describedByType": "text/html",
            "issued": "2015-04-23",
            "language": [
                "en-US"
            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
            "references": [
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            ],
            "theme": [
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            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Aquifers",
            "description": "This dataset represents percent area consisting of carbonate-rock aquifers, igneous and metamorphic-rock, sandstone, sandstone and carbonate-rock, semiconsolidated sand, and unconsolidated sand and gravel aquifers within individual,  local NHDPlusV2 catchments and upstream, contributing watersheds.",
            "keyword": [
                "inlandwaters",
                "ecosystem",
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                "monitoring",
                "natural resources",
                "surface water",
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                "united states",
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                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
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            },
            "identifier": "f9a68367-e950-4dca-a626-17d8907afddb",
            "accessLevel": "public",
            "bureauCode": [
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            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
                    "title": "StreamCat Dataset",
                    "description": "StreamCat currently contains over 600 metrics that include local catchment (Cat), watershed (Ws), and special metrics. The special metrics were derived through modeling or by combining other StreamCat metrics. These variables include predicted water temperature, predicted biological condition, and the indexes of catchment and watershed integrity. See Geospatial Framework and Terms below for definitions of catchment and watershed as used with the StreamCat Dataset.\n\nThese metrics are available for ~2.65 million stream segments and their associated catchments across the conterminous US. StreamCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "Aquifers",
                    "description": "This dataset represents percent area consisting of carbonate-rock aquifers, igneous and metamorphic-rock, sandstone, sandstone and carbonate-rock, semiconsolidated sand, and unconsolidated sand and gravel aquifers within individual,  local NHDPlusV2 catchments and upstream, contributing watersheds.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
            "describedByType": "text/html",
            "issued": "2015-04-23",
            "language": [
                "en-US"
            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
            "references": [
                "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
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            ],
            "theme": [
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            ],
            "geo": "No",
            "holdren": "No",
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            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Base Flow Index",
            "description": "This dataset represents the base flow index values within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. The base-flow index (BFI) grid for the conterminous United States was developed to estimate (1) BFI values for ungaged streams, and (2) ground-water recharge throughout the conterminous United States (see Source_Information). Estimates of BFI values at ungaged streams and BFI-based ground-water recharge estimates are useful for interpreting relations between land use and water quality in surface and ground water. The BFI (%) was summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.",
            "keyword": [
                "inlandwaters",
                "ecosystem",
                "environment",
                "monitoring",
                "natural resources",
                "surface water",
                "modeling",
                "united states of america",
                "united states",
                "usa",
                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "identifier": "66C0ED41-2707-4732-A906-E9D89E8F5A6B",
            "accessLevel": "public",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
                    "title": "StreamCat Dataset",
                    "description": "StreamCat currently contains over 600 metrics that include local catchment (Cat), watershed (Ws), and special metrics. The special metrics were derived through modeling or by combining other StreamCat metrics. These variables include predicted water temperature, predicted biological condition, and the indexes of catchment and watershed integrity. See Geospatial Framework and Terms below for definitions of catchment and watershed as used with the StreamCat Dataset.\n\nThese metrics are available for ~2.65 million stream segments and their associated catchments across the conterminous US. StreamCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "Base Flow Index",
                    "description": "This dataset represents the base flow index values within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. The base-flow index (BFI) grid for the conterminous United States was developed to estimate (1) BFI values for ungaged streams, and (2) ground-water recharge throughout the conterminous United States (see Source_Information). Estimates of BFI values at ungaged streams and BFI-based ground-water recharge estimates are useful for interpreting relations between land use and water quality in surface and ground water. The BFI (%) was summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
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            "language": [
                "en-US"
            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
            "references": [
                "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=66C0ED41-2707-4732-A906-E9D89E8F5A6B"
            ],
            "theme": [
                "environment"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Canal Density",
            "description": "This dataset represents the canal density within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. This data set is derived from NHDPlusV2 line features classified as canal, ditch, or pipeline in the conterminous United States. Canal density describes how many kilometers of canal exist in a square kilometer. A raster was produced using the ArcGIS Line Density Tool to form the landscape layer for analysis. The (kilometer of canal/square kilometer) was summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.",
            "keyword": [
                "inlandwaters",
                "ecosystem",
                "environment",
                "monitoring",
                "natural resources",
                "surface water",
                "modeling",
                "united states of america",
                "united states",
                "usa",
                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "identifier": "6B8EB461-6624-4B62-B163-D01A65669EE1",
            "accessLevel": "public",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
                    "title": "StreamCat Dataset",
                    "description": "StreamCat currently contains over 600 metrics that include local catchment (Cat), watershed (Ws), and special metrics. The special metrics were derived through modeling or by combining other StreamCat metrics. These variables include predicted water temperature, predicted biological condition, and the indexes of catchment and watershed integrity. See Geospatial Framework and Terms below for definitions of catchment and watershed as used with the StreamCat Dataset.\n\nThese metrics are available for ~2.65 million stream segments and their associated catchments across the conterminous US. StreamCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "Canal Density",
                    "description": "This dataset represents the canal density within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. This data set is derived from NHDPlusV2 line features classified as canal, ditch, or pipeline in the conterminous United States. Canal density describes how many kilometers of canal exist in a square kilometer. A raster was produced using the ArcGIS Line Density Tool to form the landscape layer for analysis. The (kilometer of canal/square kilometer) was summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
            "describedByType": "text/html",
            "issued": "2015-04-23",
            "language": [
                "en-US"
            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
            "references": [
                "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=6B8EB461-6624-4B62-B163-D01A65669EE1"
            ],
            "theme": [
                "environment"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Dam Density and Storage Volume",
            "description": "This dataset represents the dam density and storage volumes within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on National Inventory of Dams (NID) data. Attributes were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics.(See Supplementary Info for Glossary of Terms). The NID database contains information about the dams location, size, purpose, type, last inspection, regulatory facts, and other technical data. Structures on streams reduce the longitudinal and lateral hydrologic connectivity of the system. For example, impoundments above dams slow stream flow, cause deposition of sediment and reduce peak flows. Dams change both the discharge and sediment supply of streams, causing channel incision and bed coarsening downstream. Downstream areas are often sediment deprived, resulting in degradation, i.e., erosion of the stream bed and stream banks. This database was improved upon by locations verified by work from the USGS National Map (Jeff Simley Group). It was observed that some dams, some of them major and which do exist, were not part of the 2009 NID, but were represented in the USGS National Map dataset, and had been in the 2006 NID.  Approximately 1,100 such dams were added, based on the USGS National Map lat/long and the 2006 NID attributes (dam height, storage, etc.) Finally, as clean-up, a) about 600 records with duplicate NIDID were removed, and b) about 300 records were removed which represented the same location of the same dam but with a different NIDID, for the largest dams (did visual check of dams with storage above 5000 acre feet and are likely duplicated - about the 10,000 largest dams) . The (dams/catchment) and (dam_storage/catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type",
            "keyword": [
                "inlandwaters",
                "ecosystem",
                "environment",
                "monitoring",
                "natural resources",
                "surface water",
                "modeling",
                "united states of america",
                "united states",
                "usa",
                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "identifier": "C64137B3-B0C3-428D-A7A0-62DF27816CA9",
            "accessLevel": "public",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
                    "title": "StreamCat Dataset",
                    "description": "StreamCat currently contains over 600 metrics that include local catchment (Cat), watershed (Ws), and special metrics. The special metrics were derived through modeling or by combining other StreamCat metrics. These variables include predicted water temperature, predicted biological condition, and the indexes of catchment and watershed integrity. See Geospatial Framework and Terms below for definitions of catchment and watershed as used with the StreamCat Dataset.\n\nThese metrics are available for ~2.65 million stream segments and their associated catchments across the conterminous US. StreamCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "Dam Density and Storage Volume",
                    "description": "This dataset represents the dam density and storage volumes within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on National Inventory of Dams (NID) data. Attributes were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics.(See Supplementary Info for Glossary of Terms). The NID database contains information about the dams location, size, purpose, type, last inspection, regulatory facts, and other technical data. Structures on streams reduce the longitudinal and lateral hydrologic connectivity of the system. For example, impoundments above dams slow stream flow, cause deposition of sediment and reduce peak flows. Dams change both the discharge and sediment supply of streams, causing channel incision and bed coarsening downstream. Downstream areas are often sediment deprived, resulting in degradation, i.e., erosion of the stream bed and stream banks. This database was improved upon by locations verified by work from the USGS National Map (Jeff Simley Group). It was observed that some dams, some of them major and which do exist, were not part of the 2009 NID, but were represented in the USGS National Map dataset, and had been in the 2006 NID.  Approximately 1,100 such dams were added, based on the USGS National Map lat/long and the 2006 NID attributes (dam height, storage, etc.) Finally, as clean-up, a) about 600 records with duplicate NIDID were removed, and b) about 300 records were removed which represented the same location of the same dam but with a different NIDID, for the largest dams (did visual check of dams with storage above 5000 acre feet and are likely duplicated - about the 10,000 largest dams) . The (dams/catchment) and (dam_storage/catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
            "describedByType": "text/html",
            "issued": "2015-04-23",
            "language": [
                "en-US"
            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
            "references": [
                "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=C64137B3-B0C3-428D-A7A0-62DF27816CA9"
            ],
            "theme": [
                "environment"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Facility Registry Services (FRS) : Toxic Release Inventory (TRI) , National Pollutant Discharge Elimination System (NPDES) , and Superfund Sites",
            "description": "This dataset represents the estimated density of georeferenced sites within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on the EPA's Facility Registry Services (FRS) geodatabase. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and then accumulated to provide watershed-level metrics. The FRS geodatabase is a collection of point locations of facilities or sites subject to environmental regulation. TRI, NPDES, and Superfund sites were extracted individually to summarize for each in the resulting .csv. (see Data Sources for links to NHDPlusV2 data and FRS data) The (site locations / catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a points data type (see Data Structure and Attribute Information for a description of each metric).",
            "keyword": [
                "inlandwaters",
                "ecosystem",
                "environment",
                "monitoring",
                "natural resources",
                "surface water",
                "modeling",
                "united states of america",
                "united states",
                "usa",
                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "identifier": "630C3CAA-B678-45FC-8641-E91C591BE13F",
            "accessLevel": "public",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
                    "title": "StreamCat Dataset",
                    "description": "StreamCat currently contains over 600 metrics that include local catchment (Cat), watershed (Ws), and special metrics. The special metrics were derived through modeling or by combining other StreamCat metrics. These variables include predicted water temperature, predicted biological condition, and the indexes of catchment and watershed integrity. See Geospatial Framework and Terms below for definitions of catchment and watershed as used with the StreamCat Dataset.\n\nThese metrics are available for ~2.65 million stream segments and their associated catchments across the conterminous US. StreamCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "Facility Registry Services (FRS) : Toxic Release Inventory (TRI) , National Pollutant Discharge Elimination System (NPDES) , and Superfund Sites",
                    "description": "This dataset represents the estimated density of georeferenced sites within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on the EPA's Facility Registry Services (FRS) geodatabase. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and then accumulated to provide watershed-level metrics. The FRS geodatabase is a collection of point locations of facilities or sites subject to environmental regulation. TRI, NPDES, and Superfund sites were extracted individually to summarize for each in the resulting .csv. (see Data Sources for links to NHDPlusV2 data and FRS data) The (site locations / catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a points data type (see Data Structure and Attribute Information for a description of each metric).",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
            "describedByType": "text/html",
            "issued": "2015-04-23",
            "language": [
                "en-US"
            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
            "references": [
                "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=630C3CAA-B678-45FC-8641-E91C591BE13F"
            ],
            "theme": [
                "environment"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Forest Loss By Year 2001 to 2013",
            "description": "This dataset represents the characterization of global forest extent and change by year from 2001 through 2013 within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on the Global Forest Change 2000-2013. These data are based on global tree cover loss for the period from 2001 to 2013 at a spatial resolution of 30m. The analysis used to create the landscape layer is based on Landsat data. Forest loss was defined as a stand-replacement disturbance or the complete removal of tree cover canopy at the Landsat pixel scale. This landscape layer is a disaggregation of total forest loss to annual time scales. Encoded as either 0 (no loss) or else a value in the range 1, representing loss detected primarily in the year 2000-2013, respectively. The forest loss by year characteristics (%) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
            "keyword": [
                "inlandwaters",
                "ecosystem",
                "environment",
                "monitoring",
                "natural resources",
                "surface water",
                "modeling",
                "united states of america",
                "united states",
                "usa",
                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "identifier": "14889232-F9DE-468E-854D-9C11A25238D5",
            "accessLevel": "public",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
                    "title": "StreamCat Dataset",
                    "description": "StreamCat currently contains over 600 metrics that include local catchment (Cat), watershed (Ws), and special metrics. The special metrics were derived through modeling or by combining other StreamCat metrics. These variables include predicted water temperature, predicted biological condition, and the indexes of catchment and watershed integrity. See Geospatial Framework and Terms below for definitions of catchment and watershed as used with the StreamCat Dataset.\n\nThese metrics are available for ~2.65 million stream segments and their associated catchments across the conterminous US. StreamCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "Forest Loss By Year 2001 to 2013",
                    "description": "This dataset represents the characterization of global forest extent and change by year from 2001 through 2013 within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on the Global Forest Change 2000-2013. These data are based on global tree cover loss for the period from 2001 to 2013 at a spatial resolution of 30m. The analysis used to create the landscape layer is based on Landsat data. Forest loss was defined as a stand-replacement disturbance or the complete removal of tree cover canopy at the Landsat pixel scale. This landscape layer is a disaggregation of total forest loss to annual time scales. Encoded as either 0 (no loss) or else a value in the range 1, representing loss detected primarily in the year 2000-2013, respectively. The forest loss by year characteristics (%) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
            "describedByType": "text/html",
            "issued": "2015-04-23",
            "language": [
                "en-US"
            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
            "references": [
                "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=14889232-F9DE-468E-854D-9C11A25238D5"
            ],
            "theme": [
                "environment"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: GeoChemPhys",
            "description": "This dataset represents geochemical or geophysical attributes in surface or near surface geology within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metric. For information regarding how the Landscape layers were created see https://www.sciencebase.gov/catalog/item/53481333e4b06f6ce034aae7. Landscape Layers are partitioned into 4 tables based on the location of no-data cells within their rasters to correctly reflect the PctFull attributes within each table.",
            "keyword": [
                "inlandwaters",
                "ecosystem",
                "environment",
                "monitoring",
                "natural resources",
                "surface water",
                "modeling",
                "united states of america",
                "united states",
                "usa",
                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "identifier": "61F319E2-0048-4FEE-A3BF-4B1298EB93FE",
            "accessLevel": "public",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
                    "title": "StreamCat Dataset",
                    "description": "StreamCat currently contains over 600 metrics that include local catchment (Cat), watershed (Ws), and special metrics. The special metrics were derived through modeling or by combining other StreamCat metrics. These variables include predicted water temperature, predicted biological condition, and the indexes of catchment and watershed integrity. See Geospatial Framework and Terms below for definitions of catchment and watershed as used with the StreamCat Dataset.\n\nThese metrics are available for ~2.65 million stream segments and their associated catchments across the conterminous US. StreamCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "GeoChemPhys",
                    "description": "This dataset represents geochemical or geophysical attributes in surface or near surface geology within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metric. For information regarding how the Landscape layers were created see https://www.sciencebase.gov/catalog/item/53481333e4b06f6ce034aae7. Landscape Layers are partitioned into 4 tables based on the location of no-data cells within their rasters to correctly reflect the PctFull attributes within each table.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
            "describedByType": "text/html",
            "issued": "2015-04-23",
            "language": [
                "en-US"
            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
            "references": [
                "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=61F319E2-0048-4FEE-A3BF-4B1298EB93FE"
            ],
            "theme": [
                "environment"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Index of Watershed Integrity / Index of Catchment Integrity (IWI/ICI)",
            "description": "This dataset represents the Index of Watershed Integrity / Index of Catchment Integrity (IWI/ICI) within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on 23 other StreamCat metrics. The Index of Watershed Integrity (IWI) is based on first order approximations of relationships between stressors and six watershed functions: hydrologic regulation, regulation of water chemistry, sediment regulation, hydrologic connectivity, temperature regulation, and habitat provision. Link to paper: https://doi.org/10.1016/j.ecolind.2017.10.070\\\\nThe Index of Watershed Integrity / Index of Catchment Integrity (IWI/ICI) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
            "keyword": [
                "inlandwaters",
                "ecosystem",
                "environment",
                "monitoring",
                "natural resources",
                "surface water",
                "modeling",
                "united states of america",
                "united states",
                "usa",
                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "identifier": "520397B1-342A-45EA-B8F9-B05694C0A194",
            "accessLevel": "public",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
                    "title": "StreamCat Dataset",
                    "description": "StreamCat currently contains over 600 metrics that include local catchment (Cat), watershed (Ws), and special metrics. The special metrics were derived through modeling or by combining other StreamCat metrics. These variables include predicted water temperature, predicted biological condition, and the indexes of catchment and watershed integrity. See Geospatial Framework and Terms below for definitions of catchment and watershed as used with the StreamCat Dataset.\n\nThese metrics are available for ~2.65 million stream segments and their associated catchments across the conterminous US. StreamCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "Index of Watershed Integrity / Index of Catchment Integrity (IWI/ICI)",
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                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
            "describedByType": "text/html",
            "issued": "2015-04-23",
            "language": [
                "en-US"
            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
            "references": [
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            ],
            "theme": [
                "environment"
            ],
            "geo": "No",
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            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Mean Hillslope",
            "description": "This dataset represents mean hillslope percent within individual,  local NHDPlusV2 catchments and upstream, contributing watersheds.",
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                "natural resources",
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                "united states",
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                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
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                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
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            },
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            "programCode": [
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
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                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
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                {
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            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
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            ],
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            "geo": "No",
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            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
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            "description": "This dataset represents the mine density within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on mine plants and operations monitored by the USGS National Minerals Information Center. The National Minerals Information Center canvasses the nonfuel mining and mineral-processing industry in the United States for data on mineral production, consumption, recycling, stocks, and shipments. Mine plants and operations for commodities are expressed as points in a shapefile that was downloaded from the USGS directly. The (mines / catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type.",
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                "ecosystem",
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                "monitoring",
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                "united states",
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                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
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                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
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            },
            "identifier": "E195B424-0A8A-4836-BE03-C48C122AF701",
            "accessLevel": "public",
            "bureauCode": [
                "020:00"
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            "programCode": [
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
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                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
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                    "description": "StreamCat currently contains over 600 metrics that include local catchment (Cat), watershed (Ws), and special metrics. The special metrics were derived through modeling or by combining other StreamCat metrics. These variables include predicted water temperature, predicted biological condition, and the indexes of catchment and watershed integrity. See Geospatial Framework and Terms below for definitions of catchment and watershed as used with the StreamCat Dataset.\n\nThese metrics are available for ~2.65 million stream segments and their associated catchments across the conterminous US. StreamCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
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                {
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                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "Mine Density  Active Mines and Mineral Plants in the US",
                    "description": "This dataset represents the mine density within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on mine plants and operations monitored by the USGS National Minerals Information Center. The National Minerals Information Center canvasses the nonfuel mining and mineral-processing industry in the United States for data on mineral production, consumption, recycling, stocks, and shipments. Mine plants and operations for commodities are expressed as points in a shapefile that was downloaded from the USGS directly. The (mines / catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type.",
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            ],
            "theme": [
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            ],
            "geo": "No",
            "holdren": "No",
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            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: National Anthropogenic Barrier Dataset (NABD)",
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            "keyword": [
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                "ecosystem",
                "environment",
                "monitoring",
                "natural resources",
                "surface water",
                "modeling",
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                "united states",
                "usa",
                "alabama",
                "arizona",
                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
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            },
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            "accessLevel": "public",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
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                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "National Anthropogenic Barrier Dataset (NABD)",
                    "description": "This dataset represents the dam density and storage volumes within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on the National Anthropogenic Barrier Dataset (NABD). Attributes were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. The main objective of this project was to develop a dataset of large, anthropogenic barriers that are spatially linked to the National Hydrography Dataset Plus Version 1 (NHDPlusV1) for the conterminous U.S. to facilitate GIS analyses based on the NHDPlusV1/NHD and NID datasets. To meet this objective, Michigan State University conducted a spatial linkage of the point dataset of the 2009 National Inventory of Dams (NID) created by the U.S. Army Corps of Engineers (USACE) to the NHDPlusV1/NHD. The pool of dam data included were modified based on 1) dam removals that occurred after development of the 2009 NID and 2) the identification of duplicate dam records along state boundaries (cases where more than one state reported the same dam). The US Geological Survey (USGS) Aquatic GAP Program supported this work. The (dams/catchment) and (dam_storage/catchment) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                }
            ],
            "accrualPeriodicity": "R/P3Y",
            "dataQuality": true,
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
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            "language": [
                "en-US"
            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
            "references": [
                "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=83E6ECD0-1BC3-4182-B1A1-DDFF5804E405"
            ],
            "theme": [
                "environment"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: National Atmospheric Deposition Program National Trends Network - Nitrogen Deposition (NADP)",
            "description": "This dataset represents deposition estimates of nutrients within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on the National Atmospheric Deposition Program. The National Trends Network provides long-term records of precipitation chemistry across the United States. Individual rasters describe ammonium, nitrate, inorganic nitrogen, and average sulfur/nitrogen deposition per year. See Source Info for links to NADP. The nitrogen and sulfur characteristics (kg N/ha/yr) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
            "keyword": [
                "inlandwaters",
                "ecosystem",
                "environment",
                "monitoring",
                "natural resources",
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                "usa",
                "alabama",
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                "arkansas",
                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
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                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
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                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
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            },
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            "accessLevel": "public",
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                "020:00"
            ],
            "programCode": [
                "020:072"
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
                    "title": "StreamCat Dataset",
                    "description": "StreamCat currently contains over 600 metrics that include local catchment (Cat), watershed (Ws), and special metrics. The special metrics were derived through modeling or by combining other StreamCat metrics. These variables include predicted water temperature, predicted biological condition, and the indexes of catchment and watershed integrity. See Geospatial Framework and Terms below for definitions of catchment and watershed as used with the StreamCat Dataset.\n\nThese metrics are available for ~2.65 million stream segments and their associated catchments across the conterminous US. StreamCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "National Atmospheric Deposition Program National Trends Network - Nitrogen Deposition (NADP)",
                    "description": "This dataset represents deposition estimates of nutrients within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on the National Atmospheric Deposition Program. The National Trends Network provides long-term records of precipitation chemistry across the United States. Individual rasters describe ammonium, nitrate, inorganic nitrogen, and average sulfur/nitrogen deposition per year. See Source Info for links to NADP. The nitrogen and sulfur characteristics (kg N/ha/yr) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
                    "mediaType": "text/csv",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
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            ],
            "accrualPeriodicity": "R/P3Y",
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            "issued": "2015-04-23",
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            ],
            "landingPage": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
            "references": [
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            ],
            "theme": [
                "environment"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: National Coal Resource Dataset System",
            "description": "This dataset represents the coal mine density and storage volumes within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on the National Coal Resource Dataset System (NCRDS). Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. The National Coal Resources Data System (NCRDS) began as a cooperative venture between the USGS and State geological agencies in 1975 and focused on the stratigraphy and chemistry of coal. Web pages have been developed to query data within both the USCOAL database and a subset of the USCHEM database. The USTRAT database, due to its size and complexity, was first made available in 2011 for direct query through web pages. The (coal mine sites/AreaSqKm) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type.",
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                "illinois",
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                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
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                "texas",
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                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
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                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
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                    "description": "StreamCat currently contains over 600 metrics that include local catchment (Cat), watershed (Ws), and special metrics. The special metrics were derived through modeling or by combining other StreamCat metrics. These variables include predicted water temperature, predicted biological condition, and the indexes of catchment and watershed integrity. See Geospatial Framework and Terms below for definitions of catchment and watershed as used with the StreamCat Dataset.\n\nThese metrics are available for ~2.65 million stream segments and their associated catchments across the conterminous US. StreamCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
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                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
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                },
                {
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                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
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                    "title": "National Coal Resource Dataset System",
                    "description": "This dataset represents the coal mine density and storage volumes within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on the National Coal Resource Dataset System (NCRDS). Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. The National Coal Resources Data System (NCRDS) began as a cooperative venture between the USGS and State geological agencies in 1975 and focused on the stratigraphy and chemistry of coal. Web pages have been developed to query data within both the USCOAL database and a subset of the USCHEM database. The USTRAT database, due to its size and complexity, was first made available in 2011 for direct query through web pages. The (coal mine sites/AreaSqKm) were summarized and accumulated into watersheds to produce local catchment-level and watershed-level metrics as a point data type.",
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                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
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                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
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                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
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                "utah",
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                "washington",
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                "wisconsin",
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            "modified": "2023-11-13",
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            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
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                    "description": "This dataset represents the elevation values within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on the National Elevation Dataset (see Data Sources for links to NHDPlusV2 data and NED data). NHDPlusV2 records NED snapshot dates as follows: August 2010 - VPU04 February 2011 - VPUs 05, 06 June 2011 - VPU 17 August 2011 - VPUs 07, 10L, 10U, 11, 18 December 2011 - VPUs 01, 02, 03N, 03S, 03W, 08, 09, 12, 13, 14, 15, 16. The elevation characteristics were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.",
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        },
        {
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            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: National Land Cover Database",
            "description": "This dataset represents data derived from the NLCD dataset and the National Hydrography Dataset version 2.1(NHDPlusV2) (see Data Sources for links to NHDPlusV2 data and NLCD). Attributes were calculated for every local NHDPlusV2 catchment and accumulated watershed to provide watershed-level metrics for classes within the NLCD. This data set is derived from the NLCD raster composed of 16 of the modified Anderson land cover classes (categorical data type) for the conterminous USA (excluding the  four Alaska-specific land cover classes). Additional agriculture on slope  metrics were derived using slope based on  National elevation DEMs delivered with NHDplusV2 for agriculture NLCD classes. The NLCD raster was produced based on a decision-tree classification of 2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019 Landsat satellite data (see Data Structure and Attribute Information for a description of each metric). This dataset will include additional years as they become available.",
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                "oklahoma",
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                "pennsylvania",
                "rhode island",
                "south carolina",
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                "texas",
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                "vermont",
                "virginia",
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                "wyoming"
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                    "description": "This dataset represents data derived from the NLCD dataset and the National Hydrography Dataset version 2.1(NHDPlusV2) (see Data Sources for links to NHDPlusV2 data and NLCD). Attributes were calculated for every local NHDPlusV2 catchment and accumulated watershed to provide watershed-level metrics for classes within the NLCD. This data set is derived from the NLCD raster composed of 16 of the modified Anderson land cover classes (categorical data type) for the conterminous USA (excluding the  four Alaska-specific land cover classes). Additional agriculture on slope  metrics were derived using slope based on  National elevation DEMs delivered with NHDplusV2 for agriculture NLCD classes. The NLCD raster was produced based on a decision-tree classification of 2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019 Landsat satellite data (see Data Structure and Attribute Information for a description of each metric). This dataset will include additional years as they become available.",
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            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: National Land Cover Database - Impervious Surfaces",
            "description": "This dataset represents data derived from the NLCD dataset and the National Hydrography Dataset version 2.1(NHDPlusV2) (see Data Sources for links to NHDPlusV2 data and NLCD). Attributes were calculated for every local NHDPlusV2 catchment and accumulated upstream catchments to provide watershed-level metrics for imperviousness values within the NLCD.  This data set is derived from the NLCD Impervious Surfaces raster, which describes percent imperviousness (continuous data type). Values indicate the degree to which the area is composed of impervious anthropogenic materials (e.g., parking surfaces, roads, building roofs). This raster was produced based on a decision-tree classification of 2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019 Landsat satellite data. This dataset will include additional years as they become available. ",
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                {
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                    "mediaType": "text/csv",
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            ],
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        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Nitrogen From Rock Weathering",
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                "illinois",
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                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
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                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
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                "tennessee",
                "texas",
                "utah",
                "vermont",
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                "west virginia",
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                "wyoming"
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            "temporal": "2015/2030",
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                "kentucky",
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                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
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                "new hampshire",
                "new jersey",
                "new mexico",
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                "oklahoma",
                "oregon",
                "pennsylvania",
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        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Pesticide",
            "description": "This dataset represents the pesticide use within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. This data set is derived from 219, 1-kilometer (km) resolution grids depicting estimated agricultural use of each pesticide in the conterminous United States. Each grid cell value in the national grids of this dataset is the estimated total kilograms (kg) of pesticides applied to row crops, small grain crops and fallow land, pasture and hay crops, and orchard and vineyard crops within the 1- by 1-km area. A single raster was produced using the Raster Calculator Tool adding all 219 grids to form the landscape layer for analysis. (see Data Sources for links to NHDPlusV2 data and USGS Data). The (kilograms of pesticides/square kilometer) was summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.",
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                "colorado",
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                "illinois",
                "indiana",
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                "kansas",
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                "massachusetts",
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                "missouri",
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                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
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                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
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                "name": "U.S. Environmental Protection Agency, Office of Water, "
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            "identifier": "FF4DC154-0BEE-4818-8417-331705B40A12",
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            "bureauCode": [
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            "programCode": [
                "020:072"
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            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
                    "title": "StreamCat Dataset",
                    "description": "StreamCat currently contains over 600 metrics that include local catchment (Cat), watershed (Ws), and special metrics. The special metrics were derived through modeling or by combining other StreamCat metrics. These variables include predicted water temperature, predicted biological condition, and the indexes of catchment and watershed integrity. See Geospatial Framework and Terms below for definitions of catchment and watershed as used with the StreamCat Dataset.\n\nThese metrics are available for ~2.65 million stream segments and their associated catchments across the conterminous US. StreamCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "Pesticide",
                    "description": "This dataset represents the pesticide use within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. This data set is derived from 219, 1-kilometer (km) resolution grids depicting estimated agricultural use of each pesticide in the conterminous United States. Each grid cell value in the national grids of this dataset is the estimated total kilograms (kg) of pesticides applied to row crops, small grain crops and fallow land, pasture and hay crops, and orchard and vineyard crops within the 1- by 1-km area. A single raster was produced using the Raster Calculator Tool adding all 219 grids to form the landscape layer for analysis. (see Data Sources for links to NHDPlusV2 data and USGS Data). The (kilograms of pesticides/square kilometer) was summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.",
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            ],
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            "geo": "No",
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        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Predicted Biological Condition",
            "description": "This dataset consists of predicted probabilities of good biological condition based in the US EPA 2008/2009 National Rivers and Streams Assessment (NRSA). NRSA assesses the biological condition of rivers and streams using several approaches, including a benthic invertebrate multimetric index (BMMI). The development of the NRSA BMMI is documented in the 2008/2009 NRSA Report (https://www.epa.gov/national-aquatic-resource-surveys/national-rivers-and-streams-assessment-2008-2009-results) and by Stoddard et al. (2008) (http://www.bioone.org/doi/abs/10.1899/08-053.1). This assessment resulted in the classification of 1,380 streams as being in good or poor biological condition. These sites were paired with StreamCat data and a random forest model was developed to predict the probable condition of streams based on the binary response of condition to catchment and watershed features. This model was then applied to NHDPlusV2 stream segments that were within the NRSA sampling frame, i.e., streams that were candidates for sampling during the 2008/2009 NRSA (~1.1 million stream segments). Model development was documented in Fox et al. (2017) (https://link.springer.com/article/10.1007/s10661-017-6025-0) and Hill et al. (2017)(http://onlinelibrary.wiley.com/doi/10.1002/eap.1617/full).",
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                "connecticut",
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                "florida",
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                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Office of Water, "
            },
            "contactPoint": {
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                "fn": "U.S. Environmental Protection Agency, Office of Water, Marc Weber",
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            },
            "identifier": "347BAA74-DA58-4F3D-BD51-7A424CAA8EBD",
            "accessLevel": "public",
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                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
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                    "@type": "dcat:Distribution",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
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                    "description": "StreamCat currently contains over 600 metrics that include local catchment (Cat), watershed (Ws), and special metrics. The special metrics were derived through modeling or by combining other StreamCat metrics. These variables include predicted water temperature, predicted biological condition, and the indexes of catchment and watershed integrity. See Geospatial Framework and Terms below for definitions of catchment and watershed as used with the StreamCat Dataset.\n\nThese metrics are available for ~2.65 million stream segments and their associated catchments across the conterminous US. StreamCat metrics represent both natural (e.g., soils and geology) and anthropogenic (e.g, urban areas and agriculture) landscape information.",
                    "format": "API",
                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
                    "describedByType": "text/html"
                },
                {
                    "@type": "dcat:Distribution",
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                    "description": "This dataset consists of predicted probabilities of good biological condition based in the US EPA 2008/2009 National Rivers and Streams Assessment (NRSA). NRSA assesses the biological condition of rivers and streams using several approaches, including a benthic invertebrate multimetric index (BMMI). The development of the NRSA BMMI is documented in the 2008/2009 NRSA Report (https://www.epa.gov/national-aquatic-resource-surveys/national-rivers-and-streams-assessment-2008-2009-results) and by Stoddard et al. (2008) (http://www.bioone.org/doi/abs/10.1899/08-053.1). This assessment resulted in the classification of 1,380 streams as being in good or poor biological condition. These sites were paired with StreamCat data and a random forest model was developed to predict the probable condition of streams based on the binary response of condition to catchment and watershed features. This model was then applied to NHDPlusV2 stream segments that were within the NRSA sampling frame, i.e., streams that were candidates for sampling during the 2008/2009 NRSA (~1.1 million stream segments). Model development was documented in Fox et al. (2017) (https://link.springer.com/article/10.1007/s10661-017-6025-0) and Hill et al. (2017)(http://onlinelibrary.wiley.com/doi/10.1002/eap.1617/full).",
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                    "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-metrics-and-definitions",
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            ],
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            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Predicted Channel Widths and Depths",
            "description": "This dataset represents predicted channel widths and depths from Doyle et al. 2023. Values include: Predicted wetted width: distance of the water\\\\u2019s edge from left to right bank, Predicted thalweg depth: deepest point in the channel cross section from the bottom substrate to the water surface, Predicted bankfull width: distance from left to right bank at bankfull stage where the potential water height would spill outside of the channel and into the floodplain, and Predicted bankfull depth: thalweg depth plus bankfull height, which is the height from the water surface to the bankfull stage.",
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                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
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                "nebraska",
                "nevada",
                "new hampshire",
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                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
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                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
            ],
            "modified": "2023-11-13",
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            },
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            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
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                {
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                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
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                    "format": "API",
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                },
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                    "description": "This dataset represents predicted channel widths and depths from Doyle et al. 2023. Values include: Predicted wetted width: distance of the water\\\\u2019s edge from left to right bank, Predicted thalweg depth: deepest point in the channel cross section from the bottom substrate to the water surface, Predicted bankfull width: distance from left to right bank at bankfull stage where the potential water height would spill outside of the channel and into the floodplain, and Predicted bankfull depth: thalweg depth plus bankfull height, which is the height from the water surface to the bankfull stage.",
                    "mediaType": "text/csv",
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        },
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            "@type": "dcat:Dataset",
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            "description": "This dataset represents climate observations within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. PRISM is a set of monthly, yearly, and single-event gridded data products of mean temperature and precipitation, max/min temperatures, and dewpoints, primarily for the United States. In-situ point measurements are ingested into the PRISM (Parameter elevation Regression on Independent Slopes Model) statistical mapping system. The PRISM products use a weighted regression scheme to account for complex climate regimes associated with orography, rain shadows, temperature inversions, slope aspect, coastal proximity, and other factors. These data are summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.",
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                "oklahoma",
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            "rights": "public (Data asset is or could be made publicly available to all without restrictions)",
            "spatial": "-125.0,24.5,-66.5,49.5",
            "temporal": "2015/2030",
            "distribution": [
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                    "@type": "dcat:Distribution",
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                {
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                    "downloadURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset#access-streamcat-data",
                    "format": "Comma-Separated Values (.csv)",
                    "title": "PRISM Normals Data",
                    "description": "This dataset represents climate observations within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. PRISM is a set of monthly, yearly, and single-event gridded data products of mean temperature and precipitation, max/min temperatures, and dewpoints, primarily for the United States. In-situ point measurements are ingested into the PRISM (Parameter elevation Regression on Independent Slopes Model) statistical mapping system. The PRISM products use a weighted regression scheme to account for complex climate regimes associated with orography, rain shadows, temperature inversions, slope aspect, coastal proximity, and other factors. These data are summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.",
                    "mediaType": "text/csv",
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            ],
            "accrualPeriodicity": "R/P3Y",
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            ],
            "theme": [
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            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water (StreamCat)",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/StreamCat.json"
        },
        {
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        {
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                    "description": "This dataset represents the density of 18 USGS lithology classes within individual, local NHDPlusV2 catchments and upstream, contributing watersheds(see Data Sources for links to NHDPlusV2 data and USGS). Attributes were calculated for every local NHDPlusV2 catchment and then accumulated to provide watershed-level metrics for USGS lithology data. This data set is derived from the USGS raster map of 18 lithology classes (categorical data type) for the conterminous USA. The map was produced based on texture, internal structure, thickness, and environment of deposition or formation of materials. These 18 lithology classes were summarized by local catchment and by watershed to produce 18 local catchment-level and watershed-level metrics as a categorical data type.",
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            "issued": "2015-04-23",
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        },
        {
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            "title": "The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Surplus Precipitation",
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                "california",
                "colorado",
                "connecticut",
                "delaware",
                "district of columbia",
                "florida",
                "georgia",
                "idaho",
                "illinois",
                "indiana",
                "iowa",
                "kansas",
                "kentucky",
                "louisiana",
                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
                "nevada",
                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
                "north dakota",
                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
                "south carolina",
                "south dakota",
                "tennessee",
                "texas",
                "utah",
                "vermont",
                "virginia",
                "washington",
                "west virginia",
                "wisconsin",
                "wyoming"
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            "modified": "2023-11-13",
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                "massachusetts",
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                "minnesota",
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                "missouri",
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                "new hampshire",
                "new jersey",
                "new mexico",
                "new york",
                "north carolina",
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                "ohio",
                "oklahoma",
                "oregon",
                "pennsylvania",
                "rhode island",
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            "modified": "2023-11-13",
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                "maine",
                "maryland",
                "massachusetts",
                "michigan",
                "minnesota",
                "mississippi",
                "missouri",
                "montana",
                "nebraska",
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                "new hampshire",
                "new jersey",
                "new mexico",
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            "modified": "2023-11-13",
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        {
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                    "accessURL": "https://www.ncbi.nlm.nih.gov/pmc/funder/epa",
                    "@type": "dcat:Distribution"
                },
                {
                    "downloadURL": "https://www.ncbi.nlm.nih.gov/pmc/funder/epa",
                    "@type": "dcat:Distribution",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2014-04-17",
            "theme": [
                "environment"
            ],
            "dataQuality": true,
            "landingPage": "https://www.ncbi.nlm.nih.gov/pmc/funder/epa/",
            "bureauCode": [
                "020:00"
            ],
            "issued": "2017-04-17",
            "accrualPeriodicity": "R/P1D",
            "spatial": "-80.542601,36.666691,-74.580735,42.987042",
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "contactPoint": {
                "hasEmail": "mailto:vega.ann@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Ann Vega"
            },
            "identifier": "00bf8c5a-dc57-11e7-9296-cec278b6b50a",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "ORD",
            "sourcetitle": "EPA Office of Research and Development, National Health & Environmental Effects Research Laboratory",
            "sourcefile": "https://edg.epa.gov/data/public/ORD/NHEERL/metadata/PubCentral.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Drinking Water Treatability Database (TDB)",
            "description": "The Drinking Water Treatability Database (TDB) presents referenced information on the control of contaminants in drinking water. It allows drinking water utilities, first responders to spills or emergencies, treatment process designers, research organizations, regulators and others to access referenced information gathered from thousands of literature sources on regulated and unregulated contaminants.",
            "keyword": [
                "human health",
                "health risks",
                "toxicity",
                "substances",
                "chemicals",
                "environment",
                "environment",
                "united states",
                "health"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
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                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Thomas Speth, U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)",
                "hasEmail": "mailto:Speth.Thomas@epa.gov"
            },
            "identifier": "{05F6B3E7-ED0F-468D-8D74-DA40D48DD100}",
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            "references": [
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                "https://edg.epa.gov/metadata/rest/document?id=%7B05F6B3E7-ED0F-468D-8D74-DA40D48DD100%7D"
            ],
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            ],
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            ],
            "license": "https://edg.epa.gov/EPA_Data_License.htm",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "title": "Office of Water Linked Data",
            "description": "The Office of Water Linked Data (OWLD) dataset stores EPA Water program information indexed to several National Hydrography Dataset frameworks. Indexing may be accomplished by catchment, reach or hydrologic unit referencing and includes a curated set of relevant program data attributes. OWLD is closely related to the NHD Event Data model with extensions added to cover catchment-based indexing.",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "WATERS Support",
                "hasEmail": "mailto:waters_support@epa.gov"
            },
            "keyword": [
                "environment",
                "Surface Water",
                "Water",
                "United States",
                "inlandWaters",
                "location",
                "oceans",
                "mapping",
                "stream network",
                "NHDPlus"
            ],
            "bureauCode": [
                "020:00"
            ],
            "modified": "2024-05-14",
            "identifier": "d4ae8812-b921-40ee-96b5-ba9829b96568",
            "accessLevel": "public",
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "temporal": "2000-01-01/2024-05-14",
            "dataQuality": true,
            "landingPage": "https://www.epa.gov/waterdata/waters-watershed-assessment-tracking-environmental-results-system/",
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "accessURL": "https://watersgeo.epa.gov/arcgis/rest/services/owld",
                    "title": "Office of Water GIS Services for OWLD datasets",
                    "format": "API"
                }
            ],
            "programCode": [
                "020:112"
            ],
            "primaryitinvestmentuii": "020-000000087",
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Water Contaminant Information Tool",
            "description": "The Water Contaminant Information Tool (WCIT) is a secure, on-line database that provides current, reliable information on chemical, biological, and radiological contaminants of concern for water security. The WCIT database assists in planning for and responding to drinking water and wastewater (water) contamination threats and incidents. As a planning tool, WCIT supports vulnerability assessments, emergency response plans, and site-specific response guidelines. As a response tool, WCIT provides contaminant data to help responders (including utilities) make appropriate response decisions. WCIT also helps EPA to identify gaps in contaminant data, which will, in turn, help inform future research efforts.",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Veronica Aponte-Morales",
                "hasEmail": "mailto:aponte-morales.veronica@epa.gov"
            },
            "keyword": [
                "Chemicals",
                "Drinking Water",
                "Emergency Response",
                "Water",
                "United States",
                "utilitiesCommunication",
                "Drinking Water Utilities",
                "Water Security"
            ],
            "bureauCode": [
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            ],
            "modified": "2021",
            "identifier": "c3b1fc8c-3966-46b4-84ba-92cb4529ccfd",
            "accessLevel": "non-public",
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "temporal": "2005/2021",
            "dataQuality": true,
            "programCode": [
                "020:038"
            ],
            "systemofrecords": "https://www.epa.gov/privacy/privacy-act-system-records-epa-central-data-exchange-customer-registration-subsystem-epa-52",
            "primaryitinvestmentuii": "020-000000087",
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "WIFIA Vault",
            "description": "The Water Infrastructure Finance and Innovation Act of 2014 (WIFIA) established a federal credit program administered by EPA. WIFIA authorizes EPA to provide loans to eligible water infrastructure projects. After a loan is closed, WIFIA\u2019s portfolio management team leads individual transactions from closing to final maturity (this can be 35+ years). Portfolio management responsibilities are numerous but generally are intended to achieve the following critical objectives:\n\u2022\tmonitor portfolio risk and compliance, \n\u2022\ttrack key loan requirements, information and status, \n\u2022\tdocument and track disbursements, repayments, and related accounting actions, \n\u2022\tmaintain and document borrower communication, and \n\u2022\tmaintain robust loan-specific and portfolio-wide metrics reporting capabilities.",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW)"
            },
            "contactPoint": {
                "fn": "Kudzai Mukushi",
                "hasEmail": "mailto:Mukushi.Kudzai@epa.gov",
                "@type": "vcard:Contact"
            },
            "keyword": [
                "Water",
                "Drinking Water",
                "United States",
                "utilitiesCommunication",
                "structure",
                "Loan",
                "Finance",
                "Infrastructure"
            ],
            "identifier": "7a9c7c95-3f18-4ece-aad0-dc748a206d89",
            "accessLevel": "non-public",
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "bureauCode": [
                "020:00"
            ],
            "temporal": "2019/2021",
            "accrualPeriodicity": "R/P1D",
            "dataQuality": true,
            "programCode": [
                "020:000"
            ],
            "primaryitinvestmentuii": "020-000000104",
            "modified": "2021-12-14",
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Data on Aquatic Resources Tracking for Effective Regulation",
            "description": "DARTER is EPA's system to manage its workflow in the Clean Water Act Section 404 permit program. Section 404 requires a permit from the U.S. Army Corps of Engineers, or EPA-approved State, for the discharge of dredged or fill material into waters of the United States. EPA plays a number of roles in the Section 404 permit program including developing and interpreting policy, guidance and environmental criteria used in evaluating permit applications, determining the scope of geographic jurisdiction and reviewing and commenting on proposed Section 404 permits. DARTER allows EPA staff to: \n- Track agency involvement in pre-application coordination, review of public notices for proposed permits, review of third party mitigation projects and proposed jurisdictional determinations;\n- Prepare and share EPA-generated jurisdictional determinations; and\n- Access shared data from the U.S. Army Corps of Engineers\u2019 national regulatory program data management system known as OMBIL Regulatory Module (ORM2)\n",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW)"
            },
            "contactPoint": {
                "fn": "Brian Topping",
                "hasEmail": "mailto:Topping.Brian@epa.gov",
                "@type": "vcard:Contact"
            },
            "keyword": [
                "Surface Water",
                "United States",
                "inlandWaters",
                "oceans",
                "environment",
                "Section 404",
                "Fill",
                "Wetlands",
                "Compensatory mitigation",
                "Mitigation",
                "Jurisdictional determinations"
            ],
            "identifier": "c916f0ad-d87b-4b60-8d33-80e0f093fa15",
            "accessLevel": "restricted public",
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "bureauCode": [
                "020:00"
            ],
            "temporal": "1987/2021",
            "accrualPeriodicity": "R/P1D",
            "dataQuality": true,
            "programCode": [
                "020:112"
            ],
            "primaryitinvestmentuii": "020-000000087",
            "modified": "2023-02-28",
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Water Quality Portal",
            "description": "The Water Quality Portal (WQP) is the premiere source of discrete water-quality data in the United States and beyond. This cooperative service integrates publicly available water-quality data from the United States Geological Survey (USGS), the Environmental Protection Agency (EPA), and over 400 state, federal, tribal, and local agencies.",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Geological Survey and U.S. EPA Office of Water (OW)"
            },
            "contactPoint": {
                "fn": "Kevin Christian",
                "hasEmail": "mailto:christian.kevin@epa.gov",
                "@type": "vcard:Contact"
            },
            "keyword": [
                "Waste",
                "Surface Water",
                "Quality",
                "United States",
                "environment",
                "inlandWaters",
                "oceans",
                "Water Quality",
                "Monitoring Data",
                "schema",
                "Data Standard",
                "STORET",
                "WQX",
                "NWIS",
                "Stewards"
            ],
            "identifier": "28bc151c-da9c-4daa-a45d-cb92141cb6a2",
            "accessLevel": "public",
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "bureauCode": [
                "020:00"
            ],
            "temporal": "1987/2021",
            "accrualPeriodicity": "R/P1D",
            "dataQuality": true,
            "landingPage": "https://www.waterqualitydata.us/",
            "programCode": [
                "020:112"
            ],
            "primaryitinvestmentuii": "020-000000103",
            "modified": "2021-12-14",
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "State-Specific Water Quality Standards Effective under the Clean Water Act (CWA)",
            "description": " EPA has compiled state, territorial, and authorized tribal water quality standards that EPA has approved or are otherwise in effect for Clean Water Act purposes.  This compilation is continuously updated as EPA approves new or revised WQS.Please note the water quality standards may contain additional provisions outside the scope of the Clean Water Act, its implementing federal regulations, or EPA's authority. In some cases, these additional provisions have been included as supplementary information. EPA is posting the water quality standards as a convenience to users and has made a reasonable effort to assure their accuracy. Additionally, EPA has made a reasonable effort to identify parts of the standards that are approved, disapproved, or are otherwise not in effect for Clean Water Act purposes.",
            "keyword": [
                "environmental media topics",
                "water",
                "drinking water",
                "substances",
                "pollutants & contaminants",
                "regulated contaminants & pollutants",
                "substances",
                "pollutants & contaminants",
                "unregulated contaminants & pollutants",
                "substances",
                "pollutants & contaminants",
                "water pollutants",
                "drinking water contaminants",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-01-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Gregory Stapleton, U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)",
                "hasEmail": "mailto:stapleton.gregory@epa.gov"
            },
            "identifier": "{6D51530E-0EFF-4126-8404-36C00A8F1548}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://www.epa.gov/wqs-tech/state-specific-water-quality-standards-effective-under-clean-water-act-cwa",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B6D51530E-0EFF-4126-8404-36C00A8F1548%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B6D51530E-0EFF-4126-8404-36C00A8F1548%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.htm",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Wetland Program Pilot Grants",
            "description": "The Wetland Grant Database (WGD) houses grant data for Wetland Program Development Grants (created by EPA in 1990 under the Clean Water Act Section 104(b)(3) authority).   The Wetland Grants Database contains further information on Wetland Program Pilot Grants that were awarded in past years.",
            "keyword": [
                "wetlands",
                "grants",
                "database",
                "wgd",
                "clean water act",
                "section 104(b)(3)",
                "wetland restoration",
                "pilot grants",
                "wpdg",
                "environment",
                "environment",
                "united states",
                "inlandwaters"
            ],
            "modified": "2014-10-01",
            "issued": "2014-01-01",
            "publisher": {
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                "name": "U.S. EPA Office of Water (OW)"
            },
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            },
            "identifier": "{A719BA4D-91AC-45AC-BFFD-46EF90AC7F9C}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BA719BA4D-91AC-45AC-BFFD-46EF90AC7F9C%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7BA719BA4D-91AC-45AC-BFFD-46EF90AC7F9C%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Wetland Program Development Grants (WPDGs) Case Studies",
            "description": "The Wetland Grant Database (WGD) houses grant data for Wetland Program Development Grants (created by EPA in 1990 under the Clean Water Act Section 104(b)(3) authority).   The Wetland Grants Database contains further information on WPDG Case Studies that were awarded in past years.",
            "keyword": [
                "wetlands",
                "grants",
                "database",
                "wgd",
                "clean water act",
                "section 104(b)(3)",
                "wetland restoration",
                "case studies",
                "wpdg",
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            ],
            "modified": "2014-10-01",
            "issued": "2014-01-01",
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                "name": "U.S. EPA Office of Water (OW)"
            },
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            },
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            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BFDA9BF78-09CC-4E36-B74D-04F770973E57%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7BFDA9BF78-09CC-4E36-B74D-04F770973E57%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Wetland Program Development Grants (WPDGs)",
            "description": "The Wetland Grant Database (WGD) houses grant data for Wetland Program Development Grants (created by EPA in 1990 under the Clean Water Act Section 104(b)(3) authority).   The Wetland Grants Database contains further information on Wetland Program Development Grants that were awarded in past years.",
            "keyword": [
                "wetlands",
                "grants",
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                "wpdg",
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            ],
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            },
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            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
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                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B1893AF89-489E-4D8B-9308-DC401A4F716A%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Unregulated Contaminant Monitoring Program Data",
            "description": "EPA uses the Unregulated Contaminant Monitoring (UCM) program to collect data for contaminants suspected to be present in drinking water, but that do not have health-based standards set under the Safe Drinking Water Act (SDWA). Every five years EPA reviews the list of contaminants, largely based on the Contaminant Candidate List.",
            "keyword": [
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                "pollution prevention",
                "environment",
                "environment",
                "united states",
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            ],
            "modified": "2012-05-02",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)"
            },
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                "fn": "Safe Drinking Water Hotline, U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)",
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            },
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            "accessLevel": "public",
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                "https://edg.epa.gov/metadata/rest/document?id=%7BF31D0AC6-A317-41D9-A0B2-06304478185C%7D"
            ],
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            ],
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            ],
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            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Unregulated Contaminant Monitoring Rule 3 (UCMR 3), (2013-2015) Occurrence Data",
            "description": "The third Unregulated Contaminant Monitoring Rule (UCMR 3), conducted under EPA oversight, was published in the Federal Register on May 2, 2012. UCMR 3 requires monitoring for 30 contaminants: 28 chemicals and 2 viruses.",
            "keyword": [
                "unregulated contaminants",
                "contaminants",
                "pollution",
                "human health",
                "drinking water",
                "ucmr",
                "sdwa",
                "public water systems",
                "environment",
                "environment",
                "united states",
                "health"
            ],
            "modified": "2012-05-02",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Safe Drinking Water Hotline",
                "hasEmail": "mailto:safewater@epa.gov"
            },
            "identifier": "{C590EF66-7551-4959-BFE1-1D37D329A517}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BC590EF66-7551-4959-BFE1-1D37D329A517%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7BC590EF66-7551-4959-BFE1-1D37D329A517%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Unregulated Contaminant Monitoring Rule 2 (UCMR 2), (2008-2010) Occurrence Data",
            "description": "The Unregulated Contaminant Monitoring Rule supporting the second cycle (UCMR 2) of monitoring, conducted under EPA oversight, was published in the Federal Register on January 4, 2007. The UCMR 2 required monitoring for 25 contaminants using five analytical methods.",
            "keyword": [
                "unregulated contaminants",
                "contaminants",
                "pollution",
                "human health",
                "drinking water",
                "ucmr",
                "sdwa",
                "environment",
                "environment",
                "united states",
                "health"
            ],
            "modified": "2007-01-04",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Safe Drinking Water Hotline",
                "hasEmail": "mailto:safewater@epa.gov"
            },
            "identifier": "{9ADCB4EC-B670-4989-8F1E-1237B510F462}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B9ADCB4EC-B670-4989-8F1E-1237B510F462%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B9ADCB4EC-B670-4989-8F1E-1237B510F462%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Summary of Annual Beach Notifications",
            "description": "To help beachgoers make informed decisions about swimming at U.S. beaches, EPA gathers state-by-state data about beach closings and advisories. Between 1999 and 2012, EPA published a national summary report about the previous year's swimming season data.",
            "keyword": [
                "beach",
                "swimming",
                "recreation",
                "beach closures",
                "human health advisories",
                "environment",
                "environment",
                "united states",
                "health"
            ],
            "modified": "2023-06-22",
            "issued": "2023-06-22",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Bill Kramer, U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)",
                "hasEmail": "mailto:kramer.bill@epa.gov"
            },
            "identifier": "{AFC8F1AD-0DF4-496C-842A-1E85FE0462BD}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7BAFC8F1AD-0DF4-496C-842A-1E85FE0462BD%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BAFC8F1AD-0DF4-496C-842A-1E85FE0462BD%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "State National Pollutant Discharge Elimination System (NPDES) Program Withdrawal Petitions",
            "description": "Search for pending and resolved NPDES withdrawal petitions by state, region, date, or keyword.  \"Pending\" means EPA has received the petition and is working with the state and petitioner to resolve it. \"Withdrew petition\" means that the petitioner has withdrawn the petition they submitted. \"Resolved\" means that EPA has resolved the issues raised in the petition and has denied the petition. \"Partially resolved\" means that EPA has partially denied the petition by resolving some of the issues, while continuing to work with the state and petitioner on other pending issues. \"Program withdrawn\" would apply if, after conducting investigations, EPA withdrew a state's NPDES authority.",
            "keyword": [
                "ndpes",
                "permits",
                "withdrawal",
                "water quality",
                "clean water act",
                "cwa",
                "environment",
                "environment",
                "united states",
                "inlandwaters"
            ],
            "modified": "2012-12-12",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Wastewater Management (OWM)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Jackie Clark, U.S. EPA Office of Water (OW) - Office of Wastewater Management (OWM)",
                "hasEmail": "mailto:clark.jackie@epa.gov"
            },
            "identifier": "{90E487AE-AE70-4692-BA27-D1CCD06C6B55}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B90E487AE-AE70-4692-BA27-D1CCD06C6B55%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B90E487AE-AE70-4692-BA27-D1CCD06C6B55%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Six-Year Review Contaminant Occurrence Data",
            "description": "The Safe Drinking Water Act (SDWA) requires EPA to review each National Primary Drinking Water Regulation (NPDWR) at least once every six years and revise them, if appropriate.  The purpose of the review, called the Six-Year Review, is to identify those NPDWRs for which current health effects assessments, changes in technology, and/or other factors provide a health or technical basis to support a regulatory revision that will maintain or strengthen public health protection. To support the national contaminant occurrence and exposure assessments performed under the Six-Year Review process, EPA analyzes SDWA compliance monitoring data from public water supplies for regulated drinking water contaminants.  This analysis allows EPA to characterize the national occurrence of contaminants to help the Agency determine if there may be a meaningful opportunity to improve public health protection.",
            "keyword": [
                "drinking water",
                "sdwa",
                "npdwr",
                "six-year review",
                "contaminants",
                "pollution",
                "human health",
                "public water systems",
                "environment",
                "environment",
                "united states",
                "health"
            ],
            "modified": "2010-03-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Safe Drinking Water Hotline, U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)",
                "hasEmail": "mailto:safewater@epa.gov"
            },
            "identifier": "{616538BA-B7B5-4D4E-B1F8-A5A441F275D1}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B616538BA-B7B5-4D4E-B1F8-A5A441F275D1%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B616538BA-B7B5-4D4E-B1F8-A5A441F275D1%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "SDWISFED Drinking Water Data",
            "description": "SDWIS/FED is EPA's national regulatory compliance database for the drinking water program. It includes information on the nation's 160,000 public water systems and violations of drinking water regulations. Access aggregated information on all violations reported in an EPA region, state, and county since 1993 using the MS Excel PivotTables. These multidimensional tables contain aggregated information on water systems; violations reported by violation type and by contaminant/rule, and GPRA data, for each year since 1993; and current Envirofacts data. Sort, categorize, and analyze the data across several dimensions.",
            "keyword": [
                "pwss",
                "drinking water",
                "sdwa",
                "public water systems",
                "human health",
                "compliance",
                "violations",
                "environment",
                "environment",
                "united states",
                "health"
            ],
            "modified": "2014-10-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Safe Drinking Water Hotline, U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)",
                "hasEmail": "mailto:safewater@epa.gov"
            },
            "identifier": "{10CF7CDC-83C5-46FF-8581-342DD8ADE202}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B10CF7CDC-83C5-46FF-8581-342DD8ADE202%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B10CF7CDC-83C5-46FF-8581-342DD8ADE202%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "National List of Beaches",
            "description": "EPA has published a list of coastal recreation waters adjacent to beaches (or similar points of access) used by the public in the U.S.  The list, required by the Beaches Environmental Assessment and Coastal Health Act (BEACH Act), identifies waters that are subject to a state beach water quality monitoring and public notification program consistent with the National Beach Guidance and Required Performance Criteria for BEACH Act Grants.",
            "keyword": [
                "beaches",
                "recreation",
                "beach act",
                "environment",
                "environment",
                "united states",
                "health"
            ],
            "modified": "2013-02-13",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Bill Kramer, U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)",
                "hasEmail": "mailto:kramer.bill@epa.gov"
            },
            "identifier": "{F1EA07EA-7243-49F1-A50E-682B90DF4741}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BF1EA07EA-7243-49F1-A50E-682B90DF4741%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7BF1EA07EA-7243-49F1-A50E-682B90DF4741%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Drinking Water State Revolving Fund",
            "description": "The Drinking Water State Revolving Fund (DWSRF) National Information Management System collects information that provide a record of progress and accountability for the program.  Reports on DWSRF activity are currently available for state fiscal years (July-June) 1996 through 2010.",
            "keyword": [
                "drinking water",
                "srf",
                "water quality",
                "capital costs",
                "infrastructure",
                "national survey",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2009-07-30",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Safe Drinking Water Hotline",
                "hasEmail": "mailto:safewater@epa.gov"
            },
            "identifier": "{1A9B6384-B900-4E31-A6B1-16FC45402E16}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B1A9B6384-B900-4E31-A6B1-16FC45402E16%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B1A9B6384-B900-4E31-A6B1-16FC45402E16%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Drinking Water Maximum Contaminant Levels (MCLs)",
            "description": "National Primary Drinking Water Regulations (NPDWRs or primary standards) are legally enforceable standards that apply to public water systems. Primary standards protect public health by limiting the levels of contaminants in drinking water.",
            "keyword": [
                "drinking water",
                "sdwa",
                "mcl",
                "contaminants",
                "pollution",
                "human health",
                "public water systems",
                "environment",
                "environment",
                "united states",
                "health"
            ],
            "modified": "2009-05-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Safe Drinking Water Hotline, U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)",
                "hasEmail": "mailto:safewater@epa.gov"
            },
            "identifier": "{801C993D-B195-4B7A-97B6-17B299ED1E95}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B801C993D-B195-4B7A-97B6-17B299ED1E95%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B801C993D-B195-4B7A-97B6-17B299ED1E95%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Distribution (State Allotment) of Drinking Water State Revolving Fund Appropriation from the American Recovery and Reinvestment Act of 2009 (ARRA)",
            "description": "The ARRA appropriation for the DWSRF program is $2,000,000,000. DWSRF allotments are based on percentages derived from the 2003 Drinking Water Infrastructure Needs Survey. For general and government-wide ARRA information, please visit EPA's Recovery site or RECOVERY.gov. This ARRA appropriation is in addition to the DWSRF appropriation for FY 2009",
            "keyword": [
                "drinking water",
                "arra",
                "srf",
                "water quality",
                "capital costs",
                "infrastructure",
                "finance",
                "grants",
                "funds",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2009-07-29",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Safe Drinking Water Hotline, U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)",
                "hasEmail": "mailto:safewater@epa.gov"
            },
            "identifier": "{2CE25440-7393-406C-B21E-45D378344FB2}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B2CE25440-7393-406C-B21E-45D378344FB2%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B2CE25440-7393-406C-B21E-45D378344FB2%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Contaminant Candidate List 3",
            "description": "CCL 3 is a list of contaminants that are currently not subject to any proposed or promulgated national primary drinking water regulations, that are known or anticipated to occur in public water systems, and which may require regulation under the Safe Drinking Water Act (SDWA). The list includes, among others, pesticides, disinfection byproducts, chemicals used in commerce, waterborne pathogens, pharmaceuticals, and biological toxins. The Agency considered the best available data and information on health effects and occurrence to evaluate thousands of unregulated contaminants. EPA used a multi-step process to select 116 candidates for the final CCL 3. The final CCL 3 includes 104 chemicals or chemical groups and 12 microbiological contaminants.",
            "keyword": [
                "drinking water",
                "sdwa",
                "mcl",
                "contaminants",
                "pollution",
                "human health",
                "public water systems",
                "ccl",
                "environment",
                "environment",
                "united states",
                "health"
            ],
            "modified": "2009-10-08",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Safe Drinking Water Hotline",
                "hasEmail": "mailto:safewater@epa.gov"
            },
            "identifier": "{756BBB59-7208-459A-A008-C64107182AAC}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B756BBB59-7208-459A-A008-C64107182AAC%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B756BBB59-7208-459A-A008-C64107182AAC%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Contaminant Candidate List 2",
            "description": "CCL 2 is a list of contaminants that are currently not subject to any proposed or promulgated national primary drinking water regulations, that are known or anticipated to occur in public water systems, and which may require regulation under the Safe Drinking Water Act (SDWA). The list includes, among others, pesticides, disinfection byproducts, chemicals used in commerce, waterborne pathogens, pharmaceuticals, and biological toxins. The Agency considered the best available data and information on health effects and occurrence to evaluate thousands of unregulated contaminants.",
            "keyword": [
                "drinking water",
                "sdwa",
                "mcl",
                "contaminants",
                "pollution",
                "human health",
                "public water systems",
                "ccl",
                "environment",
                "environment",
                "united states",
                "health"
            ],
            "modified": "2005-02-24",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Safe Drinking Water Hotline",
                "hasEmail": "mailto:safewater@epa.gov"
            },
            "identifier": "{479F758A-F9B6-4330-9E0F-933822232A28}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B479F758A-F9B6-4330-9E0F-933822232A28%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B479F758A-F9B6-4330-9E0F-933822232A28%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Contaminant Candidate List 1",
            "description": "CCL 1 is a list of contaminants that are currently not subject to any proposed or promulgated national primary drinking water regulations, that are known or anticipated to occur in public water systems, and which may require regulation under the Safe Drinking Water Act (SDWA). The list includes, among others, pesticides, disinfection byproducts, chemicals used in commerce, waterborne pathogens, pharmaceuticals, and biological toxins. The Agency considered the best available data and information on health effects and occurrence to evaluate thousands of unregulated contaminants.",
            "keyword": [
                "drinking water",
                "sdwa",
                "mcl",
                "contaminants",
                "pollution",
                "human health",
                "public water systems",
                "ccl",
                "environment",
                "environment",
                "united states",
                "health"
            ],
            "modified": "1998-03-02",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Ground Water and Drinking Water (OGWDW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Safe Drinking Water Hotline",
                "hasEmail": "mailto:safewater@epa.gov"
            },
            "identifier": "{C74548B9-0661-4B3D-8980-BF0E9C72C81F}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7BC74548B9-0661-4B3D-8980-BF0E9C72C81F%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BC74548B9-0661-4B3D-8980-BF0E9C72C81F%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "2013 EPA Vessels General Permit (VGP)",
            "description": "Information for any vessel that submitted a Notice of Intent (NOI), Notice of Termination (NOT), or annual report under EPA's 2013 Vessel General Permit (VGP).  Search results will be presented in a table; however, you can also download more detailed information on the vessels identified in these search results into an excel spreadsheet, or an HTML file, which can be saved to your desktop for further review and analysis.",
            "keyword": [
                "permits",
                "npdes",
                "vgp",
                "vessels",
                "discharges",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2014-10-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Wastewater Management (OWM)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Jack Faulk, U.S. EPA Office of Water (OW) - Office of Wastewater Management (OWM)",
                "hasEmail": "mailto:faulk.jack@epa.gov"
            },
            "identifier": "{B4829C41-1361-41A4-A24C-DC40305DC71B}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7BB4829C41-1361-41A4-A24C-DC40305DC71B%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BB4829C41-1361-41A4-A24C-DC40305DC71B%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Beach Advisory and Closing Online Notification (BEACON) system",
            "description": "Beach Advisory and Closing Online Notification system (BEACON) is a colletion of state and local data reported to EPA about beach closings and advisories.  BEACON is the public-facing query of the Program tracking, Beach Advisories, Water quality standards, and Nutrients database (PRAWN) which tracks beach closing and advisory information.",
            "keyword": [
                "datafinder",
                "water",
                "surface water",
                "lakes",
                "oceans",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2013-11-12",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Bill Kramer, U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)",
                "hasEmail": "mailto:kramer.bill@epa.gov"
            },
            "identifier": "020CFECD-E8C1-4FA7-ADC7-CDE9B40F2F2C",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B020CFECD-E8C1-4FA7-ADC7-CDE9B40F2F2C%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B020CFECD-E8C1-4FA7-ADC7-CDE9B40F2F2C%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.htm",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Human Health Benchmarks for Pesticides",
            "description": "Advanced testing methods now allow pesticides to be detected in water at very low levels. These small amounts of pesticides detected in drinking water or source water for drinking water do not necessarily indicate a health risk. The EPA has developed human health benchmarks for 363 pesticides to enable our partners to better determine whether the detection of a pesticide in drinking water or source waters for drinking water may indicate a potential health risk and to help them prioritize monitoring efforts.\n\nThe table below includes benchmarks for acute (one-day) and chronic (lifetime) exposures for the most sensitive populations from exposure to pesticides that may be found in surface or ground water sources of drinking water. The table also includes benchmarks for 40 pesticides in drinking water that have the potential for cancer risk. The HHBP table includes pesticide active ingredients for which Health Advisories or enforceable National Primary Drinking Water Regulations (e.g., maximum contaminant levels) have not been developed.",
            "keyword": [
                "human health",
                "pesticides",
                "drinking water",
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "modified": "2013-08-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Groundwater and Drinking Water (OGWDW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Safe Drinking Water Hotline",
                "hasEmail": "mailto:safewater@epa.gov"
            },
            "identifier": "{0FF393D0-2B3C-47E0-A43A-3E691A72C417}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://www.epa.gov/sdwa/2021-human-health-benchmarks-pesticides",
                "https://edg.epa.gov/metadata/rest/document?id=%7B0FF393D0-2B3C-47E0-A43A-3E691A72C417%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B0FF393D0-2B3C-47E0-A43A-3E691A72C417%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "National Coastal Condition Assessment (NCCA)",
            "description": "During the summer of 2010, state and EPA crews conducted field sampling for the fifth National Coastal Condition Assessment (NCCA). The assessment is in the data analysis and report development phase. A summary of the results of the assessment, National Coastal Condition Assessment 2010, is planned by late 2014. The NCCR IV, which summarizes the findings of the coastal assessment conducted between 2003 and 2006, is now available.",
            "keyword": [
                "national coastal condition assessment",
                "coastal",
                "sampling",
                "assessment",
                "environment",
                "environment",
                "united states",
                "inlandwaters"
            ],
            "modified": "2012-02-02",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Wetlands Oceans and Watersheds (OWOW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Sarah Lehmann, U.S. EPA Office of Water (OW) - Office of Wetlands Oceans and Watersheds (OWOW)",
                "hasEmail": "mailto:lehmann.sarah@epa.gov"
            },
            "identifier": "{8069F7C0-73FD-40AC-9E13-8B06CC7B8D14}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B8069F7C0-73FD-40AC-9E13-8B06CC7B8D14%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B8069F7C0-73FD-40AC-9E13-8B06CC7B8D14%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Commercial Nitrogen Fertilizer Purchased",
            "description": "Amounts of fertilizer nitrogen (N) purchased by states in individual years 2003, 2005, 2007, 2009 and 2011, and the % change in average amounts purchased per year from 2002-2006 to 2007-2011. Fertilizer information is reported by state fertilizer control offices and excludes livestock manure, liming materials, peat, potting soils, soil amendments, soil additives, and soil conditioners.",
            "keyword": [
                "commercial purchases",
                "nitrogen",
                "fertilzer",
                "environment",
                "environment",
                "united states",
                "inlandwaters"
            ],
            "modified": "2002-10-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": " U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Mario Sengco,  U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)",
                "hasEmail": "mailto:sengco.mario@epa.gov"
            },
            "identifier": "{E6ED0B26-F4A5-4DD0-AA45-1BE1101DB2EC}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://www.epa.gov/nutrientpollution/commercial-fertilizer-purchased",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BE6ED0B26-F4A5-4DD0-AA45-1BE1101DB2EC%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7BE6ED0B26-F4A5-4DD0-AA45-1BE1101DB2EC%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Commercial Phosphorus Fertilizer Purchased",
            "description": "Amounts of fertilizer P2O5 purchased by states in individual years 2003, 2005, 2007, 2009 and 2011, and the % change in average amounts purchased per year from 2002-2006 to 2007-2011. Fertilizer information is reported by state fertilizer control offices and excludes livestock manure, liming materials, peat, potting soils, soil amendments, soil additives, and soil conditioners.",
            "keyword": [
                "commercial purchases",
                "phosporus",
                "fertilzer",
                "environment",
                "environment",
                "united states",
                "inlandwaters"
            ],
            "modified": "2002-10-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Mario Sengco, U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)",
                "hasEmail": "mailto:sengco.mario@epa.gov"
            },
            "identifier": "{46B3DC8A-2ABA-47A3-96B5-1567C2496214}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://www.epa.gov/nutrientpollution/commercial-fertilizer-purchased",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B46B3DC8A-2ABA-47A3-96B5-1567C2496214%7D",
                "https://edg.epa.gov/metadata/rest/document?id=%7B46B3DC8A-2ABA-47A3-96B5-1567C2496214%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Estimated Animal Agriculture Nitrogen and Phosphorus from Manure",
            "description": "Animal agriculture manure is a primary source of nitrogen and phosphorus to surface and groundwater. Manure runoff from cropland and pastures or discharging animal feeding operations and concentrated animal feeding operations (CAFOs) often reaches surface and groundwater systems through surface runoff or infiltration. Permitting discharging CAFOs to limit nitrogen and phosphorus discharge to surface waters, and implementing best management practices outlined in a manure management plan are critical steps to protecting water quality. This indicator shows animal agriculture manure produced in states in 2007 and 2017 (the year of the last Census of Agriculture) and expressed in terms of nitrogen and phosphorus content, rather than total amounts of manure, since different animal types produce manure with differing nitrogen and phosphorus concentrations. Data are for cattle, swine, poultry (chickens and turkeys), sheep, and horses. Data are presented as 1000s of kg of manure nitrogen and phosphorus as well as kilograms of manure nitrogen and phosphorus per km2 of farmland.",
            "keyword": [
                "nitrogen",
                "phosporus",
                "n",
                "p",
                "environment",
                "environment",
                "united states",
                "inlandwaters"
            ],
            "modified": "2002-10-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Mario Sengco, U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)",
                "hasEmail": "mailto:sengco.mario@epa.gov"
            },
            "identifier": "{CC5FDADD-8F9D-44CE-90A4-46461820DB9C}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://www.epa.gov/nutrientpollution/estimated-animal-agriculture-nitrogen-and-phosphorus-manure",
                "https://edg.epa.gov/metadata/rest/document?id=%7BCC5FDADD-8F9D-44CE-90A4-46461820DB9C%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BCC5FDADD-8F9D-44CE-90A4-46461820DB9C%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Estimated Total Nitrogen and Total Phosphorus Loads and Yields Generated within States",
            "description": "Estimated state-wide total nitrogen (TN) and total phosphorus (TP) loads and yields, as predicted by the 2012 regional USGS SPARROW models.Excess nitrogen and phosphorus loading impacts not only local waters, but also downstream waterbodies and coastal systems including the Chesapeake Bay, the Great Lakes, the Gulf of Mexico, and Puget Sound. The data in this indicator table are based on output from the United States Geological Survey\u2019s (USGS) Spatially Referenced Regression On Watershed Attributes (SPARROW) models. SPARROW is a watershed modeling tool which, based on a mass-balance approach, estimates the excess amounts (i.e., amounts beyond assimilative capacity) of nitrogen and phosphorus exported from watersheds and delivered to downstream waterbodies. The models relate in-stream water quality measurements of nutrients taken at a network of monitoring stations to spatially referenced attributes of the corresponding watersheds, such as nutrient sources and environmental factors that affect rates of delivery to streams, as well as in-stream processing of nutrients.",
            "keyword": [
                "nutrients",
                "nitrogen",
                "n",
                "phosporus",
                "p",
                "model outputs",
                "sparrow",
                "environment",
                "environment",
                "united states",
                "inlandwaters"
            ],
            "modified": "2002-10-01",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Mario Sengco, U.S. EPA Office of Water (OW) - Office of Science and Technology (OST)",
                "hasEmail": "mailto:sengco.mario@epa.gov"
            },
            "identifier": "{20874229-6A65-4AF7-BBF6-B0CB84B64ED5}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://www.epa.gov/nutrientpollution/estimated-total-nitrogen-and-total-phosphorus-loads-and-yields-generated-within",
                "https://edg.epa.gov/metadata/rest/document?id=%7B20874229-6A65-4AF7-BBF6-B0CB84B64ED5%7D",
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B20874229-6A65-4AF7-BBF6-B0CB84B64ED5%7D"
            ],
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:072"
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "spatial": "-180.0,18.0,-66.0,72.0",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "OW",
            "sourcetitle": "EPA Office of Water",
            "sourcefile": "https://edg.epa.gov/data/public/OW/metadata/OW.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "National Lakes Assessment Data",
            "description": "The National Lakes Assessment (NLA) is a statistical survey of the condition of our nation's lakes, ponds, and reservoirs. It is designed to provide information on the extent of lakes that support healthy biological condition and recreation, estimate how widespread major stressors are that impact lake quality, and provide insight into whether lakes nationwide are getting cleaner.",
            "keyword": [
                "clean water act",
                "lakes",
                "nla",
                "statistical survey",
                "water quality",
                "reservoirs",
                "environment",
                "environment",
                "united states",
                "inlandwaters"
            ],
            "modified": "2010-08-13",
            "issued": "2014-01-01",
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. EPA Office of Water (OW) - Office of Wetlands Oceans and Watersheds (OWOW)"
            },
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "Sarah Lehmann, U.S. EPA Office of Water (OW) - Office of Wetlands Oceans and Watersheds (OWOW)",
                "hasEmail": "mailto:lehmann.sarah@epa.gov"
            },
            "identifier": "{668F7BE3-50D1-465C-A73D-B21625689159}",
            "accessLevel": "public",
            "accrualPeriodicity": "irregular",
            "references": [
                "https://www.epa.gov/national-aquatic-resource-surveys/nla",
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            "description": "The Wadeable Streams Assessment (WSA) is a first-ever statistically-valid survey of the biological condition of small streams throughout the U.S. EPA worked with the states to conduct the assessment in 2000-2004. 1,392 sites were selected at random to represent the condition of all streams in regions that share similar ecological characteristics. Participants used the same standardized methods at all sites, to ensure results that are comparable across the nation.",
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                "en-us",
                "en"
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            "description": "In response to The Deepwater Horizon oil spill (also referred to as the BP oil spill), EPA monitored air near the spill.  While emergency response data collection has ended, results continue to be available on this site.",
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            "title": "The Deepwater Horizon oil spill (also referred to as the BP oil spill) in the Gulf of Mexico Air Data",
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            "identifier": "C34A756B-3237-449F-B7D4-642580811389",
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            "accessLevel": "public",
            "description": "Tracks the Circulation, Production, and Maintenance of Superfund site records and related information.  Identifies records structure for Superfund sites in the Region",
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            "title": "Superfund Quick Records Management System",
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        {
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            "description": "The Great Lakes Initiative Toxicity Data Clearinghouse is a central location for information on criteria, toxicity data, exposure parameters and other supporting documents used in developing water quality standards in the Great Lakes Watershed.",
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            "sourcefile": "https://edg.epa.gov/data/public/R5/R5.json"
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        {
            "@type": "dcat:Dataset",
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            "description": "A catalog of the holdings (i.e. books, documents, journals, etc) in all the EPA libraries.  It is available to the public via epa.gov.  In addition to being an online catalog, it also has modules that support the various operations of the libraries (circulation, serials management, dispersal tracking) that are only accessible by authorized users.",
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            "holdren": "No",
            "ORG": "R05",
            "sourcetitle": "EPA Region 5",
            "sourcefile": "https://edg.epa.gov/data/public/R5/R5.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Region 6"
            },
            "accessLevel": "public",
            "description": "Compliance Assurance and Enforcement Division Document Repository (CAEDDOCRESP) provides internal and external access of Inspection Records, Enforcement Actions, and National Environmental Protection Act (NEPA) documents to all CAED staff. NEPA is a foundational U.S. law, enacted in 1970, that requires federal agencies to assess the environmental effects of proposed major actions before making decisions. It mandates transparency, public participation, and the consideration of alternatives to ensure informed, environmentally responsible agency actions. The respository will also include supporting documents, images, etc.",
            "keyword": [
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "CAED Document Repository",
            "issued": "2014-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
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            "accrualPeriodicity": "irregular",
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                "020:072"
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            "license": "https://edg.epa.gov/EPA_Data_License.htm",
            "contactPoint": {
                "hasEmail": "mailto:Nguyen.Linh@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Linh Nguyen, U.S. Environmental Protection Agency, Region 6"
            },
            "identifier": "3A9C90DA-5D98-49E5-9435-2655A7DFA5D4",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "R06",
            "sourcetitle": "EPA Region 6",
            "sourcefile": "https://edg.epa.gov/data/public/R6/metadata/Region6.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Region 6"
            },
            "accessLevel": "public",
            "description": "The initial module incorporated into the application was the eDisclosure module to track regulatory audit disclosure reports that come through EPA's Central Data Exchange to Region 6 for review, and if approved, route Notice of Determinations back to the disclosing entity via email. This module was developed in 2007 and approved for use on the local area network in September 2008.",
            "keyword": [
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "eSelf Disclosure",
            "issued": "2014-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
                "020:00"
            ],
            "references": [
                "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BCB4991F6-7F92-4944-A68D-82E26AA062DD%7D",
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            "license": "https://edg.epa.gov/EPA_Data_License.htm",
            "contactPoint": {
                "hasEmail": "mailto:Griffin.Debra@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Debra Griffin, U.S. Environmental Protection Agency, Region 6"
            },
            "identifier": "CB4991F6-7F92-4944-A68D-82E26AA062DD",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "R06",
            "sourcetitle": "EPA Region 6",
            "sourcefile": "https://edg.epa.gov/data/public/R6/metadata/Region6.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Region 6"
            },
            "accessLevel": "public",
            "description": "Web Based Training for Integrated Compliance Information System Updated Compliance Monitoring Training for ICIS Federal Enforcement and Compliance User. This training goes through the changes in the screens for the application.",
            "keyword": [
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "ICIS FE&C Compliance Monitoring Screens",
            "issued": "2014-01-01",
            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
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            ],
            "references": [
                "https://edg.epa.gov/metadata/rest/document?id=%7B21765B81-E9FA-4E89-802D-75C84321200B%7D",
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            "license": "https://edg.epa.gov/EPA_Data_License.htm",
            "contactPoint": {
                "hasEmail": "mailto:Nguyen.Linh@epa.gov",
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                "fn": "Linh Nguyen, U.S. Environmental Protection Agency, Region 6"
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            "identifier": "21765B81-E9FA-4E89-802D-75C84321200B",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "R06",
            "sourcetitle": "EPA Region 6",
            "sourcefile": "https://edg.epa.gov/data/public/R6/metadata/Region6.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Region 6"
            },
            "accessLevel": "public",
            "description": "This database processes approximately 3,000 Notice of Arrival (NOA) reporting forms from importers and exporters of pesticide products. This is an electronic version of the EPA Form 3540-1. The external user fills out the NOA and submits it electronically. The form is then processed by the Pesticides section and either approved or disapproved. The system then generates an Adobe PDF version of the EPA Form 3540-1 with signature or disapproval and emailed to the external user. The e-filing system eliminates the need for the Region to invest in paper, copying, storage and mailing expenses, while at the same time allowing the regulated community to conduct its business with us in a more expeditious manner.",
            "keyword": [
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                "environment",
                "united states",
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            ],
            "title": "R6 FIFRA e-Notice of Arrival",
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            "modified": "2014-01-01",
            "dataQuality": false,
            "bureauCode": [
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            "license": "https://edg.epa.gov/EPA_Data_License.htm",
            "contactPoint": {
                "hasEmail": "mailto:Carroll.Craig@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Craig Carroll, U.S. Environmental Protection Agency, Region 6"
            },
            "identifier": "6C81BB2B-6314-4248-9382-DA59097D9658",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "R06",
            "sourcetitle": "EPA Region 6",
            "sourcefile": "https://edg.epa.gov/data/public/R6/metadata/Region6.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Region 6"
            },
            "accessLevel": "public",
            "description": "This database tracks the status of all Quality Assurance documents as required by 40 CFR Parts 30 and 31. 40 CFR Parts 30 and 31 historically established the uniform administrative requirements for EPA grants and cooperative agreements. Part 30 covered agreements with non-profit organizations, hospitals, and universities, while Part 31 applied to state and local governments. These regulations have largely been superseded by 2 CFR Part 200.",
            "keyword": [
                "environment",
                "environment",
                "united states",
                "environment"
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            "title": "Region 6 QTRAK",
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            "dataQuality": false,
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            "contactPoint": {
                "hasEmail": "mailto:Nguyen.Linh@epa.gov",
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                "fn": "Linh Nguyen, U.S. Environmental Protection Agency, Region 6"
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            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "R06",
            "sourcetitle": "EPA Region 6",
            "sourcefile": "https://edg.epa.gov/data/public/R6/metadata/Region6.json"
        },
        {
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency, Region 6"
            },
            "accessLevel": "public",
            "description": "This is now a storage and retrieval application. Permit information and enforcement information of Underground Injection Wells are scanned and stored as a part of this application.",
            "keyword": [
                "environment",
                "environment",
                "united states",
                "environment"
            ],
            "title": "Region 6 Underground Injection Control (UIC) Program",
            "issued": "2014-01-01",
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            "dataQuality": false,
            "bureauCode": [
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            "references": [
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            "programCode": [
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            "license": "https://edg.epa.gov/EPA_Data_License.htm",
            "contactPoint": {
                "hasEmail": "mailto:Eckhart.Jeanne@epa.gov",
                "@type": "vcard:Contact",
                "fn": "Jeanne Eckhart, U.S. Environmental Protection Agency, Region 6"
            },
            "identifier": "C6B690AD-63E8-4B13-93CB-B78469E81F8C",
            "@type": "dcat:Dataset",
            "geo": "No",
            "holdren": "No",
            "ORG": "R06",
            "sourcetitle": "EPA Region 6",
            "sourcefile": "https://edg.epa.gov/data/public/R6/metadata/Region6.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "NPL-PAD (National Priorities List Publication Assistance Database) for Region 7",
            "description": "THIS DATA ASSET NO LONGER ACTIVE: This is metadata documentation for the National Priorities List (NPL) Publication Assistance Databsae (PAD), a Lotus Notes application that holds Region 7's universe of NPL site information such as site description, threats and contaminants, cleanup approach, environmental process, community involvement, site repository, and regional contacts. This database used to be updated annually, at different times for different NPLs, but it is currently no longer being used.  This work fell under objectives for EPA's 2003-2008 Strategic Plan (Goal 3) for Land Preservation & Restoration, which are to clean up and reuse contaminated land.",
            "keyword": [
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                "cleanup",
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                "name": "U.S. Environmental Protection Agency, Region 7"
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                "fn": "Mary Peterson, U.S. Environmental Protection Agency, Region 7",
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            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "R07",
            "sourcetitle": "EPA Region 7",
            "sourcefile": "https://edg.epa.gov/data/public/R7/metadata/R7.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "INSPTRAX - The Inspection Targeting, Planning and Tracking Database",
            "description": "The INSPTRAX System tracks Air, RCRA, and Water inspection targeting, planning and tracking information. It is used by the the Air, RCRA, and Water programs to input annual inspection targets, then used by the Region to send a list of draft and final targets to Region 7 four states (Iowa, Kansas, Missouri, Nebraska). It is then used to generate quarterly inspection schedules for conducting the actural inspection activities by our ENSV inspectors and finally used to track all inspection activities.",
            "keyword": [
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            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "R07",
            "sourcetitle": "EPA Region 7",
            "sourcefile": "https://edg.epa.gov/data/public/R7/metadata/R7.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Air Compliance Complaint Database (ACCD)",
            "description": "THIS DATA ASSET NO LONGER ACTIVE:  This is metadata documentation for the Region 7 Air Compliance Complaint Database (ACCD) which logs all air pollution complaints received by Region 7. It contains information about the complaint along with how the complaint was addressed. The Air and Waste Management Division is the primary managing entity for this database.  This work falls under objectives for EPA's 2003-2008 Strategic Plan (Goal 1) for Clean Air & Global Climate Change, which are to achieve healthier outdoor air.",
            "keyword": [
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            "geo": "No",
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            "sourcefile": "https://edg.epa.gov/data/public/R7/metadata/R7.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Drycleaner Database - Region 7",
            "description": "THIS DATA ASSET NO LONGER ACTIVE: This is metadata documentation for the Region 7 Drycleaner Database (R7DryClnDB) which tracks all Region7 drycleaners who notify Region 7 subject to Maximum Achievable Control Technologiy (MACT) standards. The Air and Waste Management Division is the primary managing entity for this database.  This work falls under objectives for EPA's 2003-2008 Strategic Plan (Goal 4) for Healthy Communities & Ecosystems, which are to reduce chemical and/or pesticide risks at facilities.",
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            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "R07",
            "sourcetitle": "EPA Region 7",
            "sourcefile": "https://edg.epa.gov/data/public/R7/metadata/R7.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Quality Assurance Tracking System - R7 (QATS-R7)",
            "description": "This is metadata documentation for the Quality Assurance Tracking System - R7, an EPA Region 7 resource that tracks information on quality assurance reviews.  Also called the QA Tracking System-R7 or QATS-R7.  The reviews are completed under the Environmental Services (ENSV) Divsion at EPA Region 7.",
            "keyword": [
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                "iowa",
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            "modified": "2000-01-03",
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            "license": "https://edg.epa.gov/EPA_Data_License.htm",
            "spatial": "-104.056219,35.989656,-89.105034,43.501457",
            "dataQuality": false,
            "geo": "No",
            "holdren": "No",
            "ORG": "R07",
            "sourcetitle": "EPA Region 7",
            "sourcefile": "https://edg.epa.gov/data/public/R7/metadata/R7.json"
        },
        {
            "@type": "dcat:Dataset",
            "title": "Region 7 Laboratory Information Management System",
            "description": "This is metadata documentation for the Region 7 Laboratory Information Management System (R7LIMS) which maintains records for the Regional Laboratory.  Any Laboratory analytical work performed is stored in this system which replaces LIMS-Lite, and before that LAST.  The EPA and its contractors may use this database. The Office of Policy & Management (PLMG) Division at EPA Region 7 is the primary managing entity; contractors can access this database but it is not accessible to the public.",
            "keyword": [
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                "iowa",
                "kansas",
                "missouri",
                "nebraska",
                "environment"
            ],
            "modified": "2006-03-04",
            "publisher": {
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                "name": "U.S. Environmental Protection Agency, Region 7"
            },
            "contactPoint": {
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                "fn": "Richard Dixon, U.S. Environmental Protection Agency, Region 7",
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            "identifier": "E88D7D87-3331-4420-8BF3-2779512B36F6",
            "accessLevel": "restricted public",
            "accrualPeriodicity": "irregular",
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            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/83eb-xbyy",
            "bureauCode": [
                "020:00"
            ],
            "issued": "2025-01-24",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
            "keyword": [
                "heat pumps",
                "air source heat pumps"
            ],
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/83eb-xbyy",
            "description": "Certified models meet all ENERGY STAR requirements as listed in the Version 6.1 or 6.2 ENERGY STAR Program Requirements for Air-Source Heat Pumps that are effective as of January 1, 2023. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/heating_cooling/heat_pumps_air_source/key_product_criteria",
            "title": "ENERGY STAR Certified Heat Pumps",
            "programCode": [
                "020:033"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/83eb-xbyy/export.csv?accessType=DOWNLOAD",
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                },
                {
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                    "describedBy": "https://data.energystar.gov/api/views/83eb-xbyy/columns.json",
                    "describedByType": "application/json",
                    "@type": "dcat:Distribution"
                },
                {
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                    "downloadURL": "https://data.energystar.gov/api/v3/views/83eb-xbyy/query.xml?accessType=DOWNLOAD",
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                    "describedByType": "application/xml",
                    "@type": "dcat:Distribution"
                }
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "theme": [
                "Active Specifications"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/8dv7-nngq",
            "bureauCode": [
                "020:00"
            ],
            "issued": "2021-09-07",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
            "keyword": [
                "vent fans",
                "ventilating fans"
            ],
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/8dv7-nngq",
            "description": "Certified models meet all ENERGY STAR requirements as listed in the Version 4.0 ENERGY STAR Program Requirements for Ventilating Fans that were effective as of October 1, 2015 or the Version 4.1 requirements that are effective as of July 24, 2018. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/heating_cooling/fans_ventilating/key_product_criteria .",
            "title": "ENERGY STAR Certified Ventilating Fans",
            "programCode": [
                "020:033"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/8dv7-nngq/export.csv?accessType=DOWNLOAD",
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                {
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                },
                {
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                    "downloadURL": "https://data.energystar.gov/api/v3/views/8dv7-nngq/query.xml?accessType=DOWNLOAD",
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                    "describedByType": "application/xml",
                    "@type": "dcat:Distribution"
                }
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "theme": [
                "Active Specifications"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/8edu-y555",
            "bureauCode": [
                "020:00"
            ],
            "issued": "2022-06-29",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
            "keyword": [
                "untagged"
            ],
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/8edu-y555",
            "description": "A list of all UPC codes and corresponding model numbers provided by partners for ENERGY STAR certified products. The brand, model name and model number continue to serve as the identifiers used to establish certification. The UPC code data below is intended to aid in identification of ENERGY STAR models. UPC code data is not provided for all certified models.",
            "title": "ENERGY STAR Certified Products  UPC Codes",
            "programCode": [
                "020:033"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/8edu-y555/export.csv?accessType=DOWNLOAD",
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                {
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                {
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                    "@type": "dcat:Distribution"
                }
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/8t9c-g3tn",
            "bureauCode": [
                "020:00"
            ],
            "issued": "2021-12-06",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
            "keyword": [
                "residential freezers"
            ],
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/8t9c-g3tn",
            "description": "Certified models meet all ENERGY STAR requirements as listed in the Version 5.0 ENERGY STAR Program Requirements for Residential Refrigerators and Freezers that are effective as of September 15, 2014. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/appliances/refrigerators/key_product_criteria",
            "title": "ENERGY STAR Certified Residential Freezers",
            "programCode": [
                "020:033"
            ],
            "distribution": [
                {
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                },
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                    "downloadURL": "https://data.energystar.gov/api/v3/views/8t9c-g3tn/query.xml?accessType=DOWNLOAD",
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                    "@type": "dcat:Distribution"
                }
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "theme": [
                "Active Specifications"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/8wj2-sec8",
            "bureauCode": [
                "020:00"
            ],
            "issued": "2022-10-18",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
            "keyword": [
                "untagged"
            ],
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/8wj2-sec8",
            "description": "This data set contains a simplified list of all currently certified ENERGY STAR models with basic model information collected across all product categories including ENERGY STAR Unique IDs, ENERGY STAR partners, model names and numbers, and brand names. Learn more about ENERGY STAR products at www.energystar.gov/products. A full list of ENERGY STAR specifications can be found at www.energystar.gov/specifications.",
            "title": "ENERGY STAR Model Index",
            "programCode": [
                "020:033"
            ],
            "distribution": [
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                    "downloadURL": "https://data.energystar.gov/api/v3/views/8wj2-sec8/export.csv?accessType=DOWNLOAD",
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                {
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                    "describedByType": "application/json",
                    "@type": "dcat:Distribution"
                },
                {
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                    "downloadURL": "https://data.energystar.gov/api/v3/views/8wj2-sec8/query.xml?accessType=DOWNLOAD",
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                    "describedByType": "application/xml",
                    "@type": "dcat:Distribution"
                }
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "theme": [
                "Active Specifications"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/9g6r-cpdt",
            "bureauCode": [
                "020:00"
            ],
            "issued": "2018-02-04",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
            "keyword": [
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            ],
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/9g6r-cpdt",
            "description": "Certified models meet all ENERGY STAR requirements as listed in the Version 8.0 ENERGY STAR Program Requirements for Clothes Washers that are effective as of February 5, 2018. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/appliances/clothes_washers/key_product_criteria.",
            "title": "ENERGY STAR Certified Commercial Clothes Washers",
            "programCode": [
                "020:033"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/9g6r-cpdt/export.csv?accessType=DOWNLOAD",
                    "mediaType": "text/csv"
                },
                {
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                    "downloadURL": "https://data.energystar.gov/api/v3/views/9g6r-cpdt/query.json?accessType=DOWNLOAD",
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                },
                {
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                    "downloadURL": "https://data.energystar.gov/api/v3/views/9g6r-cpdt/query.xml?accessType=DOWNLOAD",
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                    "@type": "dcat:Distribution"
                }
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "theme": [
                "Active Specifications"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/acvd-5wvz",
            "bureauCode": [
                "020:00"
            ],
            "issued": "2021-09-09",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
            "keyword": [
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            ],
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
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                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/acvd-5wvz",
            "description": "All ENERGY STAR certified geothermal heat pump models are recognized as Most Efficient, as they deliver superior performance, particularly when it is very cold or very hot. Certified models meet all ENERGY STAR requirements as listed in the Version 3.0 ENERGY STAR Program Requirements for Geothermal Heat Pumps that are effective as of January 1, 2012 or the Version 3.2 Program Requirements that are effective as of July 16, 2020. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/heating_cooling/heat_pumps_geothermal/key_product_criteria.",
            "title": "ENERGY STAR Certified Geothermal Heat Pumps",
            "programCode": [
                "020:033"
            ],
            "distribution": [
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                    "@type": "dcat:Distribution",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/acvd-5wvz/export.csv?accessType=DOWNLOAD",
                    "mediaType": "text/csv"
                },
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                    "describedByType": "application/json",
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                },
                {
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                    "downloadURL": "https://data.energystar.gov/api/v3/views/acvd-5wvz/query.xml?accessType=DOWNLOAD",
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                    "describedByType": "application/xml",
                    "@type": "dcat:Distribution"
                }
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "theme": [
                "Active Specifications"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/bghd-e2wd",
            "bureauCode": [
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            ],
            "issued": "2021-06-07",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
            "keyword": [
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            ],
            "contactPoint": {
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                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/bghd-e2wd",
            "description": "Certified models meet all ENERGY STAR requirements as listed in the Version 8.0 and Version 8.1 ENERGY STAR Program Requirements for Clothes Washers that are effective as of February 5, 2018. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/appliances/clothes_washers/key_product_criteria",
            "title": "ENERGY STAR Certified Residential Clothes Washers",
            "programCode": [
                "020:033"
            ],
            "distribution": [
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                    "mediaType": "text/csv"
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            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "theme": [
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            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/bpzy-9tg8",
            "bureauCode": [
                "020:00"
            ],
            "issued": "2021-09-07",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
            "keyword": [
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            ],
            "contactPoint": {
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                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/bpzy-9tg8",
            "description": "Certified models meet all ENERGY STAR requirements as listed in the Version 3.0 ENERGY STAR Program Requirements for Telephony (cordless telephones and VoIP telephones) that are effective as of October 1, 2014. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/electronics/cordless_phones/key_product_criteria",
            "title": "ENERGY STAR Certified Telephones",
            "programCode": [
                "020:033"
            ],
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                    "downloadURL": "https://data.energystar.gov/api/v3/views/bpzy-9tg8/query.xml?accessType=DOWNLOAD",
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            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "theme": [
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            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/c8av-ccf7",
            "bureauCode": [
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            ],
            "issued": "2022-12-12",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
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            ],
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/c8av-ccf7",
            "description": "Certified models meet all ENERGY STAR requirements as listed in the V3.0 ENERGY STAR Program Requirements for Commercial Ovens that are effective as of January 12, 2023. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/commercial_food_service_equipment/commercial_ovens/key_product_criteria",
            "title": "ENERGY STAR Certified Commercial Ovens",
            "programCode": [
                "020:033"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/c8av-ccf7/export.csv?accessType=DOWNLOAD",
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                },
                {
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                    "downloadURL": "https://data.energystar.gov/api/v3/views/c8av-ccf7/query.json?accessType=DOWNLOAD",
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                    "describedByType": "application/json",
                    "@type": "dcat:Distribution"
                },
                {
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                "@type": "vcard:Contact",
                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/t9u7-4d2j",
            "description": "Certified dryers and combination all-in-one washer-dryers that meet all ENERGY STAR requirements as listed in the Version 1.1 ENERGY STAR Program Requirements for Clothes Dryers that are effective as of January 1, 2015. Combination all-in-one washer-dryers also meet the Version 8.1 ENERGY STAR Program Requirements for Clothes Washers that are effective as of February 5, 2018. A detailed listing of key efficiency criteria are available at: https://www.energystar.gov/products/appliances/clothes_dryers/key_product_criteria",
            "title": "ENERGY STAR Certified Residential Clothes Dryers",
            "programCode": [
                "020:033"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/t9u7-4d2j/export.csv?accessType=DOWNLOAD",
                    "mediaType": "text/csv"
                },
                {
                    "mediaType": "application/json",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/t9u7-4d2j/query.json?accessType=DOWNLOAD",
                    "describedBy": "https://data.energystar.gov/api/views/t9u7-4d2j/columns.json",
                    "describedByType": "application/json",
                    "@type": "dcat:Distribution"
                },
                {
                    "mediaType": "application/xml",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/t9u7-4d2j/query.xml?accessType=DOWNLOAD",
                    "describedBy": "https://data.energystar.gov/api/views/t9u7-4d2j/columns.xml",
                    "describedByType": "application/xml",
                    "@type": "dcat:Distribution"
                }
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "theme": [
                "Active Specifications"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/vtsv-aq9u",
            "bureauCode": [
                "020:00"
            ],
            "issued": "2021-09-15",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
            "keyword": [
                "commercial steam cookers"
            ],
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/vtsv-aq9u",
            "description": "Certified models meet all ENERGY STAR requirements as listed in the Version 1.2 ENERGY STAR Program Requirements for Commercial Steam Cookers that are effective as of August 1, 2003. A detailed listing of key efficiency criteria are available at  https://www.energystar.gov/products/commercial_food_service_equipment/commercial_steam_cookers/key_product_criteria",
            "title": "ENERGY STAR Certified Commercial Steam Cookers",
            "programCode": [
                "020:033"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/vtsv-aq9u/export.csv?accessType=DOWNLOAD",
                    "mediaType": "text/csv"
                },
                {
                    "mediaType": "application/json",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/vtsv-aq9u/query.json?accessType=DOWNLOAD",
                    "describedBy": "https://data.energystar.gov/api/views/vtsv-aq9u/columns.json",
                    "describedByType": "application/json",
                    "@type": "dcat:Distribution"
                },
                {
                    "mediaType": "application/xml",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/vtsv-aq9u/query.xml?accessType=DOWNLOAD",
                    "describedBy": "https://data.energystar.gov/api/views/vtsv-aq9u/columns.xml",
                    "describedByType": "application/xml",
                    "@type": "dcat:Distribution"
                }
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "theme": [
                "Active Specifications"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/wati-2tfp",
            "bureauCode": [
                "020:00"
            ],
            "issued": "2022-11-21",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
            "keyword": [
                "commercial refrigerators and freezers"
            ],
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/wati-2tfp",
            "description": "Certified models meet all ENERGY STAR requirements as listed in the Version 5.0 ENERGY STAR Program Requirements for Commercial Refrigerators and Freezers that are effective as of December 22, 2022. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/commercial_food_service_equipment/commercial_refrigerators_freezers/key_product_criteria.",
            "title": "ENERGY STAR Certified Commercial Refrigerators and Freezers",
            "programCode": [
                "020:033"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/wati-2tfp/export.csv?accessType=DOWNLOAD",
                    "mediaType": "text/csv"
                },
                {
                    "mediaType": "application/json",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/wati-2tfp/query.json?accessType=DOWNLOAD",
                    "describedBy": "https://data.energystar.gov/api/views/wati-2tfp/columns.json",
                    "describedByType": "application/json",
                    "@type": "dcat:Distribution"
                },
                {
                    "mediaType": "application/xml",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/wati-2tfp/query.xml?accessType=DOWNLOAD",
                    "describedBy": "https://data.energystar.gov/api/views/wati-2tfp/columns.xml",
                    "describedByType": "application/xml",
                    "@type": "dcat:Distribution"
                }
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "theme": [
                "Active Specifications"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/wjtt-3zwd",
            "bureauCode": [
                "020:00"
            ],
            "issued": "2026-04-15",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
            "keyword": [
                "untagged"
            ],
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/wjtt-3zwd",
            "description": "Certified models meet all ENERGY STAR requirements as listed in the Version 1.0 ENERGY STAR Program Requirements for Medical Imaging Equipment that are effective as of November 3rd 2025. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/medical-imaging-equipment",
            "title": "ENERGY STAR Certified Medical Imaging Equipment",
            "programCode": [
                "020:033"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/wjtt-3zwd/export.csv?accessType=DOWNLOAD",
                    "mediaType": "text/csv"
                },
                {
                    "mediaType": "application/json",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/wjtt-3zwd/query.json?accessType=DOWNLOAD",
                    "describedBy": "https://data.energystar.gov/api/views/wjtt-3zwd/columns.json",
                    "describedByType": "application/json",
                    "@type": "dcat:Distribution"
                },
                {
                    "mediaType": "application/xml",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/wjtt-3zwd/query.xml?accessType=DOWNLOAD",
                    "describedBy": "https://data.energystar.gov/api/views/wjtt-3zwd/columns.xml",
                    "describedByType": "application/xml",
                    "@type": "dcat:Distribution"
                }
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "theme": [
                "Active Specifications"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/wyw6-sr4d",
            "bureauCode": [
                "020:00"
            ],
            "issued": "2021-09-14",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
            "keyword": [
                "commercial hot food holding cabinets"
            ],
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/wyw6-sr4d",
            "description": "Certified models meet all ENERGY STAR requirements as listed in the Version 2.0 ENERGY STAR Program Requirements for Commercial Hot Food Holding Cabinets that are effective as of October 1, 2011. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/commercial_food_service_equipment/commercial_hot_food_holding_cabinets/key_product_criteria.",
            "title": "ENERGY STAR Certified Commercial Hot Food Holding Cabinet",
            "programCode": [
                "020:033"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/wyw6-sr4d/export.csv?accessType=DOWNLOAD",
                    "mediaType": "text/csv"
                },
                {
                    "mediaType": "application/json",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/wyw6-sr4d/query.json?accessType=DOWNLOAD",
                    "describedBy": "https://data.energystar.gov/api/views/wyw6-sr4d/columns.json",
                    "describedByType": "application/json",
                    "@type": "dcat:Distribution"
                },
                {
                    "mediaType": "application/xml",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/wyw6-sr4d/query.xml?accessType=DOWNLOAD",
                    "describedBy": "https://data.energystar.gov/api/views/wyw6-sr4d/columns.xml",
                    "describedByType": "application/xml",
                    "@type": "dcat:Distribution"
                }
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "theme": [
                "Active Specifications"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "accessLevel": "public",
            "landingPage": "https://data.energystar.gov/d/xmq6-bm79",
            "bureauCode": [
                "020:00"
            ],
            "issued": "2021-09-16",
            "@type": "dcat:Dataset",
            "modified": "2026-09-11",
            "keyword": [
                "commercial water heaters"
            ],
            "contactPoint": {
                "@type": "vcard:Contact",
                "fn": "EPA ENERGY STAR program",
                "hasEmail": "mailto:certification@energystar.gov"
            },
            "publisher": {
                "@type": "org:Organization",
                "name": "U.S. Environmental Protection Agency"
            },
            "identifier": "https://data.energystar.gov/api/views/xmq6-bm79",
            "description": "Certified models meet all ENERGY STAR requirements as listed in the Version 2.0 ENERGY STAR Program Requirements for Commercial Water Heaters that are effective as of  October 1, 2018. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/water_heaters/commercial_water_heaters/key_product_criteria .",
            "title": "ENERGY STAR Certified Commercial Water Heaters",
            "programCode": [
                "020:033"
            ],
            "distribution": [
                {
                    "@type": "dcat:Distribution",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/xmq6-bm79/export.csv?accessType=DOWNLOAD",
                    "mediaType": "text/csv"
                },
                {
                    "mediaType": "application/json",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/xmq6-bm79/query.json?accessType=DOWNLOAD",
                    "describedBy": "https://data.energystar.gov/api/views/xmq6-bm79/columns.json",
                    "describedByType": "application/json",
                    "@type": "dcat:Distribution"
                },
                {
                    "mediaType": "application/xml",
                    "downloadURL": "https://data.energystar.gov/api/v3/views/xmq6-bm79/query.xml?accessType=DOWNLOAD",
                    "describedBy": "https://data.energystar.gov/api/views/xmq6-bm79/columns.xml",
                    "describedByType": "application/xml",
                    "@type": "dcat:Distribution"
                }
            ],
            "license": "https://edg.epa.gov/EPA_Data_License.html",
            "theme": [
                "Active Specifications"
            ],
            "geo": "No",
            "holdren": "No",
            "ORG": "OAR",
            "sourcetitle": "EnergyStar",
            "sourcefile": "https://data.energystar.gov/data.json"
        },
        {
            "title": "StreamCat",
            "description": "The StreamCat Dataset provides summaries of natural and anthropogenic landscape features for ~2.65 million streams, and their associated catchments, within the conterminous USA. \n\nThis dataset is associated with the following publication:\nHill, R.A., M. Weber , S. Leibowitz , T. Olsen , and D.J. Thornbrugh. The Stream-Catchment (StreamCat) Dataset: A database of watershed metrics for the conterminous USA.   JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION. American Water Resources Association, Middleburg, VA, USA,  9, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-qz6k-6",
            "keyword": [
                "streams",
                "catchments",
                "watersheds",
                "watershed metrics",
                "National Hydrography Dataset Plus (NHDPlus)",
                "database",
                "conterminous USA",
                "spatial prediction"
            ],
            "contactPoint": {
                "fn": "Marc Weber",
                "hasEmail": "mailto:weber.marc@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset"
                }
            ],
            "modified": "2015-08-17",
            "references": [
                "https://doi.org/10.1111/1752-1688.12372"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "HexSim",
            "description": "Not applicable. This dataset is not publicly accessible because: Source code comments are the only item that meets the stated criteria for data.\r\nThe source code is not meaningful to store in ScienceHub and stored in with redundancy both on and off site.\r\nIt changes frequently. It can be accessed through the following means: The source code lives within a version control application and is not generally available to the public. Format: There are no datasets to add. \n\nThis dataset is associated with the following publication:\nDunk, J.R., B. Woodbridge, E.M. Glenn, R.J. Davis, K. Fitzgerald, P. Henson, D.W. LaPlante, B.G. Marcot, B.R. Noon, M.G. Raphael, N. Schumaker , and B. White. The Scientific Basis for Modeling Northern Spotted Owl Habitat: A Response to Loehle, Irwin, Manly, and Merrill.   FOREST ECOLOGY AND MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 358: 355-360, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1390068",
            "keyword": [
                "HexSim",
                "Simulation Model",
                "wildlife",
                "plants"
            ],
            "contactPoint": {
                "fn": "Nathan Schumaker",
                "hasEmail": "mailto:schumaker.nathan@epa.gov"
            },
            "distribution": [],
            "modified": "2005-01-01",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Marcell peatland carbon and nitrogen dynamics",
            "description": "This dataset include US Forest Service (contact Dr. Stephen Sebestyen at USFS) long-term precipitation, atmospheric deposition, and hydrologic data for the years 2010-2013. The dataset also includes unique (never before collected) data on ammonification, denitrification, microbial enzyme activity, and nitrification. These data will be useful for long-term trend analyses and for further investigations on carbon and nitrogen cycling in peatlands. \n\nThis dataset is associated with the following publication:\nHill , B., T. Jicha , L. Lehto, C. Elonen , S. Sebestyen , and R. Kolka. Comparisons of soil nitrogen mass balances for an ombrotrophic bog and a minerotrophic fen in northern Minnesota.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 550: 880-892, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-h18p-3",
            "keyword": [
                "peatlands",
                "microbial enzyme activity",
                "ammonification",
                "bog",
                "dentrification",
                "fen",
                "nitrification",
                "watershed N budget"
            ],
            "contactPoint": {
                "fn": "Brian Hill",
                "hasEmail": "mailto:hill.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "Marcell_all.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/3/Marcell_all.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2015-05-20",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.01.178"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/3/documents/MARCELL_All%20Data%20Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Estimation of Radiative Efficiency of Chemicals with Potentially Significant Global Warming Potential",
            "description": "The set of commercially available chemical substances in commerce that may have significant global warming potential (GWP) is not well defined. Although there are currently over 200 chemicals with high GWP reported by the Intergovernmental Panel on Climate Change, World Meteorological Organization, or Environmental Protection Agency, there may be hundreds of additional chemicals that may also have significant GWP. Evaluation of various approaches to estimate radiative efficiency (RE) and atmospheric lifetime will help to refine GWP estimates for compounds where no measured IR spectrum is available. This study compares values of RE calculated using computational chemistry techniques for 235 chemical compounds against the best available values. It is important to assess the reliability of the underlying computational methods for computing RE to understand the sources of deviations from the best available values. Computed vibrational frequency data is used to estimate RE values using several Pinnock-type models. The values derived using these models are found to be in reasonable agreement with reported RE values (though significant improvement is obtained through scaling). The effect of varying the computational method and basis set used to calculate the frequency data is also discussed. It is found that the vibrational intensities have a strong dependence on basis set and are largely responsible for differences in computed values of RE in this study. Deviations of calculated RE values are also analyzed by chemical classification, and it is found that some classes are computed more accurately than others. \n\nThis dataset is associated with the following publication:\nBetowski , D., C. Bevington , and T. Allison. Estimation of Radiative Forcing of Chemicals with Potentially Significant Global Warming Potential.   CRITICAL REVIEWS IN ENVIRONMENTAL SCIENCE AND TECHNOLOGY. CRC Press LLC, Boca Raton, FL, USA, 0(0): 1-31, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-rbpj-11",
            "keyword": [
                "computational chemistry",
                "global warming potentials",
                "radiative efficiency",
                "IR frequencies"
            ],
            "contactPoint": {
                "fn": "Leon Betowski",
                "hasEmail": "mailto:betowski.don@epa.gov"
            },
            "distribution": [
                {
                    "title": "Supporting Information_EST_3_31_16.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/11/Supporting%20Information_EST_3_31_16.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2015-12-08",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Lipid correction for carbon stable isotope analysis of fish tissue",
            "description": "Fish chemistry data (d13C, d15N, C:N, lipid content) published in Rapid Commun. Mass Spectrom. 2015, 29, 2069\u20132077 DOI: 10.1002/rcm.7367. \n\nThis dataset is associated with the following publication:\nHoffman , J., M. Sierszen , and A. Cotter. Fish tissue lipid-C:N relationships for correcting \u00e413C values and estimating lipid content in aquatic food web studies.   Rapid Communications in Mass Spectrometry. Wiley InterScience, Silver Spring, MD, USA, 29(21): 2069\u20132077, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-280j-22",
            "keyword": [
                "food web",
                "stable isotope analsis",
                "Large Lakes assessment"
            ],
            "contactPoint": {
                "fn": "Joel Hoffman",
                "hasEmail": "mailto:hoffman.joel@epa.gov"
            },
            "distribution": [
                {
                    "title": "HoffmanJoel_A_280j_Dataset_20160401.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/22/HoffmanJoel_A_280j_Dataset_20160401.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2011-06-28",
            "references": [
                "https://doi.org/10.1002/rcm.7367"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Brown, C.A., D. Sharp, and T. Mochon Collura.  2016.  Effect of Climate Change on Water Temperature and Attainment of Water Temperature Criteria in the Yaquina Estuary, Oregon (USA).   Estuarine, Coastal and Shelf Science.  169:136-146.",
            "description": "This dataset contains the research described in the following publication:\nBrown, C.A., D. Sharp, and T. Mochon Collura.  2016.  Effect of Climate Change on Water Temperature and Attainment of Water Temperature Criteria in the Yaquina Estuary, Oregon (USA).   Estuarine, Coastal and Shelf Science.  169:136-146, doi: 10.1016/j.ecss.2015.11.006. \n\nThis dataset is associated with the following publication:\nBrown , C., D. Sharp, and T. MochonCollura. Effect of Climate Change on Water Temperature and Attainment of Water Temperature Criteria in the Yaquina Estuary, Oregon (USA).   ESTUARINE, COASTAL AND SHELF SCIENCE. Elsevier Science Ltd, New York, NY, USA, 169: 136-146, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-x6bc-37",
            "keyword": [
                "Yaquina Estuary",
                "Oregon",
                "climate change",
                "estuary",
                "temperature"
            ],
            "contactPoint": {
                "fn": "Cheryl Brown",
                "hasEmail": "mailto:brown.cheryl@epa.gov"
            },
            "distribution": [
                {
                    "title": "Brown et al Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/37/Brown%20et%20al%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-04-28",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Effects of Cold Temperature and Ethanol Content on VOC Emissions from Light-Duty Gasoline Vehicles",
            "description": "Supporting information Table S6 provides emission rates in g/km of volatile organic compounds measured from gasoline vehicle exhaust during chassis dynamometer testing. Vehicles operated on ethanol blended fuels, E0, E10 and E85. Test temperatures were -7 and 24 degrees C. Data are average of replicate tests and listed by test condition and driving phase. \n\nThis dataset is associated with the following publication:\nGeorge , I., M. Hays , R. Snow , J. Faircloth , B. George , T. Long , and R. Baldauf. Cold temperature and biodiesel fuel effects on speciated VOC emissions from diesel trucks.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 48(24): 14782-14789, (2014).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-w0wg-44",
            "keyword": [
                "biofuels",
                "dynamometer",
                "air toxics",
                "vehicle emissions"
            ],
            "contactPoint": {
                "fn": "Ingrid George",
                "hasEmail": "mailto:george.ingrid@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://pubs.acs.org/doi/suppl/10.1021/acs.est.5b04102",
                    "accessURL": "https://pubs.acs.org/doi/suppl/10.1021/acs.est.5b04102"
                }
            ],
            "modified": "2015-09-30",
            "references": [
                "https://doi.org/10.1021/es502949a"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/44/documents/Data%20Dictionary%20for%20A-w0wg.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for generation of all Tables and Figures for CTEP publication in 2015 pertaining to large-scale diesel gensets tested",
            "description": "particulate and gaseous emissions and particle optical properties for emissions from large-scale diesel gensets with and without aftermarket PM controls. \n\nThis dataset is associated with the following publication:\nYelverton , T., A. Holder , and J. Pavlovic. Emissions Removal Efficiency from Diesel Gensets Using Aftermarket PM Controls.   CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY. Springer-Verlag, New York, NY, USA, 17(7): 1861-1871, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-gxdf-56",
            "keyword": [
                "EC",
                "BC",
                "PM mass",
                "particle size distribution",
                "diesel emissions",
                "diesel genset",
                "emissions factors",
                "PM control"
            ],
            "contactPoint": {
                "fn": "Tiffany Yelverton",
                "hasEmail": "mailto:yelverton.tiffany@epa.gov"
            },
            "distribution": [
                {
                    "title": "SH-CTEP2015 data tables with data dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/56/SH-CTEP2015%20data%20tables%20with%20data%20dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2013-09-05",
            "references": [
                "https://doi.org/10.1007/s10098-015-0900-6"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for generation of all Tables and Figures for AIMS-ES publication in 2016 pertaining to dry sorbent injection of trona for acid gas control",
            "description": "emissions data and removal efficiencies for coal combustion utilizing PM control devices and dry sorbent injection of trona specifically for acid gas control. \n\nThis dataset is associated with the following publication:\nYelverton , T., D. Nash , E. Brown , C. Singer, J. Ryan , and P. Kariher. Dry sorbent injection of trona to control acid gases from a pilot-scale coal-fired combustion facility.   AIMS Environmental Science. AIMS Press, Springfield, MO, USA, 3(1): 45-57, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-x0kw-57",
            "keyword": [
                "removal efficiency",
                "ESP",
                "baghouse/fabric filter",
                "coal combustion",
                "acid gases",
                "dry sorbent injection (DSI)",
                "trona",
                "MATS",
                "emissions reduction"
            ],
            "contactPoint": {
                "fn": "Tiffany Yelverton",
                "hasEmail": "mailto:yelverton.tiffany@epa.gov"
            },
            "distribution": [
                {
                    "title": "SH-AIMS ES 2016 data tables with data dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/57/SH-AIMS%20ES%202016%20data%20tables%20with%20data%20dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-08-18",
            "references": [
                "https://doi.org/10.3934/environsci.2016.1.45"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Bob McEwen Treatment Plant Data (support ECM) and Water Quality Translation Data (support PDL)",
            "description": "Worksheet titled Data for ECM:  Data set used to estimate the error correction model to understand how turbidity and other variables affect drinking water treatment costs.  Worksheet titled Data for PDL:  Data set used to estimate the polynomial distributed lag model to understand how phosphorus load entering reservoir impacts turbidity at the drinking water treatment plant. \n\nThis dataset is associated with the following publication:\nHeberling , M., C. Nietch , H. Thurston , M. Elovitz , K. Birkenhauer, S. Panguluri, B. Ramakrishnan, E. Heiser, and T. Neyer. Comparing drinking water treatment costs to source water protection costs using time series analysis..   WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 51(11): 8741-8756, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-63xz-23",
            "keyword": [
                "water treatment costs",
                "source water protection",
                "time series analysis",
                "water quality trading",
                "drinking water treatment plant"
            ],
            "contactPoint": {
                "fn": "Matthew Heberling",
                "hasEmail": "mailto:heberling.matt@epa.gov"
            },
            "distribution": [
                {
                    "title": "A-63xz-DWTP data-Heberling-20160405.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/23/A-63xz-DWTP%20data-Heberling-20160405.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-07-01",
            "references": [
                "https://doi.org/10.1002/2014wr016422"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Moser_NTT_52:2015",
            "description": "data supporting manuscript figures. \n\nThis dataset is associated with the following publication:\nMoser , V.C., P. Phillips , J. Hedge , and K. Mcdaniel. Neurotoxicological and thyroid evaluations of rats developmentally exposed to tris(1,3-dichloro-2-propyl)phosphate (TDICPP) and tris(2-chloro-2-ethyl)phosphate(TCEP).   NEUROTOXICOLOGY AND TERATOLOGY. Elsevier Science Ltd, New York, NY, USA, 52: 236-247, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-7h4b-20",
            "keyword": [
                "flame retardants",
                "TDCPP",
                "TDCIPP",
                "TCEP",
                "developmental neurotoxicity",
                "alternative models"
            ],
            "contactPoint": {
                "fn": "Virginia Moser",
                "hasEmail": "mailto:moser.ginger@epa.gov"
            },
            "distribution": [
                {
                    "title": "Moser_A-7h4b_SDMP_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/20/Moser_A-7h4b_SDMP_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-03-30",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Integrated dataset of impact of dissolved organic matter on particle behavior and phototoxicity of titanium dioxide nanoparticles",
            "description": "This dataset is generated to both qualitatively and quantitatively examine the interactions between nano-TiO2 and natural organic matter (NOM). This integrated dataset assemble all data generated in this project through a series of experiments. \n\nThis dataset is associated with the following publication:\nLi , S., H. Ma, L. Wallis, M. Etterson , B. Riley , D. Hoff , and S. Diamond. Impact of natural organic matter on particle behavior and phototoxicity of titanium dioxide nanoparticles.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 542: 324-333, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-41nw-24",
            "keyword": [
                "Nano-TiO2",
                "Dissolved Organic Matter",
                "Quenching",
                "Aquatic Organism",
                "Linear Model",
                "Power Analysis"
            ],
            "contactPoint": {
                "fn": "Shibin Li",
                "hasEmail": "mailto:li.shibin@epa.gov"
            },
            "distribution": [
                {
                    "title": "DATA.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/24/DATA.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-01-08",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2015.09.141",
                "https://pasteur.epa.gov/uploads/24/documents/Abbreviation.docx"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A noninvasive method to study regulation of extracellular fluid volume in rats using nuclear magnetic resonance",
            "description": "NMR fluid measurements of commonly used rat strains when subjected to SQ normotonic or hypertonic salines, as well as physiologic comparisons to sedentary and exercised subjects. \n\nThis dataset is associated with the following publication:\nGordon , C., P. Phillips , and A. Johnstone. A Noninvasive Method to Study Regulation of Extracellular Fluid Volume in Rats Using Nuclear Magnetic Resonance.   American Journal of Physiology- Renal Physiology. American Physiological Society, Bethesda, MD, USA, 310(5): 426-31, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-5x6g-58",
            "keyword": [
                "Fluid homeostasis",
                "rodent",
                "nonivasive",
                "unanesthetized",
                "dehydration"
            ],
            "contactPoint": {
                "fn": "Christopher Gordon",
                "hasEmail": "mailto:gordon.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "SHC 2_63 Fluid NMR A5x6g_Data for Figures .xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/58/SHC%202_63%20Fluid%20NMR%20A5x6g_Data%20for%20Figures%20.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-12-07",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Caloric restriction in lean and obese strains of laboratory rat: effects on body composition, metabolism, growth and overall health",
            "description": "Data related to obese and lean strains of rat commonly used in the laboratory that are calorically restricted and its effects on physiologic parameters (Body Composition and metabolism). \n\nThis dataset is associated with the following publication:\nAydin, C., K. Jarema , P. Phillips , and C. Gordon. Caloric Restriction in Lean and Obese Strains of Laboratory Rat: Effects on Body Composition, Metabolism, Growth, and Overall Health.   Experimental Physiology Journal. Wiley-Blackwell, Hoboken, NJ, USA, 100(1): 1280-97, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-kd5g-34",
            "keyword": [
                "Caloric restriction",
                "obesity",
                "Body composition",
                "Metabolism"
            ],
            "contactPoint": {
                "fn": "Christopher Gordon",
                "hasEmail": "mailto:gordon.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science Hub - Caloric Restriction (E317).zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/34/Science%20Hub%20-%20Caloric%20Restriction%20%28E317%29.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-04-27",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Effect of high-fructose and high-fat diets on pulmonary sensitivity, motor activity, and body composition of brown Norway rats exposed to ozone",
            "description": "pulmonary parameters, BALF biomarkers, body composition, motor activity data collected from rats exposed to ozone after high fructose or high fat diets. \n\nThis dataset is associated with the following publication:\nGordon , C., P. Phillips , A. Johnstone , T. Beasley , A. Ledbetter , M. Schladweiler , S. Snow, and U. Kodavanti. Effect of High Fructose and High Fat Diets on Pulmonary Sensitivity, Motor Activity, and Body Composition of Brown Norway Rats Exposed to Ozone.   INHALATION TOXICOLOGY. Taylor & Francis, Inc., Philadelphia, PA, USA, 28(5): 203-15, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-nk9s-71",
            "keyword": [
                "air pollution",
                "BALF biomarkers",
                "food conusumption",
                "Metabolism",
                "obesity",
                "penH"
            ],
            "contactPoint": {
                "fn": "Christopher Gordon",
                "hasEmail": "mailto:gordon.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "GordonChristopher_SHC 2_63 Diet and Ozone in Brown Norways.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/71/GordonChristopher_SHC%202_63%20Diet%20and%20Ozone%20in%20Brown%20Norways.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-12-14",
            "references": [
                "https://doi.org/10.3109/08958378.2015.1134730"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Acute and subchronic toxicity of inhaled toluene in male Long Evans rats: oxidative stress markers in brain",
            "description": "Research interested in oxidative stress markers following exposure to VOCs. \n\nThis dataset is associated with the following publication:\nKodavanti , P., J. Royland , D.A. Moore-Smith, J. Beas, J. Richards , T. Beasley , P. Evansky , and P.J. Bushnell. Acute and Subchronic Toxicity of Inhaled Toluene in Male Long-Evans Rats: Oxidative Stress Markers in Brain.   NEUROTOXICOLOGY. Elsevier B.V., Amsterdam,  NETHERLANDS, 51: 10-19, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-x96m-82",
            "keyword": [
                "toluene",
                "oxidative stress",
                "solvents",
                "antioxidants",
                "protein carbonyls",
                "aconiatase",
                "neurotoxicity"
            ],
            "contactPoint": {
                "fn": "Prasada Kodavanti",
                "hasEmail": "mailto:kodavanti.prasada@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science Hub-toluene-AcuteSubchro-calculated data.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/82/Science%20Hub-toluene-AcuteSubchro-calculated%20data.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2015-05-27",
            "references": [
                "https://doi.org/10.1016/j.neuro.2015.09.001"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data supporting Boyes et al., Neurotoxicology 53, 257-270, 2016 ",
            "description": "Visual evoked potential data from rats exposed to toluene\nElectroretinogram data from rats exposed to toluene\nCounts of rod and m-cone photoreceptor cells in retinas of rats exposed to toluene. \n\nThis dataset is associated with the following publication:\nBoyes , W., M. Bercegeay, L. Degn , T. Beasley , P. Evansky , J.C. Mwanza, A. Geller , C. Pinckney, M.T. Nork, and P.J. Bushnell. Toluene Inhalation Exposure for 13 Weeks Causes Persistent Changes in Electroretinograms of Long-Evans Rats.   NEUROTOXICOLOGY. Elsevier B.V., Amsterdam,  NETHERLANDS, 53: 257-270, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-2549-92",
            "keyword": [
                "visual evoked potentials",
                "electroretinograms",
                "toluene",
                "rod and m-cone photoreceptors",
                "organic solvents",
                "hydrocarbon vapors",
                "neurotoxicity",
                "visual impairment",
                "retina",
                "hazardous air pollutants",
                "volatile organic compounds"
            ],
            "contactPoint": {
                "fn": "William Boyes",
                "hasEmail": "mailto:boyes.william@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data support files for ORD-015081.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/92/Data%20support%20files%20for%20ORD-015081.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-06-01",
            "references": [
                "https://doi.org/10.1016/j.neuro.2016.02.008"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data and Summaries for Catalytic Destruction of a Surrogate Organic Hazardous Air Pollutant as a Potential Co-benefit for Coal-Fired Selective Catalytic Reduction Systems",
            "description": "Table 1 summarizes and explanis the Operating Conditions of the SCR Reactor used in the Benzene-Destruction.\nTable 2 summarizes and explains the Experimental Design and Test Results.\nTable 3 summarizes and explains the Estimates for Individual Effects and Cross Effects Obtained from the Linear Regression Models for Destruction of C6H6 and Reduction of NO.\n\nFig. 1 shows the Down-flow SCR reactor system in detail.\nFig. 2 shows the graphical summary of the Effect of the inlet C6H6 concentration to the SCR reactor on the destruction of C6H6.\nFig.3 shows the summary of Carbon mass balance for C6H6 destruction promoted by the V2O5-WO3/TiO2 catalyst. \n\nThis dataset is associated with the following publication:\nLee , C., Y. Zhao, S. Lu, and W.R. Stevens. Catalytic Destruction of a Surrogate Organic Hazardous Air Polutant as a Potential Co-benefit for Coal-fired Selective Catalyst Reduction Systems.   AMERICAN CHEMICAL SOCIETY. American Chemical Society, Washington, DC, USA, 30(3): 2240-2247, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-1rnb-94",
            "keyword": [
                "hazardous air pollutants (HAPs) selective catalytic reduction (SCR) resonance-enhanced multiphoton ionization time-of-flight mass spectrometer (REMPI-TOFMS) total hydrocarbon (THC) benzene (C6H6)",
                "selective catalytic reduction; organic hazardous air pollutants; co-benefit; benzene; coal combustion"
            ],
            "contactPoint": {
                "fn": "Chun Lee",
                "hasEmail": "mailto:lee.chun-wai@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/94/Data.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-01-11",
            "references": [
                "https://doi.org/10.1021/acs.energyfuels.5b02058"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Pulmonary sensitivity to ozone exposure in sedentary versus chronically trained, female rats",
            "description": "Pulmonary effects to ozone with rats that have chronically exercised or have been continuously sedentary.  Also includes body composition of both groups throughout experimentation. \n\nThis dataset is associated with the following publication:\nGordon , C., P. Phillips , T. Beasley , A. Ledbetter , A. Cenk, U. Kodavanti , and A. Johnstone. Pulmonary Sensitivity to Ozone Exposure in Sedentary Versus Chronically Trained, Female Rats.   INHALATION TOXICOLOGY. Informa Healthcare USA, New York, NY, USA,  293-302, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-prrp-60",
            "keyword": [
                "air pollution",
                "Body composition",
                "fat loss",
                "obesity"
            ],
            "contactPoint": {
                "fn": "Christopher Gordon",
                "hasEmail": "mailto:gordon.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "SHC 2_63_Ozone and exercise_Data for figures.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/60/SHC%202_63_Ozone%20and%20exercise_Data%20for%20figures.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-07-15",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "2000-2010 Annual State-Scale Service and Domain Scores for Forecasting Well-Being from Service-Based Decisions",
            "description": "2000-2010 Annual State-Scale Service and Domain scores used to support the approach for forecasting EPA's Human Well-Being Index. A modeling approach was developed based relationship function equations derived from select economic, social and ecosystem final goods and service scores and calculated human well-being index and related domain scores. These data are being used in a secondary capacity. The foundational data and scoring techniques were originally described in: a) U.S. EPA. 2012. Indicators and Methods for Constructing a U.S. Human Well-being Index (HWBI) for Ecosystem Services Research. Report. EPA/600/R-12/023. pp. 121; and b) U.S. EPA. 2014. Indicators and Methods for Evaluating Economic, Ecosystem and Social Services Provisioning. Report. EPA/600/R-14/184. pp. 174. Mode Smith, L. M., Harwell, L. C., Summers, J. K., Smith, H. M., Wade, C. M., Straub, K. R. and J.L. Case (2014). \n\nThis dataset is associated with the following publication:\nSummers , K., L. Harwell , and L. Smith. A Model For Change: An Approach for Forecasting Well-Being From Service-Based Decisions.   ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 69: 295-309, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-1jwv-28",
            "keyword": [
                "Service scores",
                "Domain scores",
                "HWBI",
                "Secondary data",
                "Human Well-Being Index",
                "Forecasting",
                "Relationship Functions",
                "Affective Forecasting",
                "Community Decision-Making"
            ],
            "contactPoint": {
                "fn": "James Summers",
                "hasEmail": "mailto:summers.kevin@epa.gov"
            },
            "distribution": [
                {
                    "title": "SummersJames_A-1jwv_DATA_20160421.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/28/SummersJames_A-1jwv_DATA_20160421.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2014-05-14",
            "references": [
                "https://doi.org/10.1016/j.ecolind.2016.04.033"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/28/documents/SH-Data-Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Economic and environmental evaluation of coal-and-biomass-to-liquids-and-electricity plants equipped with carbon capture and storage (data for figures and tables)",
            "description": "Data used in the manuscript's tables and figures. Most data represent the modeled optimal capacity of the coal-and-biomass-to-liquid fuels-and-electricity (CBTLE) with integrated carbon capture and sequestration (CCS) over a wide range of scenarios. \n\nThis dataset is associated with the following publication:\nAitken, M., D. Loughlin , R. Dodder , and W. Yelverton. Economic and environmental evaluation of coal-and-biomass-to-liquids-and-electricity plants equipped with carbon capture and storage.   CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY. Springer-Verlag, New York, NY, USA, 18(2): 573-581, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-9gj5-70",
            "keyword": [
                "Energy systems modeling",
                "MARKAL",
                "nested sensitivity analysis",
                "electricity generation",
                "coal",
                "emission projections",
                "scenario analysis",
                "air quality",
                "climate change"
            ],
            "contactPoint": {
                "fn": "Daniel Loughlin",
                "hasEmail": "mailto:loughlin.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "CBTLE_TableFigData_A-9gj5.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/70/CBTLE_TableFigData_A-9gj5.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-06-02",
            "references": [
                "http://link.springer.com/article/10.1007/s10098-015-1020-z/fulltext.html"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Suppression of antigen-specific antibody responses in mice exposed to perfluorooctanoic acid: Role of PPARa and T- and B-cell targeting",
            "description": "Dosing information, body weights during exposure and immune system endpoints. \n\nThis dataset is associated with the following publication:\nDeWitt, J., W. Williams , J. Creech, and R. Luebke. Suppression of antigen-specific antibody responses in mice exposed to perfluorooctanoic acid: Role of PPARalpha and T- and B-cell targeting.   JOURNAL OF IMMUNOTOXICOLOGY. Taylor & Francis, Inc., Philadelphia, PA, USA, 13(1): 38-45, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-z61s-75",
            "keyword": [
                "perfluorooctanoic acid",
                "peroxisome proliferator activated receptor alpha",
                "immunotoxicity"
            ],
            "contactPoint": {
                "fn": "Robert Luebke",
                "hasEmail": "mailto:luebke.robert@epa.gov"
            },
            "distribution": [
                {
                    "title": "PFOA-21 phenotype support data sciehub.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/75/PFOA-21%20phenotype%20support%20data%20sciehub.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "PFOA-17 data for scihub.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/75/PFOA-17%20data%20for%20scihub.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-05-23",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Age- and Brain Region-Specific Differences in Mitochondrial Bioenergetics in Brown Norway Rats  ",
            "description": "Differences in various mitochondrial bioenergetics parameters in different brain regions in different age groups. \n\nThis dataset is associated with the following publication:\nPandya, J.D., J. Royland , R.C. McPhail, P.G. Sullivan, and P. Kodavanti. Age-and Brain Region-Specific Differences in Mitochondrial Bioenergetics in Brown Norway Rats.   NEUROBIOLOGY OF AGING. Elsevier Science Ltd, New York, NY, USA, 42: 25-34, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-8671-108",
            "keyword": [
                "Aging",
                "Bioenergetics",
                "Enzyme activity",
                "Mitochondria",
                "Brain regions",
                "Rats",
                "Susceptibility"
            ],
            "contactPoint": {
                "fn": "Prasada Kodavanti",
                "hasEmail": "mailto:kodavanti.prasada@epa.gov"
            },
            "distribution": [
                {
                    "title": "Sciencehub-Brain-Enzyme-Seahorse data for Stats.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/108/Sciencehub-Brain-Enzyme-Seahorse%20data%20for%20Stats.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-23",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Simkin et al. 2016 PNAS data on herbaceous species richness and associated plot and covariate information",
            "description": "This dataset includes the geographic location (lat/lon) for 15,136 plots, as well as the herbaceous species richness, climate, soil pH, and other variables related to the plots. \n\nThis dataset is associated with the following publication:\nSimkin, S., C. Clark , W. Bowman, E. Allen, J. Belnap, and L. Pardo. Conditional vulnerability of plant diversity to atmospheric nitrogen deposition across the United States.   PNAS  (PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES). National Academy of Sciences, WASHINGTON, DC, USA, 113(15): 4086-4091, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-8czh-72",
            "keyword": [
                "nitrogen deposition",
                "biodiversity",
                "plant species richness",
                "soil pH",
                "climate",
                "critical loads"
            ],
            "contactPoint": {
                "fn": "Christopher Clark",
                "hasEmail": "mailto:clark.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "README.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/72/README.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Simkin_et_al_2016_data_from_PNAS_Div_and_N_dep.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/72/Simkin_et_al_2016_data_from_PNAS_Div_and_N_dep.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-03-31",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/72/documents/README.csv",
            "describedByType": "text/csv",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "LJFO00000000, LJFQ00000000, LJFT00000000, LJFU00000000, LJFX00000000, LJFY00000000",
            "description": "Draft genome sequences of six Mycobacterium immunogenum strains isolated from a chloraminated drinking water distribution system simulator subjected to changes in operational parameters. \n\nThis dataset is associated with the following publication:\nGomez-Alvarez, V., and R. Revetta. Draft Genome Sequences of Six Mycobacterium immunogenum, Obtained from a Chloraminated Drinking Water Distribution System Simulator.   Genome Announcements. American Society for Microbiology, Washington, DC, USA, 4(1): e01538-15, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-2282-100",
            "keyword": [
                "drinking water",
                "genome",
                "chloramine",
                "sequences",
                "Mycobacterium"
            ],
            "contactPoint": {
                "fn": "Randy Revetta",
                "hasEmail": "mailto:revetta.randy@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.ncbi.nlm.nih.gov/genbank/",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/genbank/"
                }
            ],
            "modified": "2016-03-01",
            "references": [
                "https://doi.org/10.1128/genomea.01538-15"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CHARACTERIZING EMISSIONS FROM OPEN BURNING OF MILITARY FOOD WASTE AND PACKAGING FROM FORWARD OPERATING BASES",
            "description": "Data for tables and figures. \n\nThis dataset is associated with the following publication:\nDominguez, T., J. Aurell, B. Gullett, R. Eninger, and D. Yamamoto. Characterizing emissions from open burning of military food\r\nwaste and ration packaging compositions.   Journal of Material Cycles and Waste Management. Springer Japan KK, Tokyo,  JAPAN, 20(2): 903-913, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390097",
            "keyword": [
                "military waste",
                "emissions",
                "packaging",
                "open burning",
                "MREs"
            ],
            "contactPoint": {
                "fn": "Brian Gullett",
                "hasEmail": "mailto:gullett.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data Table Dominguez MRE & FBD - Tables & Figures Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390097/Data%20Table%20Dominguez%20MRE%20%26%20FBD%20-%20Tables%20%26%20Figures%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-02",
            "references": [
                "https://doi.org/10.1007/s10163-017-0652-y"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset of NRDA emission data",
            "description": "Emissions data from open air oil burns. \n\nThis dataset is associated with the following publication:\nGullett, B., J. Aurell, A. Holder, B. Mitchell, D. Greenwell, M. Hays, R. Conmy, D. Tabor, W. Preston, I. George, J. Abrahamson, R. Vander Wal, and E. Holder. Characterization of Emissions and Residues from Simulations of the Deepwater Horizon Surface Oil Burns.   MARINE POLLUTION BULLETIN. Elsevier Science Ltd, New York, NY, USA, 117: 392-405, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-v9ss-131",
            "keyword": [
                "oil spill",
                "in situ burns",
                "emissions",
                "Deepwater Horizon"
            ],
            "contactPoint": {
                "fn": "Brian Gullett",
                "hasEmail": "mailto:gullett.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "Copy of Data Table Science Hub 06-07-2016 JA.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/131/Copy%20of%20Data%20Table%20Science%20Hub%2006-07-2016%20JA.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-08",
            "references": [
                "https://doi.org/10.1016/j.marpolbul.2017.01.083"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Total and methyl mercury, moisture, and porosity in Lake Michigan surficial sediment",
            "description": "Total and methyl mercury, moisture content (%), and porosity were measured in Lake Michigan sediment by the U.S. Environmental Protection Agency/Office of Research and Development/National Health and Environmental Effects Research Laboratory/Mid-Continent Ecology Division/Large Lakes Research Station, Grosse Ile, MI. Both core and Ponar grab samples were collected. The samples were collected from 1994 through 1996. These mercury data were used in the LM2-Mercury model. \n\nThis dataset is associated with the following publication:\nZhang, X., K. Rygwelski , M. Rowe, R. Rossmann, and R. Kreis. Global and regional contributions to total mercury concentrations in Lake Michigan water.   JOURNAL OF GREAT LAKES RESEARCH. International Association for Great Lakes Research, Ann Arbor, MI, USA, 42(1): 62-69, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-kps6-25",
            "keyword": [
                "total mercury",
                "methyl mercury",
                "sediments",
                "porosity",
                "percent moisture",
                "Lake Michigan"
            ],
            "contactPoint": {
                "fn": "Kenneth Rygwelski",
                "hasEmail": "mailto:rygwelski.kenneth@epa.gov"
            },
            "distribution": [
                {
                    "title": "Hg Lake MI surficial sediments.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/25/Hg%20Lake%20MI%20surficial%20sediments.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2009-11-05",
            "references": [
                "https://doi.org/10.1016/j.jglr.2015.10.010"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "St. Louis River Estuary 2011 - 2013 Faucet snail location data",
            "description": "The dataset consists of GPS coordinates for benthic invertebrate collections made in the St. Louis River Estuary in 2011 through 2013, and information on whether and how many faucet snail individuals were found. \n\nThis dataset is associated with the following publication:\nTrebitz , A., G. Shepard, V. Brady, and K. Schmude. The non-native faucet snail (Bithynia tentaculata) makes the leap to Lake Superior.   JOURNAL OF GREAT LAKES RESEARCH. International Association for Great Lakes Research, Ann Arbor, MI, USA, 41(4): 1197-1200, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-5hqh-27",
            "keyword": [
                "faucet snail",
                "Bithynia tentaculata",
                "St. Louis River estuary",
                "Great Lakes",
                "Aquatic invasive species",
                "sampling design",
                "DNA technology"
            ],
            "contactPoint": {
                "fn": "Anett Trebitz",
                "hasEmail": "mailto:trebitz.anett@epa.gov"
            },
            "distribution": [
                {
                    "title": "FaucetSnailJGLR2015pub_ScienceHub_DataMetadata.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/27/FaucetSnailJGLR2015pub_ScienceHub_DataMetadata.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-04-22",
            "references": [
                "https://doi.org/10.1016/j.jglr.2015.09.013"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Lead mineral types identified in control and treated Garden and City Lot soil using X-ray absorption fine structure spectroscopy",
            "description": "Table listing the location, amendment type, distribution (percentage) of lead phases identified, and fitting error (R-factor). BM=bone meal, FB=fish bone, DAP=diammonium phosphate, MAP=monoammonium phosphate, TSP=triple super phosphate, PL=poultry litter. \n\nThis dataset is associated with the following publication:\nObrycki, J., N. Basta, K. Scheckel , B. Stevens, and K. Minca. Phosphorus Amendment Efficacy for In Situ Remediation of Soil Lead Depends on the Bioaccessible Method.  Elizabeth Guertal, David Myroid, and C. Wayne Smith  JOURNAL OF ENVIRONMENTAL QUALITY. American Society of Agronomy, MADISON, WI, USA, 45(1): 37-44, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-15dw-47",
            "keyword": [
                "lead speciation",
                "phosphate amendments",
                "in vitro bioaccessibility",
                "lead contaminated soil"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Table5.JEQ2016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/47/Table5.JEQ2016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-11-03",
            "references": [
                "https://doi.org/10.2134/jeq2015.05.0244"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Linear combination fitting data",
            "description": "The dataset shows the weighted percentage of arsenic speciation for untreated and treated soil samples with amendments designed to immobilize arsenic in soils. \n\nThis dataset is associated with the following publication:\nMele, E., E. Donner, A. Juhasz, G. Brunetti, E. Smith, A. Betts , P. Castaldi, S. Deiana, K. Scheckel , and E. Lombi. In situ fixation of metal(loid)s in contaminated soils: a comparison of conventional, by product and engineered soil amendments.  David L. Sedlak  ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 49: 13501-13509, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-r4z2-76",
            "keyword": [
                "synchrotron speciation",
                "arsenic",
                "soil amendments",
                "lead",
                "soil",
                "immobilization",
                "waste reuse"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Table 3 Mele etal.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/76/Table%203%20Mele%20etal.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2015-10-15",
            "references": [
                "https://doi.org/10.1021/acs.est.5b01356"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Synchrotron speciation data for zero-valent iron nanoparticles: Linear combination fitting table(#6) and figure(#9), and extended x-ray absorption fine structure figure(#10) and table(#7)",
            "description": "This data set encompasses a complete analysis of synchrotron speciation data for 5 iron nanoparticle samples (P1, P2, P3, S1, S2, and metallic iron) to include linear combination fitting results (Table 6 and Figure 9) and ab-initio extended x-ray absorption fine structure spectroscopy fitting (Figure 10 and Table 7).\nTable 6: Linear combination fitting of the XAS data for the 5 commercial nZVI/ZVI products tested. Species proportions are presented as percentages. Goodness of fit is indicated by the chi^2 value.\nFigure 9: Normalised Fe K-edge k3-weighted EXAFS of the 5 commercial nZVI/ZVI\nproducts tested. Dotted lines show the best 4-component linear combination fit of\nreference spectra.\nFigure 10: Fourier transformed radial distribution functions (RDFs) of the five samples\nand an iron metal foil. The black lines in Fig. 10 represent the sample data and the red\ndotted curves represent the non-linear fitting results of the EXAFS data.\nTable 7: Coordination parameters of Fe in the samples. \n\nThis dataset is associated with the following publication:\nChekli, L., B. Bayatsarmadi, R. Sekine, B. Sarkar, A. Maoz Shen, K. Scheckel , W. Skinner, R. Naidu, H. Shon, E. Lombi, and E. Donner. Analytical Characterisation of Nanoscale Zero-Valent Iron: A Methodological Review.  Richard P. Baldwin  ANALYTICA CHIMICA ACTA. Elsevier Science Ltd, New York, NY, USA, 903: 13-35, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-z8x1-50",
            "keyword": [
                "synchrotron speciation",
                "zero-valent iron nanoparticles",
                "characterization techniques",
                "nanoparticle remediation",
                "surface chemistry",
                "particle size"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "ChekliData.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/50/ChekliData.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2015-09-01",
            "references": [
                "https://doi.org/10.1016/j.aca.2015.10.040"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Ecohydrology_GoldenHeaher_Data_052316",
            "description": "Table of data used for statistical analyses. \n\nThis dataset is associated with the following publication:\nGolden , H., H. Sander, C. Lane , C. Zhao, K. Price, E. D'Amico, and J. Christensen. Relative effects of geographically isolated wetlands on streamflow: a watershed-scale analysis.   ECOHYDROLOGY. Wiley Interscience, Malden, MA, USA, 9(1): 21-38, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-jdg2-77",
            "keyword": [
                "streamflow",
                "wetlands",
                "Watershed",
                "model"
            ],
            "contactPoint": {
                "fn": "Heather Golden",
                "hasEmail": "mailto:golden.heather@epa.gov"
            },
            "distribution": [
                {
                    "title": "GoldenHeather_A-jdg2_SDMP_Data_20160523.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/77/GoldenHeather_A-jdg2_SDMP_Data_20160523.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-05-01",
            "references": [
                "https://doi.org/10.1002/eco.1608"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Evaluation of near surface ozone and particulate matter in air quality simulations driven by dynamically downscaled historical meteorological fields",
            "description": "This dataset supports the modeling study of Seltzer et al. (2016) published in Atmospheric Environment. In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields without correcting toward higher resolution observations. The Weather Research and Forecasting model and the Community Multiscale Air Quality model are used to simulate regional climate and air quality over the contiguous United States for 2000-2010. The air quality simulations for that historical period are then compared to observations from four national networks. Comparisons are drawn between defined performance metrics and other published modeling results for predicted ozone, fine particulate matter, and speciated fine particulate matter. The results indicate that the historical air quality simulations driven by dynamically downscaled meteorology are typically within defined modeling performance benchmarks and are consistent with results from other published modeling studies using finer-resolution meteorology. This indicates that the regional climate and air quality modeling framework utilized here does not introduce substantial bias, which provides confidence in the method\u2019s use for future air quality projections. \n\nThis dataset is associated with the following publication:\nSeltzer, K., C. Nolte, T. Spero, W. Appel, and J. Xing. Evaluation of near surface ozone and particulate matter in air quality simulations driven by dynamically downscaled historical meteorological fields.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 138: 42-54, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-37pz-84",
            "keyword": [
                "model evaluation",
                "air quality",
                "climate change",
                "regional climate modeling",
                "dynamical downscaling",
                "CMAQ"
            ],
            "contactPoint": {
                "fn": "Christopher Nolte",
                "hasEmail": "mailto:nolte.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Seltzer_2016.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/84/Seltzer_2016.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-05-26",
            "references": [
                "http://www.sciencedirect.com/science/journal/aip/13522310"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Kelly et al. (2016): Simulating the phase partitioning of NH3, HNO3, and HCl with size-resolved particles over northern Colorado in winter",
            "description": "In this study, modeled gas- and aerosol phase ammonia, nitric acid, and hydrogen chloride are compared to measurements taken during a field campaign conducted in northern Colorado in February and March 2011.  We compare the modeled and observed gas-particle partitioning, and assess potential reasons for discrepancies between the model and measurements.  This data set contains scripts and data used for each figure in the associated manuscript.  Figures are generated using the R project statistical programming language. Data files are in either comma-separated value (CSV) format or netCDF, a standard self-describing binary data format commonly used in the earth and atmospheric sciences. \n\nThis dataset is associated with the following publication:\nKelly , J., K. Baker , C. Nolte, S. Napelenok , W.C. Keene, and A.A.P. Pszenny. Simulating the phase partitioning of NH3, HNO3, and HCl with size-resolved particles over northern Colorado in winter.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 131: 67-77, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-r7t9-152",
            "keyword": [
                "aerosol size distributions",
                "source apportionment",
                "NACHTT",
                "air quality",
                "CMAQ",
                "WRF",
                "model evaluation"
            ],
            "contactPoint": {
                "fn": "Christopher Nolte",
                "hasEmail": "mailto:nolte.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Kelly_et_al_2016.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/152/Kelly_et_al_2016.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-08-02",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2016.01.049"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Outdoor air quality impacts data for USGCRP Climate and Health Assessment",
            "description": "Gridded values of daily maximum temperature and ozone levels simulated over the continental U.S. using year-2000 and year-2030 climatic conditions as represented by two different global climate models and greenhouse gas forcing scenarios. \n\nThis dataset is associated with the following publication:\nFann , N., C. Nolte , P. Dolwick , T. Spero , A. CurryBrown , S. Phillips , and S. Anenberg. The Geographic Distribution and Economic Value of Climate Change-Related Ozone Health Impacts in the United States in 2030.   JOURNAL OF AIR AND WASTE MANAGEMENT. Air & Waste Management Association, Pittsburgh, PA, USA, 65(5): 570-580, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-37pz-160",
            "keyword": [
                "USGCRP",
                "air quality",
                "climate change",
                "regional climate modeling",
                "dynamical downscaling",
                "CMAQ"
            ],
            "contactPoint": {
                "fn": "Christopher Nolte",
                "hasEmail": "mailto:nolte.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "USGCRP_CHA_CH3.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/160/USGCRP_CHA_CH3.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-08-04",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Figures and Tables in Journal Article \"Assessment of the Effects of Horizontal Grid Resolution on Long-Term Air Quality Trends using Coupled WRF-CMAQ Simulations\", doi:10.1016/j.atmosenv.2016.02.036",
            "description": "The dataset represents the data depicted in the Figures and Tables of a Journal Manuscript with the following abstract: \"The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. WRF-CMAQ simulations over the continental United State are performed over the 2001 to 2010 time period at two different horizontal resolutions of 12 and 36 km. Both simulations used the same emission inventory and model configurations. Model results are compared both in space and time to assess the potential weaknesses and strengths of using coarse resolution in long-term air quality applications. The results show that the 36 km and 12 km simulations are comparable in terms of trends analysis for both pollutant concentrations and radiation variables. The advantage of using the coarser 36 km resolution is a significant reduction of computational cost, time and storage requirement which are key considerations when performing multiple years of simulations for trend analysis. However, if such simulations are to be used for local air quality analysis, finer horizontal resolution may be beneficial since it can provide information on local gradients. In particular, divergences between the two simulations are noticeable in urban, complex terrain and coastal regions.\". \n\nThis dataset is associated with the following publication:\nGan , M., C. Hogrefe , R. Mathur , J. Pleim , J. Xing , D. Wong , R. Gilliam , G. Pouliot , and C. Wei. Assessment of the effects of horizontal grid resolution on long-term air quality trends using coupled WRF-CMAQ simulations.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 132: 207-216, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-f4r3-169",
            "keyword": [
                "horizontal grid resolution",
                "air quality application",
                "model evaluation",
                "WRF/CMAQ",
                "computational cost"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "DataTables2And3.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/169/DataTables2And3.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Data_Figure1Figure2Figure7.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/169/Data_Figure1Figure2Figure7.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Data_Figures3Through6.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/169/Data_Figures3Through6.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-02-08",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2016.02.036"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/169/documents/DataDictionary_HeadersFigures3Through6.zip",
            "describedByType": "application/zip",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Geographically isolated wetlands and watershed hydrology: A modified",
            "description": "Data for \"An improved representation of geographically isolated wetlands in a watershed-scale hydrologic model\". \n\nThis dataset is associated with the following publication:\nEvenson, G., H. Golden, C. Lane, and E. D'Amico. An improved representation of geographically isolated wetlands in a watershed-scale hydrologic model.   Hydrological Processes. John Wiley & Sons, Ltd., Indianapolis, IN, USA,  online, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-tdzn-190",
            "keyword": [
                "Watershed",
                "wetlands",
                "geographically isolated wetlands;",
                "modeling",
                "hydrology",
                "downstream effects"
            ],
            "contactPoint": {
                "fn": "Heather Golden",
                "hasEmail": "mailto:golden.heather@epa.gov"
            },
            "distribution": [
                {
                    "title": "Evensonetal2016HPScienceHubSubmission.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/190/Evensonetal2016HPScienceHubSubmission.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-30",
            "references": [
                "https://doi.org/10.1002/hyp.10930"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Modeling the current and future roles of particulate organic nitrates in the southeastern US",
            "description": "Links point to the NOAA data archive of observational data and the supplement of the article which this data supports. No model data was uploaded due to its size. All updates to CMAQ used in this work are available in the public release of CMAQv5.1 (available through github or the CMAS Center). \n\nThis dataset is associated with the following publication:\nPye , H., D. Luecken , L. Xu, C.M. Boyd, N.L. Ng, K. Baker , B.R. Ayres, J. Bash , K. Baumann, W.P.L. Carter, E. Edgerton, J.L. Fry, B. Hutzell , D. Schwede , and P.B. Shepson. Modeling the current and future role of particulate organic nitrates in the southeastern United States.   Environmental Science & Technology Letters. American Chemical Society, Washington, DC, USA, 49(24): 14195-14203, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-12jn-194",
            "keyword": [
                "SOA",
                "SOAS",
                "Aerosol",
                "organic nitrate",
                "monoterpenes",
                "NOx",
                "nitrate",
                "Secondary Organic Aerosol"
            ],
            "contactPoint": {
                "fn": "Havala Pye",
                "hasEmail": "mailto:pye.havala@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://pubs.acs.org/doi/suppl/10.1021/acs.est.5b03738",
                    "accessURL": "https://pubs.acs.org/doi/suppl/10.1021/acs.est.5b03738"
                },
                {
                    "title": "https://www.esrl.noaa.gov/csd/groups/csd7/measurements/2013senex/",
                    "accessURL": "https://www.esrl.noaa.gov/csd/groups/csd7/measurements/2013senex/"
                }
            ],
            "modified": "2015-07-02",
            "references": [
                "https://github.com/CMASCenter/CMAQ/"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CalNex Observational Data",
            "description": "Observations made during the 2010 CalNex measurement campaign. \n\nThis dataset is associated with the following publication:\nWoody , M., K. Baker , P. Hayes, J. Jimenez, B. Koo, and H. Pye. Understanding sources of organic aerosol during CalNex-2010 using the CMAQ-VBS.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 16: 4081-4100, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-dz0m-197",
            "keyword": [
                "CalNex",
                "CMAQ",
                "volatility basis set",
                "organic aerosols"
            ],
            "contactPoint": {
                "fn": "Matthew Woody",
                "hasEmail": "mailto:woody.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://esrl.noaa.gov/csd/groups/csd7/measurements/2010calnex/",
                    "accessURL": "https://esrl.noaa.gov/csd/groups/csd7/measurements/2010calnex/"
                }
            ],
            "modified": "2012-11-20",
            "references": [
                "https://doi.org/10.5194/acp-16-4081-2016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CMAQ Model Output",
            "description": "CMAQ and CMAQ-VBS model output. This dataset is not publicly accessible because: Files too large. It can be accessed through the following means: via EPA's NCC tape archive system (ASM) or by contacting the PI. Format: netCDF CMAQ model output. \n\nThis dataset is associated with the following publication:\nWoody , M., K. Baker , P. Hayes, J. Jimenez, B. Koo, and H. Pye. Understanding sources of organic aerosol during CalNex-2010 using the CMAQ-VBS.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 16: 4081-4100, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-dz0m-198",
            "keyword": [
                "CMAQ",
                "volatility basis set",
                "organic aerosols",
                "CalNex"
            ],
            "contactPoint": {
                "fn": "Matthew Woody",
                "hasEmail": "mailto:woody.matthew@epa.gov"
            },
            "distribution": [],
            "modified": "2015-09-14",
            "references": [
                "https://doi.org/10.5194/acp-16-4081-2016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CESM Lakes Supplement",
            "description": "This is a README file to indicate the locations of codes, data sets, and other supporting materials. \n\nThis dataset is associated with the following publication:\nSpero , T., C. Nolte , J.H. Bowden, M.S. Mallard, and J. Herwehe. The Impact of Incongruous Lake Temperatures on Regional Climate Extremes Downscaled from the CMIP5 Archive Using the WRF Model.   Journal of Climate. American Meteorological Society, Boston, MA, USA, 29(2): 839-853, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-31zg-205",
            "keyword": [
                "README",
                "regional climate modeling",
                "WRF",
                "CMIP5",
                "dynamical downscaling"
            ],
            "contactPoint": {
                "fn": "Tanya Spero",
                "hasEmail": "mailto:spero.tanya@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHub supplement.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/205/ScienceHub%20supplement.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2016-08-17",
            "references": [
                "https://doi.org/10.1175/jcli-d-15-0233.1"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Systemic Metabolic Derangement, Pulmonary Effects, and Insulin Insufficiency Following Subchronic Ozone Exposure in Rats",
            "description": "This data set includes individual animal data collected for various biological endpoints that are included in the manuscript.\nMiller DB, Snow SJ, Henriquez A, Schladweiler MC, Ledbetter AD, Richards JE, Andrews DL, Kodavanti UP. Systemic metabolic derangement, pulmonary effects, and insulin insufficiency following subchronic ozone exposure in rats. Toxicol Appl Pharmacol. 2016 Jun 28;306:47-57. \nThe primary author Desinia Miller, an UNC-EPA co-opp Student has since completed her PhD and is no longer in EPA database. \n\nThis dataset is associated with the following publication:\nMiller, D., S. Snow, A. Henriquez, M. Schladweiler, A. Ledbetter, J. Richards, D. Andrews, and U. Kodavanti. Systemic Metabolic Derangement, Pulmonary Effects, and Insulin Insufficiency following subchronic ozone exposure in rats.   TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 306: 47-57, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-xktb-116",
            "keyword": [
                "Metabolism Ozone Stress Response Insulin Resistance Pancreatic Beta Cells",
                "Ozone",
                "Stress Response",
                "Metabolism",
                "Insulin Resistance",
                "Pancreatic Beta Cells"
            ],
            "contactPoint": {
                "fn": "Urmila Kodavanti",
                "hasEmail": "mailto:kodavanti.urmila@epa.gov"
            },
            "distribution": [
                {
                    "title": "Miller et al., 2016 TAAP -Ozone subchronic manuscript.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/116/Miller%20et%20al.%2C%202016%20TAAP%20-Ozone%20subchronic%20manuscript.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-05-28",
            "references": [
                "https://doi.org/10.1016/j.taap.2016.06.027"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Large Drought-induced Variations in Oak Leaf Volatile Organic Compound Emissions during PINOT NOIR 2012",
            "description": "Leaf level oak isoprene emissions and co2/H2O exchange in the Ozarks, USA\n\nBAGeron.csv is the speciated biomass displayed in Figure 1.\n\nBiomass Dry Weights.xlsx is used to convert leaf area to dry leaf biomass and is used in Figure 2.\n\nDaly Ozarks leaf ISOP.txt and MOFLUX_Isoprene Summary_refined Tcurve data.xlsx are the leaf isoprene emission rate files shown in Figure 2.\n\nHarley Aug12_Chris.xls is the leaf isoprene emission rate file shown in Figure  3.\n\n\nDaly Ozarks leaf.txt is the BVOC emissions file used for Figure 7 and Table 4.\n\nDrought IS.txt is the review data given in Table 2.\n\nFig4 Aug10 2012 Harley.txt is shown in Figure 4.\n\nFig 5 Aug14 2012 Harley.txt is shown in Figure 5.\n\nDaly Ozarks Leaf.txt is used in Fig 7.\n\nDrought IS.txt is used in Fig 8. \n\nThis dataset is associated with the following publication:\nGeron , C., R. Daly , P. Harley, R. Rasmussen, R. Seco, A. Guenther, T. Karl, and L. Gu. Large Drought-Induced Variations in Oak Leaf Volatile Organic Compound Emissions during PINOT NOIR 2012.   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 146: 8-21, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-7sr2-91",
            "keyword": [
                "isoprene",
                "Monoterpene",
                "Quercus",
                "monoterpenes",
                "drought",
                "Ozarks",
                "biogenic emissions",
                "MEGAN"
            ],
            "contactPoint": {
                "fn": "Christopher Geron",
                "hasEmail": "mailto:geron.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "BAGeron.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/91/BAGeron.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Biomass Dry Weights.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/91/Biomass%20Dry%20Weights.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Daly Ozarks leaf ISOP.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/91/Daly%20Ozarks%20leaf%20ISOP.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "Daly Ozarks leaf.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/91/Daly%20Ozarks%20leaf.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "Drought IS.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/91/Drought%20IS.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "Fig4 Aug10 2012 Harley.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/91/Fig4%20Aug10%202012%20Harley.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "Fig 5 Aug14 2012 Harley.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/91/Fig%205%20Aug14%202012%20Harley.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "MOFLUX_Isoprene Summary_refined Tcurve data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/91/MOFLUX_Isoprene%20Summary_refined%20Tcurve%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Harley Aug12_Chris.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/91/Harley%20Aug12_Chris.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-06-01",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2015.11.086",
                "https://pasteur.epa.gov/uploads/91/documents/Geron%20et%20al%202016%20Chemosphere.pdf"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Xing_et_al_JGR2015",
            "description": "The data sets are outputs from the WRF-CMAQ modeling system. Typically these files contain a number of meteorological and atmospheric pollutant concentrations on a model grid which is either 2- or 3-dimensional and also in some instances vary with time. \n\nThis dataset is associated with the following publication:\nXing, J., R. Mathur , J. Pleim , C. Hogrefe , C. Gan, D. Wong , C. Wei, and J. Wang. Air pollution and climate response to aerosol direct radiative effects: A modeling study of decadal trends across the northern hemisphere.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(33): 12221-12236, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-pc8q-201",
            "keyword": [
                ": aerosol direct radiative effect",
                "WRF-CMAQ",
                "feedback",
                "trend",
                "AOD",
                "northern hemisphere",
                "aerosol direct radiatiative effects",
                "Hemispheric CMAQ"
            ],
            "contactPoint": {
                "fn": "Rohit Mathur",
                "hasEmail": "mailto:mathur.rohit@epa.gov"
            },
            "distribution": [
                {
                    "title": "Xing_JGR_data_document_updated.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/201/Xing_JGR_data_document_updated.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-08-17",
            "references": [
                "http://onlinelibrary.wiley.com/doi/10.1002/2015JD023933/full"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data summary of all endpoints measured",
            "description": "qPCR results for Vitellogenin. \n\nThis dataset is associated with the following publication:\nArmstrong, B., J. Lazorchak , K. Jensen , H. Haring , M.E. Smith, R. Flick , D. Bencic , and A. Biales. Reproductive effects in fathead minnows (Pimphales promelas) following a 21 d exposure to 17\u03b1-ethinylestradiol.   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 144(1): 366-373, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-crjq-215",
            "keyword": [
                "Ethinylestradiol",
                "Reproductive effects",
                "Fathead minnows",
                "Vitellogenin Gene and Protein"
            ],
            "contactPoint": {
                "fn": "James Lazorchak",
                "hasEmail": "mailto:lazorchak.jim@epa.gov"
            },
            "distribution": [
                {
                    "title": "9-05Expression Results.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/215/9-05Expression%20Results.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "9-05_EE2_032409.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/215/9-05_EE2_032409.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Copy of 9-05_EE2_032409.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/215/Copy%20of%209-05_EE2_032409.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "EE2 Chemtry results.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/215/EE2%20Chemtry%20results.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-22",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Tropospheric Emission Spectrometer (TES) Satellite Validations of Ammonia, Methanol, Formic Acid, and Carbon Monoxide over the Canadian Oil Sands ",
            "description": "The URLs link to the data archive of the Troposphere Emission Spectrometer (TES) retrievals. These include the transects included in the Canadian Tar Sands study. A brief description of TES is listed below. \n\nTES is a spectrometer that measures the infrared-light energy (radiance) emitted by Earth's surface and by gases and particles in Earth's atmosphere. Every substance warmer than absolute zero emits infrared radiation at certain signature wavelengths. Spectrometers measure this radiation as a means of identifying the substances.\n\nTES has very high spectral resolution, which gives it the ability to pinpoint the wavelengths at which the substances are emitting. This enables precise identification of the substances, and also provides information about their location in the atmosphere. Emission wavelengths can vary with temperature and pressure, so seeing the emissions with great precision enables scientists to infer the temperature and pressure of the chemicals from which they came. This, in turn, implies that the chemicals being observed are at a certain altitude where those temperatures and pressures apply. The ability to determine the altitude of the observed chemicals enables TES to distinguish radiation from the upper and lower atmosphere, and focus on the lower layer - the troposphere.\n\nSince it observes light in the infrared range of the electromagnetic spectrum, similar to night-vision goggles, TES can observe both day and night. Its spectral range overlaps that of HIRDLS, another of the instruments aboard the Aura satellite. So, in addition to its work in the troposphere, TES can supplement HIRDLS measurements of chemicals in the stratosphere that are common to both instruments, as well as help scientists measure additional constituents of the stratosphere. \n\nThis dataset is associated with the following publication:\nShephard, , M.W., C. McLinden, K.E. Cady-Pereira, M. Luo, S.G. Moussa, A. Leithead, J. Liggio, R.M. Staebler, A. Akingunola, P. Makar, P. Lehr, J. Zhang, D.K. Henze, D.B. Millet, J. Bash , L. Zhu, K.C. Wells, S.L. Capps, S. Chaliyakunnel, M. Gordon, K. Hayden, J.R. Brook, M. Wolde, and S. Li. Tropospheric Emission Spectrometer (TES) satellite observations of ammonia, methanol, formic acid, and carbon monoxide over the Canadian oil sands: validation and model evaluation.   Atmospheric Measurement Techniques. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 8: 5189-5211, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-9326-219",
            "keyword": [
                "NH3 Emissions",
                "Nitrogen Cycle",
                "Satellite Air Quality",
                "Air Quality Model",
                "Sensors"
            ],
            "contactPoint": {
                "fn": "Jesse Bash",
                "hasEmail": "mailto:bash.jesse@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://eosweb.larc.nasa.gov/project/tes/tes_table",
                    "accessURL": "https://eosweb.larc.nasa.gov/project/tes/tes_table"
                },
                {
                    "title": "https://asdc.larc.nasa.gov/project/TES?level=2",
                    "accessURL": "https://asdc.larc.nasa.gov/project/TES?level=2"
                }
            ],
            "modified": "2015-06-15",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Toxicokinetics of PFOS in rainbow trout",
            "description": "This ScienceHub entry was developed for the published paper:  Consoer et al., 2016, Toxicokinetics of perfluorooctane sulfonate in rainow trout (Oncorhynchus mykiss), Environ. Toxicol. Chem. 35:717-727.  Individual rainbow trout were exposed to PFOS by bolus injection (elimination studies) or by adding PFOS to incoming water (branchial uptake studies).  The trout were fitted with indwelling catheters and urinary cannulae to permit periodic collection of blood and urine.  Additional sampling was conducted to evaluate PFOS uptake from and elimination to respired water.  Data obtained from each fish was evaluated using a clearance-volume pharmacokinetic model.  Modeled kinetic parameters were then averaged to develop summary statistics which were used as a basis for interpreting modeled results and making comparisons to a previous study of rainbow trout exposed to perfluorooctanoate (PFOA; Consoer et al., 2014, Aquat. Toxicol. 156:65-73).  The results of this study, combined with that of the previous PFOA study, suggest that PFOA is a substrate for renal transporters in fish while glomerular filtration alone may be sufficient to explain the observed renal elimination of PFOS.  These findings demonstrate that models developed to predict the bioaccumulation of perfluoroalkyl acids by fish must account for differences in renal clearance of individual compounds. \n\nThis dataset is associated with the following publication:\nConsoer, D., A. Hoffman , P. Fitzsimmons , P. Kosian , and J. Nichols. Toxicokinetics of perfluorooctane sulfonate in rainbow trout (Oncorhynchus mykiss).   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 35(3): 717-727, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-qc04-240",
            "keyword": [
                "perfluorooctane sulfonate",
                "renal elimination",
                "fish",
                "bioaccumulation",
                "toxicokinetics",
                "rainbow trout"
            ],
            "contactPoint": {
                "fn": "John Nichols",
                "hasEmail": "mailto:nichols.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "Consoer et al._Sciencehub entry.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/240/Consoer%20et%20al._Sciencehub%20entry.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-25",
            "references": [
                "https://doi.org/10.1002/etc.3230"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Macroinvertebrate and organic matter export from headwater tributaries of a Central Appalachian stream",
            "description": "The dataset contains physicochemical and biological data from 12 headwater tributaries of Clemons Fork in Robinson Forest, KY. \n\nThis dataset is associated with the following publication:\nPond , G., K. Fritz , and B. Johnson. Macroinvertebrate and organic matter export from headwater tributaries of a Central Appalachian stream.   HYDROBIOLOGIA. Springer, New York, NY, USA,  1-17, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-5tb7-233",
            "keyword": [
                "headwater streams",
                "drift",
                "Central Appalachian Mountains",
                "aquatic insects",
                "dispersal"
            ],
            "contactPoint": {
                "fn": "Ken Fritz",
                "hasEmail": "mailto:fritz.ken@epa.gov"
            },
            "distribution": [
                {
                    "title": "Drift data for Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/233/Drift%20data%20for%20Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-24",
            "references": [
                "https://doi.org/10.1007/s10750-016-2800-0"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/233/documents/data%20dictionary%20for%20Hydrobiologia%20779_75-91.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Added Value via SPI supplement",
            "description": "Supplement that indicates where to find the source data sets on the EPA system. \n\nThis dataset is associated with the following publication:\nBowden, J., K.D. Talgo, T. Spero , and C. Nolte. Assessing the Added Value of Dynamical Downscaling Using the Standardized Precipitation Index.   ADVANCES IN METEOROLOGY. Hindawi Publishing Corporation, New York, NY, USA, 2016(8432064): 14 pages, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-zw4g-245",
            "keyword": [
                "supplement",
                "regional climate modeling",
                "dynamical downscaling",
                "WRF",
                "SPI"
            ],
            "contactPoint": {
                "fn": "Tanya Spero",
                "hasEmail": "mailto:spero.tanya@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHub supplement.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/245/ScienceHub%20supplement.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-08-26",
            "references": [
                "https://doi.org/10.1155/2016/8432064"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CESM Lakes Monthly",
            "description": "This dataset contains monthly aggregates of 2D near-surface fields from the WRF model simulations labeled \"default\" (using WRF default approach to setting lake surface temperatures for downscaling) and \"clmlst\" (which uses lake surface temperatures from CLM to supplement those provided with CMIP5 archive of CESM). \n\nThis dataset is associated with the following publication:\nSpero , T., C. Nolte , J.H. Bowden, M.S. Mallard, and J. Herwehe. The Impact of Incongruous Lake Temperatures on Regional Climate Extremes Downscaled from the CMIP5 Archive Using the WRF Model.   Journal of Climate. American Meteorological Society, Boston, MA, USA, 29(2): 839-853, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-31zg-223",
            "keyword": [
                "monthly",
                "regional climate modeling",
                "WRF",
                "CMIP5",
                "dynamical downscaling"
            ],
            "contactPoint": {
                "fn": "Tanya Spero",
                "hasEmail": "mailto:spero.tanya@epa.gov"
            },
            "distribution": [
                {
                    "title": "default.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/223/default.tar",
                    "mediaType": "application/x-tar"
                },
                {
                    "title": "clmlst.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/223/clmlst.tar",
                    "mediaType": "application/x-tar"
                }
            ],
            "modified": "2014-12-23",
            "references": [
                "https://doi.org/10.1175/jcli-d-15-0233.1"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Characterization of pollutant dispersion near elongated buildings based on wind tunnel simulations-BDW-1",
            "description": "This data set is associated with the results found in the journal article: Perry et al, 2016. Characterization of pollutant dispersion near elongated buildings based on wind tunnel simulations, Atmospheric Environment, 142, 286-295.\r\nThe paper presents a wind tunnel study of the effects of elongated rectangular buildings on the dispersion of pollutants from nearby stacks. The study examines the influence of source location, building aspect ratio, and wind direction on pollutant dispersion with the goal of developing improved algorithms within dispersion models. The paper also examines the current AERMOD/PRIME modeling capabilities compared to wind tunnel observations.  Differences in the amount of plume material entrained in the wake region downwind of a building for various source locations and source heights are illustrated with vertical and lateral concentration profiles. These profiles were parameterized using the Gaussian equation and show the influence of building/source configurations on those parameters. When the building is oriented at 45\u00b0 to the approach flow, for example, the effective plume height descends more rapidly than it does for a perpendicular building, enhancing the resulting surface concentrations in the wake region. Buildings at angles to the wind cause a cross-wind shift in the location of the plume resulting from a lateral mean flow established in the building wake. These and other effects that are not well represented in many dispersion models are important considerations when developing improved algorithms to estimate the location and magnitude of concentrations downwind of elongated buildings. \n\nThis dataset is associated with the following publication:\nPerry , S., D. Heist , L. Brouwer, E. Monbureau, and L. Brixey. Characterization of pollutant dispersion near elongated buildings based on wind tunnel simulations.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 142: 286-295, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-d51p-171",
            "keyword": [
                "wind tunnel",
                "dispersion modeling",
                "building downwash"
            ],
            "contactPoint": {
                "fn": "Steven Perry",
                "hasEmail": "mailto:perry.steven@epa.gov"
            },
            "distribution": [
                {
                    "title": "Perry A-d51p-DatafilesBDW-1-20160805.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/171/Perry%20A-d51p-DatafilesBDW-1-20160805.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-08-05",
            "references": [
                "http://www.sciencedirect.com/science/article/pii/S1352231016305829"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/171/documents/Perry%20A-d51p-DataDictionaryBDW-1-20160805.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data used to generate tables and figures in Holder et al. (2016) Journal of Geophsyical Research: Atmospheres 121, doi:10.1002/2015JD024321",
            "description": "This dataset provides all data used to generate the figures and tables in the article entitled \"Particulate matter and black carbon optical properties and emission factors from prescribed fires in the southeastern United States\" published in the Journal of Geophysical Research: Atmospheres. \n\nThis dataset is associated with the following publication:\nHolder , A., G. Hagler , J. Aurell, M. Hays , and B. Gullett. Particulate matter and black carbon optical properties and emission factors from prescribed fires in the southeastern United States.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 121(7): 3465-3483, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-mgr4-234",
            "keyword": [
                "biomass burning",
                "Combustion Emissions",
                "Black Carbon",
                "Brown Carbon",
                "Fine Particulate Matter",
                "Aerosol Optical Properties",
                "Secondary Organic Aerosol"
            ],
            "contactPoint": {
                "fn": "Amara Holder",
                "hasEmail": "mailto:holder.amara@epa.gov"
            },
            "distribution": [
                {
                    "title": "JGR2016 Data Tables and Dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/234/JGR2016%20Data%20Tables%20and%20Dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-03-10",
            "references": [
                "https://doi.org/10.1002/2015jd024321"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figure_2_data",
            "description": "Data for Figure 2. \n\nThis dataset is associated with the following publication:\nSarwar, G., D. Kang, K. Foley, D. Schwede, B. Gantt, and R. Mathur. Technical note: Examining ozone deposition over seawater.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 141: 255\u2013262, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-44j4-229",
            "keyword": [
                "iodide",
                "dimethylsulfide",
                "dissolved organic carbon",
                "Ozone",
                "deposition"
            ],
            "contactPoint": {
                "fn": "Golam Sarwar",
                "hasEmail": "mailto:sarwar.golam@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure_2_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/229/Figure_2_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-23",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2016.06.072"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Phylogeny and Species Diversity of Gulf of California Oysters",
            "description": "Dataset of DNA sequence data from two mitochondrial loci (COI and 16S) used to infer the phylogeny of oysters in the genus Ostrea along the Pacific coast of North America. This dataset is not publicly accessible because: It's already publicaly available. It can be accessed through the following means: GenBank/NCBI (http://www.ncbi.nlm.nih.gov/). Accession numbers KT317088-KT317610. Format: This dataset is DNA sequence data. It is available in GenBank. Accession numbers KT317088-KT317610. \n\nThis dataset is associated with the following publication:\nRaith, M., D. Zacherl, E. Pilgrim , and D. Eernisse. Phylogeny and species diversity of Gulf of California oysters (Ostreidae) inferred from mitochondrial DNA.   American Malacological Bulletin. American Malacological Society, Arlington, VA, USA, 33(2): 263-283, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-0vt5-251",
            "keyword": [
                "DNA Barcoding",
                "Ostrea",
                "Oyster",
                "Aquatic invasive species",
                "marcroinvertebrates"
            ],
            "contactPoint": {
                "fn": "Erik Pilgrim",
                "hasEmail": "mailto:pilgrim.erik@epa.gov"
            },
            "distribution": [],
            "modified": "2016-01-15",
            "references": [
                "https://doi.org/10.4003/006.033.0206"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CES_EHP_Figure_2",
            "description": "The increasing number of chemicals for which SHEDS probabilistic exposure assessment has been performed over the years. \n\nThis dataset is associated with the following publication:\nEgeghy , P., L. Sheldon, K. Isaacs , H. Ozkaynak, M. Goldsmith, J. Wambaugh , R. Judson , and T. Buckley. Computational Exposure Science: An Emerging Discipline to Support 21st-Century Risk Assessment.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 124(6): 697\u2013702, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-mgr5-248",
            "keyword": [
                "ExpoCast",
                "Exposure modeling",
                "Exposure Assessment",
                "Informatics",
                "SHEDS",
                "Computational exposure"
            ],
            "contactPoint": {
                "fn": "Peter Egeghy",
                "hasEmail": "mailto:egeghy.peter@epa.gov"
            },
            "distribution": [
                {
                    "title": "ORD-010901_dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/248/ORD-010901_dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-10-28",
            "references": [
                "https://doi.org/10.1289/ehp.1509748"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Kanawha River Basin Sediment Data",
            "description": "This data set contains sediment size data collected at research sites using a Wolman Pebble Count method. \n\nThis dataset is associated with the following publication:\nCollins , S., M. Thoms, and J. Flotemersch. Hydrogeomorphic zones characterize riverbed sediment patterns within a river network.   River Systems. E. Schweizerbart'sche Verlagsbuchhandlung, Stuttgart,  GERMANY, 21(4): 203-213, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-3bk6-252",
            "keyword": [
                "sediment count",
                "Hydrogeomorphic characterization",
                "river type",
                "functional process zones"
            ],
            "contactPoint": {
                "fn": "Joseph Flotemersch",
                "hasEmail": "mailto:flotemersch.joseph@epa.gov"
            },
            "distribution": [
                {
                    "title": "Kanawha River Basin Sediment Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/252/Kanawha%20River%20Basin%20Sediment%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-15",
            "references": [
                "https://doi.org/10.1127/1868-5749/2014/0084"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/252/documents/Data%20Dictionary%20for%20Collins%20Kanawha%20Sediment%20manuscript.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Decontamination Data - Blister Agents",
            "description": "Decontamination efficacy data for blister agents on various building materials using various decontamination solutions. \n\nThis dataset is associated with the following publication:\nStone, H., D. See, A. Smiley, A. Ellingson, J. Schimmoeller, and L. Oudejans. Surface Decontamination of Blister Agents Lewisite, Sulfur Mustard and Agent Yellow, a Lewisite and Sulfur Mustard Mixture.   JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, USA,  1-5, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "A-mkmc-4",
            "keyword": [
                "Decontamination",
                "blister agents",
                "lewisite",
                "sulfur mustard",
                "agent yellow",
                "chemical warfare agents",
                "efficacy"
            ],
            "contactPoint": {
                "fn": "Lukas Oudejans",
                "hasEmail": "mailto:oudejans.lukas@epa.gov"
            },
            "distribution": [
                {
                    "title": "Summary Data for Statistical Analysis 082216_clean.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/4/Summary%20Data%20for%20Statistical%20Analysis%20082216_clean.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "ANOVA Input and Results Combined.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/4/ANOVA%20Input%20and%20Results%20Combined.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-18",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Evaluation of the Efficacy of Methyl Bromide in the Decontamination of Building and Interior Materials Contaminated with Bacillus anthracis Spores",
            "description": "Spreadsheets containing data for recovery of spores from different materials.  Data on the fumigation parameters are also included. \n\nThis dataset is associated with the following publication:\nWood , J., M. Wendling, W. Richter, A. Lastivka, and L. Mickelsen. Evaluation of the Efficacy of Methyl Bromide in the Decontamination of Building and Interior Materials Contaminated with Bacillus anthracis Spores.   APPLIED AND ENVIRONMENTAL MICROBIOLOGY. American Society for Microbiology, Washington, DC, USA,  1-28, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "A-hmh4-107",
            "keyword": [
                "Decontamination",
                "Bacillus anthracis",
                "methyl bromide"
            ],
            "contactPoint": {
                "fn": "Joseph Wood",
                "hasEmail": "mailto:wood.joe@epa.gov"
            },
            "distribution": [
                {
                    "title": "final data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/107/final%20data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2015-04-23",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/107/documents/data%20dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset for Testing Contamination Source Identification Methods for Water Distribution Networks",
            "description": "This dataset includes the results of a simulation study using the source inversion techniques available in the Water Security Toolkit. The data was created to test the different techniques for accuracy, specificity, false positive rate, and false negative rate. The tests examined different parameters including measurement error, modeling error, injection characteristics, time horizon, network size, and sensor placement. The water distribution system network models that were used in the study are also included in the dataset. \n\nThis dataset is associated with the following publication:\nSeth, A., K. Klise, J. Siirola, T. Haxton , and C. Laird. Testing Contamination Source Identification Methods for Water Distribution Networks.   Journal of Environmental Division, Proceedings of American Society of Civil Engineers. American Society of Civil Engineers  (ASCE), Reston, VA, USA,  ., (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "A-pg4z-149",
            "keyword": [
                "accuracy",
                "specificity",
                "false positive rate",
                "false negative rate",
                "Drinking water distribution system",
                "Source identification",
                "Testing"
            ],
            "contactPoint": {
                "fn": "Terranna Haxton",
                "hasEmail": "mailto:haxton.terra@epa.gov"
            },
            "distribution": [
                {
                    "title": "Dataset_A-pg4z_TestSourceInversion_Haxton_20160728.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/149/Dataset_A-pg4z_TestSourceInversion_Haxton_20160728.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-07-28",
            "references": [
                "https://doi.org/10.1061/(asce)wr.1943-5452.0000619"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Genetic linkage map and comparative genome analysis for the estuarine Atlantic killifish (Fundulus heteroclitus)",
            "description": "Genetic linkage maps are valuable tools in evolutionary biology; however, their availability for wild populations is extremely limited. Fundulus heteroclitus (Atlantic killifish) is a non-migratory estuarine fish that exhibits high allelic and phenotypic diversity partitioned among subpopulations that reside in disparate environmental conditions. An ideal candidate model organism for studying gene-environment interactions, the molecular toolbox for F. heteroclitus is limited. We identified hundreds of novel microsatellites which, when combined with existing microsatellites and single nucleotide polymorphisms (SNPs), were used to construct the first genetic linkage map for this species. By integrating independent linkage maps from three genetic crosses, we developed a consensus map containing 24 linkage groups, consistent with the number of chromosomes reported for this species. These linkage groups span 2300 centimorgans (cM) of recombinant genomic space, intermediate in size relative to the current linkage maps for the teleosts, medaka and zebrafish. Comparisons between fish genomes support a high degree of synteny between the consensus F. heteroclitus linkage map and the medaka and (to a lesser extent) zebrafish physical genome assemblies. \n\nThis dataset is associated with the following publication:\nWaits , E., J. Martinson , B. Rinner, S. Morris, D. Proestou, D. Champlin , and D. Nacci. Genetic linkage map and comparative genome analysis for the estuarine Atlantic killifish (Fundulus heteroclitus).   Open Journal of Genetics. Scientific Research Publishing, Inc., Irvine, CA, USA, 6: 28-38, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-rn98-237",
            "keyword": [
                "Fundulus heteroclitus",
                "Genetic Linkage Map",
                "Synteny Analysis",
                "Microsatellite",
                "Single Nucleotide Polymorphism (SNP)"
            ],
            "contactPoint": {
                "fn": "Eric Waits",
                "hasEmail": "mailto:waits.eric@epa.gov"
            },
            "distribution": [
                {
                    "title": "Waits et al Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/237/Waits%20et%20al%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-03-23",
            "references": [
                "https://doi.org/10.4236/ojgen.2016.61004"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Evaluation of improved land use data and canopy representation in BEIS with biogenic VOC measurements in California",
            "description": "The link provided access to all the datasets and metadata used in this manuscript for the model development and evaluation per Geoscientific Model Development's publication guidelines with the exception of the model output due to its size. \n\nThis dataset is associated with the following publication:\nBash , J., K. Baker , and M. Beaver. Evaluation of improved land use and canopy representation in BEIS v3.61 with biogenic VOC measurements in California.   Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 9: 2191-2207, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-n03b-256",
            "keyword": [
                "Biogenic VOC",
                "BEIS",
                "MEGAN",
                "isoprene"
            ],
            "contactPoint": {
                "fn": "Jesse Bash",
                "hasEmail": "mailto:bash.jesse@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.geosci-model-dev.net/9/2191/2016/gmd-9-2191-2016-assets.html",
                    "accessURL": "https://www.geosci-model-dev.net/9/2191/2016/gmd-9-2191-2016-assets.html"
                }
            ],
            "modified": "2016-06-16",
            "references": [
                "https://doi.org/10.5194/gmd-9-2191-2016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Global evaluation of ammonia bidirectional exchange and livestock diurnal variation schemes",
            "description": "There is no EPA generated dataset in this study. This dataset is not publicly accessible because: No EPA generated datasets were used in this study. The sole EPA author assisted in the development of the model algorithms and writing portions of the manuscript. It can be accessed through the following means: Modeling and input data can be accessed by contacting the corresponding author of the paper: Daven Henze (daven.henze@colorado.edu)\r\n. Format: None. \n\nThis dataset is associated with the following publication:\nZhu, L., D. Henze, J. Bash , G. Jeong, K. Cady-Pereira, M. Shephard, M. Luo, F. Poulot, and S. Capps. Global evaluation of ammonia bidirectional exchange and livestock diurnal variation schemes.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 15: 12823-12843, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-05qg-255",
            "keyword": [
                "NH3 Emissions",
                "Nitrogen Cycle",
                "Inverse Modeling",
                "Global Model"
            ],
            "contactPoint": {
                "fn": "Jesse Bash",
                "hasEmail": "mailto:bash.jesse@epa.gov"
            },
            "distribution": [],
            "modified": "2015-11-24",
            "references": [
                "https://doi.org/10.5194/acp-15-12823-2015"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "DataSet for Passive Containment Journal Article",
            "description": "This data is for Figures 6 and 7 in the journal article.  The data also includes the two EPANET input files used for the analysis described in the paper, one for the looped system and one for the block system. \n\nThis dataset is associated with the following publication:\nGrayman, W., R. Murray , and D. Savic. Redesign of Water Distribution Systems for Passive Containment of Contamination.   JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA, 108(7): 381-391, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "A-rjf1-222",
            "keyword": [
                "EPANET",
                "containment",
                "homeland security",
                "water security",
                "water quality",
                "Contamination",
                "Drinking water distribution system",
                "modeling",
                "district meter areas"
            ],
            "contactPoint": {
                "fn": "Regan Murray",
                "hasEmail": "mailto:murray.regan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figures6and7.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/222/Figures6and7.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "EPANET_Input_Files.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/222/EPANET_Input_Files.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-01-01",
            "references": [
                "https://doi.org/10.5942/jawwa.2016.108.0105"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Nitrogen Discharge due to Climate Change and Land Cover Change",
            "description": "Simulated model output for the figures in the associated publication. Data are SWAT model simulation results for different scenarios of land-use change and climate change (Temp and Precip, Carbon Dioxide). The results are for two simulated watersheds in the Neuse River basin in North Carolina, USA. These are the raw data used to develop the figures in the paper. \n\nThis dataset is associated with the following publication:\nGabriel , M., C. Knightes , E. Cooter , and R. Dennis. Evaluating relative sensitivity of SWAT-simulated nitrogen discharge to projected climate and land cover changes for two watersheds in North Carolina, USA.   Hydrological Processes. John Wiley & Sons, Ltd., Indianapolis, IN, USA,  online, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-34tq-166",
            "keyword": [
                "nitrogen",
                "biogeochemical cycling",
                "SWAT",
                "landuse",
                "climate change",
                "Clean Air Act"
            ],
            "contactPoint": {
                "fn": "Christopher Knightes",
                "hasEmail": "mailto:knightes.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "figdata.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/166/figdata.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2014-07-31",
            "references": [
                "https://doi.org/10.1002/hyp.10707"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Hoffman etal 2016 Fisheries Data",
            "description": "Fish collection data associated with the data analysis presented in  Hoffman et al. 2016. Fisheries 41(1):26-37, DOI: 10.1080/03632415.2015.1114926. \n\nThis dataset is associated with the following publication:\nHoffman , J., J. Schloesser, A. Trebitz , G. Peterson , M. Gutsch , H. Quinlan, and J. Kelly. Sampling design for early detection of aquatic invasive species in Great Lakes ports.   FISHERIES. American Fisheries Society, Bethesda, MD, USA, 41(1): 26-37, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-sj4f-212",
            "keyword": [
                "fish",
                "Great Lakes",
                "Aquatic invasive species",
                "sampling design",
                "DNA technology"
            ],
            "contactPoint": {
                "fn": "Joel Hoffman",
                "hasEmail": "mailto:hoffman.joel@epa.gov"
            },
            "distribution": [
                {
                    "title": "HoffmanJoel_A_sj4f_Dataset_20160819.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/212/HoffmanJoel_A_sj4f_Dataset_20160819.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2013-02-06",
            "references": [
                "https://doi.org/10.1080/03632415.2015.1114926"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Literaure search for intermittent rivers research using ISI Web of Science",
            "description": "The dataset is the bibliometric information included in the ISI Web of Science database of scientific literature.  Table S2 accessible from the dataset link provides bibliometric information included in the literature search.  Table S1 provides the parameters used searching the ISI Web of Science database for each of the subdisciplines. \n\nThis dataset is associated with the following publication:\nLeigh, C., A. Boulton, J. Courtwright, K. Fritz , C. May, R. Walker, and T. Datry. Ecological research and management of intermittent rivers: an historical review and future directions.   FRESHWATER BIOLOGY. Blackwell Publishing, Malden, MA, USA, 61(8): 1181\u20131199, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-mpgm-269",
            "keyword": [
                "fish",
                "biogeochemistry",
                "ephemeral stream",
                "invertebrate",
                "temporary stream"
            ],
            "contactPoint": {
                "fn": "Ken Fritz",
                "hasEmail": "mailto:fritz.ken@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://onlinelibrary.wiley.com/doi/10.1111/fwb.12646/full",
                    "accessURL": "https://onlinelibrary.wiley.com/doi/10.1111/fwb.12646/full"
                },
                {
                    "title": "https://webofknowledge.com/",
                    "accessURL": "https://webofknowledge.com/"
                }
            ],
            "modified": "2014-08-21",
            "references": [
                "https://doi.org/10.1111/fwb.12646"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://images.webofknowledge.com/WOKRS522_2R1/help/WOS/hp_search.html",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "United States Geological Survey discharge data from five example gages on intermittent streams",
            "description": "The data are mean daily discharge data at United States Geological Survey gages.  Once column provides the date (mm/dd/yyyy) and the other column provides the mean daily discharge in cubic feet per second. \n\nThis dataset is associated with the following publication:\nCostigan, K., K. Jaeger, C. Goss, K. Fritz , and P. Goebel. Understanding controls on flow permanence in intermittent rivers to aid ecological research: integrating meteorology, geology and land cover.   ECOHYDROLOGY. Wiley Interscience, Malden, MA, USA,  online, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-cvdz-267",
            "keyword": [
                "temporary streams",
                "flow cessation",
                "connectivity",
                "continuity",
                "network expansion"
            ],
            "contactPoint": {
                "fn": "Ken Fritz",
                "hasEmail": "mailto:fritz.ken@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://waterdata.usgs.gov/nwis/dv/?site_no=06879650&agency_cd=USGS&referred_module=sw",
                    "accessURL": "https://waterdata.usgs.gov/nwis/dv/?site_no=06879650&agency_cd=USGS&referred_module=sw"
                },
                {
                    "title": "https://waterdata.usgs.gov/nwis/dv/?site_no=09470800&agency_cd=USGS&referred_module=sw",
                    "accessURL": "https://waterdata.usgs.gov/nwis/dv/?site_no=09470800&agency_cd=USGS&referred_module=sw"
                },
                {
                    "title": "https://waterdata.usgs.gov/or/nwis/dv/?site_no=11493500&agency_cd=USGS&referred_module=sw",
                    "accessURL": "https://waterdata.usgs.gov/or/nwis/dv/?site_no=11493500&agency_cd=USGS&referred_module=sw"
                },
                {
                    "title": "https://waterdata.usgs.gov/nwis/dv/?site_no=07141300&agency_cd=USGS&referred_module=sw",
                    "accessURL": "https://waterdata.usgs.gov/nwis/dv/?site_no=07141300&agency_cd=USGS&referred_module=sw"
                },
                {
                    "title": "https://waterdata.usgs.gov/id/nwis/dv/?site_no=13058529&agency_cd=USGS&referred_module=sw",
                    "accessURL": "https://waterdata.usgs.gov/id/nwis/dv/?site_no=13058529&agency_cd=USGS&referred_module=sw"
                }
            ],
            "modified": "2016-09-01",
            "references": [
                "https://doi.org/10.1002/eco.1712"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://help.waterdata.usgs.gov/codes-and-parameters",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "VIIRS satellite and ground pm2.5 monitoring data",
            "description": "contains all satellite, pm2.5, and meteorological data used in statistical modeling effort to improve prediction of pm2.5. \n\nThis dataset is associated with the following publication:\nSchliep, E., A. Gelfand, and D. Holland. Autoregressive Spatially-Varying Coefficient Models for Predicting Daily PM2:5 Using VIIRS Satellite AOT.   Advances in Statistical Climatology, Meteorology and Oceanography. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 1(0): 59-74, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-jm6j-259",
            "keyword": [
                "pm2.5",
                "satellite VIIRS data",
                "prediction"
            ],
            "contactPoint": {
                "fn": "David Holland",
                "hasEmail": "mailto:holland.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "PAgrid.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/259/PAgrid.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "PA510.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/259/PA510.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2015-01-15",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Complex watersheds, collaborative teams: Assessing pollutant presence and effects in the San Francisco Delta",
            "description": "Chemical monitoring data and biological data from field collected samples. \n\nThis dataset is associated with the following publication:\nBiales , A., D. Denton , D. Riordan, R. Breuer, A. Batt , D. Crane, and H. Schoenfuss. Complex watersheds, collaborative teams: Assessing pollutant presence and effects in the San Francisco Delta.   Integrated Environmental Assessment and Management. Allen Press, Inc., Lawrence, KS, USA, 11(4): 674-688, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-gqnz-265",
            "keyword": [
                "vitellogenin",
                "San Francisco",
                "surface water",
                "watershed assessment"
            ],
            "contactPoint": {
                "fn": "Adam Biales",
                "hasEmail": "mailto:biales.adam@epa.gov"
            },
            "distribution": [
                {
                    "title": "Supplementary Table 1 - ORD - NERL chemistry.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/265/Supplementary%20Table%201%20-%20ORD%20-%20NERL%20chemistry.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Supplementary Table 2 - ORD - NRMRL chemistry.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/265/Supplementary%20Table%202%20-%20ORD%20-%20NRMRL%20chemistry.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Supplementary Table 3 - CDFW chemistry.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/265/Supplementary%20Table%203%20-%20CDFW%20chemistry.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://onlinelibrary.wiley.com/doi/10.1002/ieam.1633/full",
                    "accessURL": "https://onlinelibrary.wiley.com/doi/10.1002/ieam.1633/full"
                }
            ],
            "modified": "2015-01-01",
            "references": [
                "https://doi.org/10.1002/ieam.1633"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "IMPACT OF GENETIC STRAIN ON BODY FAT LOSS, FOOD CONSUMPTION, METABOLISM, VENTILATION, AND MOTOR ACTIVITY IN FREE RUNNING FEMALE RATS",
            "description": "Physiologic data associated with different strains of common laboratory rat strains. \n\nThis dataset is associated with the following publication:\nGordon , C., P. Phillips , and A. Johnstone. Impact of Genetic Strain on Body Fat Loss, Food Consumption, Metabolism, Ventilation, and Motor Activity in Free Running Female Rats.   PHYSIOLOGY AND BEHAVIOR. Elsevier Science Ltd, New York, NY, USA, 153: 56-63, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-8gtr-264",
            "keyword": [
                "body fat",
                "Metabolism",
                "ventilation",
                "Running Wheel",
                "Genetic strain"
            ],
            "contactPoint": {
                "fn": "Christopher Gordon",
                "hasEmail": "mailto:gordon.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science Hub SHC 2.63 Five Strain RW BC METAB MA_Data for Figures.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/264/Science%20Hub%20SHC%202.63%20Five%20Strain%20RW%20BC%20METAB%20MA_Data%20for%20Figures.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-06-25",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Exploring Global Exposure Factors Resources URLs",
            "description": "The dataset is a compilation of hyperlinks (URLs) for resources (databases, compendia, published articles, etc.) useful for exposure assessment specific to consumer product use. \n\nThis dataset is associated with the following publication:\nZaleski, R., P. Egeghy, and P. Hakkinen. Exploring Global Exposure Factors Resources for Use in Consumer Exposure Assessments.   International Journal of Environmental Research and Public Health. Molecular Diversity Preservation International, Basel,  SWITZERLAND, 13(7): 744, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-rxx0-263",
            "keyword": [
                "URLs",
                "Web addresses",
                "ExpoCast",
                "Exposure factors",
                "Exposure Assessment",
                "Time activity patterns",
                "Consumer behavior",
                "Household products"
            ],
            "contactPoint": {
                "fn": "Peter Egeghy",
                "hasEmail": "mailto:egeghy.peter@epa.gov"
            },
            "distribution": [
                {
                    "title": "ORD\u2010016394_Data_Table.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/263/ORD%E2%80%90016394_Data_Table.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-06-13",
            "references": [
                "https://doi.org/10.3390/ijerph13070744"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/263/documents/ORD%E2%80%90016394_Data_Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data sets for manuscript titled Unexpected benefits of reducing aerosol cooling effects",
            "description": "These data sets were created using extensive model simulation results from the WRF-CMAQ model, population distributions, and through the use of an health impact assessment model - see manuscript for details. \n\nThis dataset is associated with the following publication:\nXing, J., J. Wang, R. Mathur , J. Pleim , S. Wang, C. Hogrefe , C. Gan, D. Wong , and J. Hao. Unexpected Benefits of Reducing Aerosol Cooling Effects.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(14): 7527\u20137534, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-bk3t-220",
            "keyword": [
                "WRF-CAMQ",
                "air pollution exposure",
                "Aerosol direct effects",
                "air quality-climate interactions",
                "Hemispheric CMAQ"
            ],
            "contactPoint": {
                "fn": "Rohit Mathur",
                "hasEmail": "mailto:mathur.rohit@epa.gov"
            },
            "distribution": [
                {
                    "title": "EST_data_Readme.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/220/EST_data_Readme.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "EST_data_summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/220/EST_data_summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "EST_figure3_shapefile_for_ArcGIS.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/220/EST_figure3_shapefile_for_ArcGIS.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "EST_figure1_shapefile_for_ArcGIS.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/220/EST_figure1_shapefile_for_ArcGIS.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2015-10-01",
            "references": [
                "http://pubs.acs.org/doi/abs/10.1021/acs.est.6b00767"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Published journal article with data",
            "description": "published journal article. \n\nThis dataset is associated with the following publication:\nSchumacher, B., J. Zimmerman, J. Elliot, and G. Swanson. The Effect of Equilibration Time and Tubing Material on Soil Gas Measurements.   SOIL AND SEDIMENT CONTAMINATION: AN INTERNATIONAL JOURNAL. CRC Press LLC, Boca Raton, FL, USA, 25(2): 151-163, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-7m0k-290",
            "keyword": [
                "soil gas",
                "equilibration time",
                "tubing type",
                "trichloroethylene",
                "TCE",
                "volatile organic compounds"
            ],
            "contactPoint": {
                "fn": "Brian Schumacher",
                "hasEmail": "mailto:schumacher.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "Published Article.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/290/Published%20Article.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2016-09-09",
            "references": [
                "https://doi.org/10.1080/15320383.2016.1111860"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2",
            "description": "The uploaded data consists of the BRACE Na aerosol observations paired with CMAQ model output, the updated model's parameterization of sea salt aerosol emission size distribution, and the model's parameterization of the sea salt emission factor as a function of sea surface temperature. \n\nThis dataset is associated with the following publication:\nGantt , B., J. Kelly , and J. Bash. Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2.   Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 8: 3733-3746, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-fn39-266",
            "keyword": [
                "air quality",
                "natural emissions",
                "CMAQ",
                "base cations"
            ],
            "contactPoint": {
                "fn": "Jesse Bash",
                "hasEmail": "mailto:bash.jesse@epa.gov"
            },
            "distribution": [
                {
                    "title": "Gantt et al 2015 GMD.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/266/Gantt%20et%20al%202015%20GMD.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-09-01",
            "references": [
                "https://doi.org/10.5194/gmd-8-3733-2015"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "STOTEN2016 Tong data",
            "description": "CTAG model inputs and outputs. \n\nThis dataset is associated with the following publication:\nTong, Z., R. Baldauf , V. Isakov , P.J. Deshmukh, and M. Zhang. Roadside vegetation barrier designs to mitigate near-road air pollution impacts.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 541: 920-927, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-gmsq-284",
            "keyword": [
                "particulate matter",
                "Urban Planning",
                "Green Infrastructure",
                "Dry Deposition",
                "air quality models"
            ],
            "contactPoint": {
                "fn": "Vladilen Isakov",
                "hasEmail": "mailto:isakov.vlad@epa.gov"
            },
            "distribution": [
                {
                    "title": "STOTEN2016Tong_data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/284/STOTEN2016Tong_data.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data4figures1.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/284/data4figures1.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data4figures2.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/284/data4figures2.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data4figures3.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/284/data4figures3.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data4figures4.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/284/data4figures4.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2015-06-29",
            "references": [
                "http://www.sciencedirect.com/science/article/pii/S0048969715307270"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "WRF-CMAQ simulations of Aerosol Direct Effects",
            "description": "CMAQ and WRF output files. This dataset is not publicly accessible because: Too Big. It can be accessed through the following means: The data can be accesses from the ASM data archive at the National Environmental Supercomputing Center at the USEPA. Format: WRF\u2013CMAQ Model output data including SW radiation, PM2.5 , Sulfate aerosol, EC, and SO2 concentrations,   Also aerosol optical depth (AOD). \n\nThis dataset is associated with the following publication:\nGan, C., J. Pleim , R. Mathur , C. Hogrefe , C.N. Long, J. Xing, D. Wong , R. Gilliam , and C. Wei. Assessment of long-term WRF\u2013CMAQ simulations for understanding direct aerosol effects on radiation \"brightening\" in the United States.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 15: 12193-12209, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-tmq3-170",
            "keyword": [
                "SURFRAD",
                "Castnet",
                "air quality",
                "WRF-CAMQ",
                "Aerosol",
                "Brightening"
            ],
            "contactPoint": {
                "fn": "Jonathan Pleim",
                "hasEmail": "mailto:pleim.jon@epa.gov"
            },
            "distribution": [],
            "modified": "2016-08-01",
            "references": [
                "https://doi.org/10.5194/acp-15-12193-2015"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Monthly statistics for WRF with and without MODIS vegetation",
            "description": "The 2006 monthly average statistical metrics for 2m Q (g kg-1) domain-wide for the base and MODIS WRF simulations against MADIS observations. \n\nThis dataset is associated with the following publication:\nRan, L., J. Pleim, R. Gilliam, F. Binkowski, C. Hogrefe, and L. Band. Improved meteorology from an updated WRF/CMAQ modeling system with MODIS vegetation and albedo.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 121(5): 2393-2415, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-80gj-289",
            "keyword": [
                "Water vapor mixing ratio",
                "Model statistics",
                "Sattelite",
                "LAI",
                "WRF-CMAQ",
                "MODIS",
                "Meteorology"
            ],
            "contactPoint": {
                "fn": "Jonathan Pleim",
                "hasEmail": "mailto:pleim.jon@epa.gov"
            },
            "distribution": [
                {
                    "title": "monthlyErrors_2006.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/289/monthlyErrors_2006.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "dailyError_2006.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/289/dailyError_2006.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-09-26",
            "references": [
                "https://doi.org/10.1002/2015jd024406"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "data for figures",
            "description": "Figures 1-10 and Table 1. \n\nThis dataset is associated with the following publication:\nChang, S.Y., S. Arunachalam, A. Valencia, B. Naess, V. Isakov , M. Breen , T. Palma , and W. Vizuete. A modeling framework for characterizing near-road air pollutant concentration at community scales.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 538: 905-921, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-c2g1-280",
            "keyword": [
                "Dispersion",
                "air pollution",
                "traffic",
                "exposure",
                "modeling"
            ],
            "contactPoint": {
                "fn": "Vladilen Isakov",
                "hasEmail": "mailto:isakov.vlad@epa.gov"
            },
            "distribution": [
                {
                    "title": "STOTEN2015_data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/280/STOTEN2015_data.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "model_output-hourly-2010-default.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/280/model_output-hourly-2010-default.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "model_output-hourly-2011-default.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/280/model_output-hourly-2011-default.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "model_output-hourly-2010-newfleet.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/280/model_output-hourly-2010-newfleet.zip",
                    "mediaType": "application/x-zip-compressed"
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                {
                    "title": "model_output-hourly-2011-newfleet.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/280/model_output-hourly-2011-newfleet.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "STOTEN2015_figures_and_tables.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/280/STOTEN2015_figures_and_tables.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2014-08-18",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2015.06.139"
            ],
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                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supporting Data and Information to Assessing Inhalation Exposures Associated with Contamination Events inWater Distribution Systems",
            "description": "EPANET network models (inp files) used in paper. The file \u201ccdf2003-12singles.txt\u201d developed using ATUS data, that contains tab-separated values for the starting times and cumulative probabilities plotted in Fig. 2 in supporting design report. There are 101 rows in the file. The first entry in each row is the cumulative probability (0 to 1.0) and the second entry is the corresponding starting time (0.0 to 24.0 hours). The second file (\u201ctwo events 2003-12.txt\u201d) was developed that contains data for all 36,652 ATUS respondents who reported two grooming events in 2003 to 2012. Results in this file are used in TEVA-SPOT to generate random starting time for individuals who take two showers per day. The file has 36,652 rows and five tab-separated columns. The first column contains the year the data were collected and the second column contains the ATUS identifiers used for the respondents. The third column contains the starting times in hours local time for the first event and the fourth column contains the starting time in hours local time for the second event. The fifth column provides the ATUS weights for the respondents. Weights are needed to compensate for the manner in which sampling and data collection were carried out in ATUS. The Report (EPA/600/R-15/271) documents the design for incorporating the capability for estimating inhalation doses in TEVA-SPOT. \n\nThis dataset is associated with the following publication:\nDavis, M., R. Janke , and T. Taxon. Assessing Inhalation Exposures Associated with Contamination Events in Water Distribution Systems.   PLoS ONE. Public Library of Science, San Francisco, CA, USA,  1-41, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "A-h44x-175",
            "keyword": [
                "EPANET network models",
                "Census data",
                "ATUS",
                "Cumulative probabilities for starting times for taking a shower",
                "drinking water distribution systems",
                "TEVA-SPOT",
                "Inhalation exposures",
                "microbial and volatile chemical exposures from inhalation",
                "humidifier inhalation exposures",
                "contaminants in water systems"
            ],
            "contactPoint": {
                "fn": "Robert Janke",
                "hasEmail": "mailto:janke.robert@epa.gov"
            },
            "distribution": [
                {
                    "title": "Assess_Inhal_Expos_Assoc_Contam_WDS_Davis-Janke-Taxon_PLOS1_2016.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/175/Assess_Inhal_Expos_Assoc_Contam_WDS_Davis-Janke-Taxon_PLOS1_2016.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "cdf2003-12singles.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/175/cdf2003-12singles.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "two_events_2003-12.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/175/two_events_2003-12.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "FINAL_TEVA-SPOT_Inhalation_models_EPA-600_R-15_271_REV5.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/175/FINAL_TEVA-SPOT_Inhalation_models_EPA-600_R-15_271_REV5.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2016-08-10",
            "references": [
                "https://doi.org/10.1371/journal.pone.0168051"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Maggie Creek Water Quality Data for Ecological Proper Functioning Condition Analysis",
            "description": "These data are \"standard\" water quality parameters collected for surface water condition analysis (for example pH, conductivity, DO, TSS). \n\nThis dataset is associated with the following publication:\nKozlowski, D., R. Hall , S. Swanson, and D. Heggem. Linking Management and Riparian Physical Functions to Water Quality and Aquatic Habitat.   JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT. American Society of Civil Engineers  (ASCE), Reston, VA, USA, 8(8): 797-815, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-4j13-199",
            "keyword": [
                "water quality",
                "Tribal Sustainability",
                "proper functioning condition",
                "ecological condition assessment",
                "Environmenal health",
                "Ecological Health",
                "Vulnerable Groups"
            ],
            "contactPoint": {
                "fn": "Daniel Heggem",
                "hasEmail": "mailto:heggem.daniel@epa.gov"
            },
            "distribution": [
                {
                    "title": "WQ_data_combined_v1.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/199/WQ_data_combined_v1.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2012-10-11",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Chronic test results",
            "description": "Data used for publication. \n\nThis dataset is associated with the following publication:\nStruewing, K., P. Weaver, J. Lazorchak , B. Johnson , D. Funk, and D. Buckwalter. Part 2: Sensitivity comparisons of the insect Centroptilum triangulifer to Ceriodaphnia dubia and Daphnia magna using standard reference toxicants; NaCl, KCl and CuSO4.   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 11(139): 597-603, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-brv9-224",
            "keyword": [
                "Mayfly",
                "Comparative Toxicity",
                "NaCl",
                "KCl",
                "CuSO4"
            ],
            "contactPoint": {
                "fn": "James Lazorchak",
                "hasEmail": "mailto:lazorchak.jim@epa.gov"
            },
            "distribution": [
                {
                    "title": "Katie Acute Results.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/224/Katie%20Acute%20Results.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Raw Chronic Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/224/Raw%20Chronic%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Mayfly; Chronic Cu++ Ref Tox Round III.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/224/Mayfly%3B%20Chronic%20Cu%2B%2B%20Ref%20Tox%20Round%20III.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Mayfly; Chronic Cu++ Ref Tox Round II.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/224/Mayfly%3B%20Chronic%20Cu%2B%2B%20Ref%20Tox%20Round%20II.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Mayfly; Chronic Cu++ Ref Tox Round I.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/224/Mayfly%3B%20Chronic%20Cu%2B%2B%20Ref%20Tox%20Round%20I.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-09",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2014.04.096"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Figures in Rainfall-induced release of microbes from manure: model development, parameter estimation, and uncertainty evaluation on small plots",
            "description": "\u2022\tFigure 1.  Ratio of cumulative released cells to cells initially present in the manure at Week 0 as they vary by time, manure type and age, microbe, and Event (i.e., season). The 95% confidence intervals of the observed median number of cells in microbial runoff are shown as the shaded area.\n\u2022\tFigure 2.  Typical observed and simulated cumulative microbial runoff for Plots A403 and C209 with individual plot calibration.\n\u2022\tFigure 3.  Observed versus simulated microbial runoff associated with the Approach 1, adjusted for cumulative results by manure type and Event. Results accounted for counts associated with field monitoring time intervals described in Section 2.1 Field method. NS=Nash-Sutcliffe modeling efficiency, EC=E. coli, En=enterococci, FC= fecal coliforms.\n\u2022\tFigure 4.  Ratio of cumulative released cells/mass to cells/mass initially present in the aged manure by time and component (e.g., microbe) for solid manure (a) and (b), and amended, dry litter, and slurry manure (c). Solid lines (Equation (11) correspond to values in Table 3 for solid manure, and dry litter and slurry manure, respectively: (a) uses individual b values, and (b) and (c) use the combined values for b. Bounds of first and third quartiles associated with the present study\u2019s results for cattle. Bounds of first and third quartiles associated with the present study\u2019s results for poultry and swine. The full color versions of all figures are available in the online version of this paper, at http://dx.doi.org/10.2166/wh.2016.239.\n\u2022\tFigure 5.  Ranges in \u03b1 and \u03b2 values for bovine (dairy calf, cattle, or cow) manure, as published or computed from the literature: (1) Bradford & Schijven (2002), (2) Schijven et al. (2004), (3) Guber et al. (2013), (4) Equation (9), (5) Blaustein et al. (2015), and (6) estimated in the present study (PEST and bootstrap). \n\nThis dataset is associated with the following publication:\nKim, K., G. Whelan , M. Molina , T. Purucker , Y. Pachepsky, A. Guber, M. Cyterski , D. Franklin, and R. Blaustein. Rainfall-induced release of microbes from manure: model development, parameter estimation, and uncertainty evaluation on small plots.   JOURNAL OF WATER AND HEALTH. IWA Publishing, London,  UK, 14(2): wh2016239, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-bp02-236",
            "keyword": [
                "bootstrap",
                "Bradford\u2013Schijven release model",
                "manure",
                "microbe",
                "PEST",
                "quantitative microbial risk assessment (QMRA)"
            ],
            "contactPoint": {
                "fn": "Gene Whelan",
                "hasEmail": "mailto:whelan.gene@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure1_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/236/Figure1_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure2_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/236/Figure2_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure3_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/236/Figure3_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure4_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/236/Figure4_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure5_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/236/Figure5_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-12-09",
            "references": [
                "https://doi.org/10.2166/wh.2016.239"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Table 1.  Summary of Field Testing and Measurement Data",
            "description": "Key performance parameters measured during the field demonstration such as lining thickness, compressive strength, Flexural Strength, Modulus of Elasticity, bond Strength, Density, Set/Cure Time, and Slump. \n\nThis dataset is associated with the following publication:\nMatthews, J., A. Selvakumar , S. Vaidya, and W. Condit. Large-Diameter Sewer Rehabilitation Using a Spray Applied Fiber Reinforced Geopolymer Mortar.   Practice Periodical on Structural Design and Construction. American Society of Civil Engineers (ASCE), New York, NY, USA, 20(4): 9999, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-7d83-19",
            "keyword": [
                "performance parameters",
                "lining thickness",
                "Field demonstration",
                "sewer pipe lining",
                "geopolymer",
                "spray applied"
            ],
            "contactPoint": {
                "fn": "Ariamalar Selvakumar",
                "hasEmail": "mailto:selvakumar.ariamalar@epa.gov"
            },
            "distribution": [
                {
                    "title": "Meta Data.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/19/Meta%20Data.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2014-11-03",
            "references": [
                "http://ascelibrary.org/doi/abs/10.1061/(ASCE)SC.1943-5576.0000246"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/19/documents/Meta%20Data.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for \"Controls on nitrous oxide production and consumption in reservoirs of the Ohio River Basin\"",
            "description": "Dissolved oxygen, dissolved nitrous oxide, and water temperature in reservoirs. \n\nThis dataset is associated with the following publication:\nBeaulieu , J., C. Nietch , and J. Young. Source or sink: Insight on controls of nitrous oxide biogeochemistry from a 20 reservoir survey.   Journal of Geophysical Research - Biogeosciences. American Geophysical Union, Washington, DC, USA, 120(10): 1995-2010, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-gtj6-146",
            "keyword": [
                "nitrous oxide saturation",
                "greenhouse gas emissions",
                "reservoirs",
                "epilimnion",
                "hypolimnion"
            ],
            "contactPoint": {
                "fn": "Jake Beaulieu",
                "hasEmail": "mailto:beaulieu.jake@epa.gov"
            },
            "distribution": [
                {
                    "title": "sdmp.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/146/sdmp.txt",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2015-01-30",
            "references": [
                "http://onlinelibrary.wiley.com/doi/10.1002/2015JG002941/full"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Neurite outgrowth in human iPSC-derived neurons",
            "description": "Data on morphology of rat and human neurons in cell culture. \n\nThis dataset is associated with the following publication:\nDruwe, I., T. Freudenrich , K. Wallace , T. Shafer , and W. Mundy. Comparison of Human Induced PluripotentStem Cell-Derived Neurons and Rat Primary CorticalNeurons as In Vitro Models of Neurite Outgrowth.   Applied In vitro Toxicology. Mary Ann Liebert, Inc., Larchmont, NY, USA, 2(1): 26-36, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-vdp1-99",
            "keyword": [
                "human IPSC",
                "neurite",
                "alternative models",
                "developmental neurotoxicity"
            ],
            "contactPoint": {
                "fn": "William Mundy",
                "hasEmail": "mailto:mundy.william@epa.gov"
            },
            "distribution": [
                {
                    "title": "Human iCell growth characterization.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/99/Human%20iCell%20growth%20characterization.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Neurite Growth Human iCell.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/99/Neurite%20Growth%20Human%20iCell.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Neurite Growth Rat Cortical.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/99/Neurite%20Growth%20Rat%20Cortical.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-09-01",
            "references": [
                "https://doi.org/10.1089/aivt.2015.0025"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Iron mineralogy and uranium-binding environment in the rhizosphere of a wetland soil",
            "description": "The dataset contains two XRF images of iron and uranium distribution on plant roots and a database of XANES data used to produce XANES spectra figure for Figure 7 in the published paper. \n\nThis dataset is associated with the following publication:\nKaplan, D., R. Kukkadapu, J. Seaman, B. Arey, A. Dohnalkova, S. Buettner, D. Li, T. Varga, K. Scheckel, and P. Jaffe. Iron Mineralogy and Uranium-Binding Environment in the Rhizosphere of a Wetland Soil.  D. Barcelo  SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 569: 53-64, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-8kq0-257",
            "keyword": [
                "uranium",
                "synchrotron speciation",
                "Mossbauer",
                "iron nanoparticles",
                "plant root",
                "wetlands"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "KaplanUPaper_XANES Spectra Fig 7.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/257/KaplanUPaper_XANES%20Spectra%20Fig%207.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "KaplanUPaper_XANES Spectra Fig 7XRFImages.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/257/KaplanUPaper_XANES%20Spectra%20Fig%207XRFImages.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-02-16",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.06.120"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Linear Combination Fitting (LCF)-XANES analysis of As speciation in selected mine-impacted materials",
            "description": "This table provides sample identification labels and classification of sample type (tailings, calcinated, grey slime).  For each sample, total arsenic and iron concentrations determined by acid digestion and ICP analysis are provided along with arsenic in-vitro bioaccessibility (As IVBA) values to estimate arsenic risk. Lastly, the table provides linear combination fitting results from synchrotron XANES analysis showing the distribution of arsenic speciation phases present in each sample along with fitting error (R-factor). \n\nThis dataset is associated with the following publication:\nOllson, C., E. Smith, K. Scheckel, A. Betts, and A. Juhasz. Assessment of arsenic speciation and bioaccessibility in mine-impacted materials.  Diana Aga, Wonyong Choi, Andrew Daugulis, Gianluca Li Puma, Gerasimos Lyberatos, and Joo Hwa Tay  JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, USA, 313: 130-137, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-tdzm-49",
            "keyword": [
                "in vitro bioaccessibility",
                "arsenic",
                "synchrotron speciation",
                "tailings"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Table 2 Ollsonetal_JHM2016.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/49/Table%202%20Ollsonetal_JHM2016.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2015-10-15",
            "references": [
                "https://doi.org/10.1016/j.jhazmat.2016.03.090"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Water Quality Time Series, Aggregate values, and Related Aggregate Risk Measures ",
            "description": "The excel file contains time series data of flow rates, concentrations of alachlor , atrazine, ammonia, total phosphorus, and total suspended solids observed in two watersheds in Indiana from 2002 to 2007. The aggregate time series data corresponding or representative to all these parameters was obtained using a specialized, data-driven technique. The aggregate data is hypothesized in the published paper to represent the overall health of both watersheds with respect to various potential water quality impairments. The time series data for each of the individual water quality parameters were used to compute corresponding risk measures (Rel, Res, and Vul) that are reported in Table 4 and 5. The aggregation of the risk measures, which is computed from the aggregate time series and water quality standards in Table 1, is  also reported in Table 4 and 5 of the published paper. Values under column heading \"uncertainty\" reports uncertainties associated with reconstruction of missing records of the water quality parameters. Long-term records of the water quality parameters were reconstructed in order to estimate the (R-R-V) and corresponding aggregate risk measures. \n\nThis dataset is associated with the following publication:\nHoque, Y., S. Tripathi, M. Hantush , and R. Govindaraju. Aggregate Measures of Watershed Health from Reconstructed Water Quality Data with Uncertainty.  Ed Gregorich  JOURNAL OF ENVIRONMENTAL QUALITY. American Society of Agronomy, MADISON, WI, USA, 45(2): 709-719, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-h9wd-69",
            "keyword": [
                "water quality",
                "pesticides",
                "nutrients",
                "sediment",
                "Risk Assessment",
                "Watershed",
                "Reliability",
                "Resiliance",
                "Vulnerability",
                "Uncertainty",
                "Aggregate Measure",
                "Watershed Health"
            ],
            "contactPoint": {
                "fn": "Mohamed Hantush",
                "hasEmail": "mailto:hantush.mohamed@epa.gov"
            },
            "distribution": [
                {
                    "title": "Aggregate_R-R-V_Paper_MetaData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/69/Aggregate_R-R-V_Paper_MetaData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2013-11-01",
            "references": [
                "https://doi.org/10.2134/jeq2015.10.0508"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "PNW Hydrologic Landscape Class",
            "description": "Work has been done to expand the hydrologic landscapes (HLs) concept and to develop an approach for using it to address streamflow vulnerability from climate change.  This work has included development of the HL classification framework and its application to Oregon, use of the HL classes to predict where a simple lumped hydrologic model accurately predicts daily streamflow, use of HL information to model the presence of cold-water patches at tributary confluences, and combining Oregon HL results with temperature and precipitation predictions to examine how HLs would vary as a result of climate change.  As a part of the current work, the HL approach has been expanded to the Pacific Northwest (Oregon, Washington, and Idaho) based on a revision of the approach that makes it more broadly applicable. This revised approach has several advantages compared with the original approach:  it is not limited to areas that have an aquifer permeability map; it uses a flexible approach to converting a nationally available geospatial dataset into assessment units; and it is more robust.  These improvements should allow the revised HL approach to be applied more often in situations requiring hydrologic classification, and allow greater confidence in results.  This effort paves the way for a climate change analysis for the Pacific Northwest that is currently underway, as well as expansion into the southwest (California, Arizona, and Nevada).  This dataset contains a high resolution version of the PNW HL maps along with shape files. \n\nThis dataset is associated with the following publication:\nLeibowitz , S., R. Comeleo , P.J. Wigington, Jr., M. Weber , E.A. Sproles, and K.A. Sawicz. Hydrologic Landscape Characterization for the Pacific Northwest, USA.   JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION. American Water Resources Association, Middleburg, VA, USA, 52(2): 473-493, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-w6mz-268",
            "keyword": [
                "hydrologic classification",
                "hydrologic cycle",
                "watersheds",
                "rivers/streams",
                "runoff",
                "geospatial analysis",
                "National Hydrography Dataset",
                "NHD",
                "Pacific Northwest"
            ],
            "contactPoint": {
                "fn": "Scott Leibowitz",
                "hasEmail": "mailto:leibowitz.scott@epa.gov"
            },
            "distribution": [
                {
                    "title": "PNW_HLs_41.5x36_v2_300dpi_060415.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/268/PNW_HLs_41.5x36_v2_300dpi_060415.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "https://gaftp.epa.gov/EPADataCommons/ORD/HydrologicLandscapes/pnw_hydrologic_landscape_class.zip",
                    "accessURL": "https://gaftp.epa.gov/EPADataCommons/ORD/HydrologicLandscapes/pnw_hydrologic_landscape_class.zip"
                }
            ],
            "modified": "2015-07-08",
            "references": [
                "https://doi.org/10.1111/1752-1688.12402"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Non-labile silver species in biosolids remain stable throughout 50 years of weathering and ageing",
            "description": "The dataset contains energy and absorption data for XANES spectra indicated in Figure 1 of the manuscript. \n\nThis dataset is associated with the following publication:\nDonner, E., K. Scheckel , R. Sekine, R. Popelka-Filcoff, J. Bennett, G. Brunetti, R. Naidu, S. McGrath, and E. Lombi. Non-labile silver species in biosolids remain stable throughout 50 years of weathering and ageing..  D.O. Carpenter, and E.Y. Zeng  ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 205: 78-86, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-s7hr-258",
            "keyword": [
                "silver nanoparticles",
                "synchrotron speciation",
                "biosolids",
                "isotopic dilution",
                "E-values"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "DonnerAgPaper_XANES Spectra Fig 1.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/258/DonnerAgPaper_XANES%20Spectra%20Fig%201.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-08-02",
            "references": [
                "https://doi.org/10.1016/j.envpol.2015.05.017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Fathead minnow whole-mount in situ hybridization (WISH)",
            "description": "This study demonstrates the potential of whole-mount in situ hybridization (WISH), in conjunction with quantitative real-time polymerase chain reaction (QPCR) assays, to examine the mechanistic basis of the effects of toxicants on early-lifestage fathead minnows. Specifically, fathead minnow embryos were exposed to the environmentally-relevant estrogen receptor agonist, estrone, and the data show that: (1) the estrogen-responsive gene transcripts esr1, vtg, and cyp19b can be up-regulated in very early-lifestages of the fathead minnow, (2) WISH methods developed for zebrafish can also be applied successfully to fathead minnows, and (3) WISH has potential to be a useful tool for toxicological studies pertaining to early-lifestage development in the fathead minnow. This type of mechanistic information relative to spatial distribution of gene expression is important in determining potential biological pathways that may be impacted by targeted chemicals and the development of associated adverse outcome pathways. \n\nThis dataset is associated with the following publication:\nCavallin, J., A. Schroeder, K. Jensen , D. Villeneuve , B. Blackwell, K. Carlson, M. Kahl , C. LaLone , E. Randolph , and G. Ankley. Evaluation of whole-mount in situ hybridization as a tool for pathway-based  toxicological research with early-life stage fathead minnows.   AQUATIC TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 169: 19-26, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-9w14-314",
            "keyword": [
                "qPCR",
                "whole mount in situ hybridization",
                "development",
                "adverse outcome pathway",
                "fathead minnow",
                "endocrine disruption"
            ],
            "contactPoint": {
                "fn": "Gerald Ankley",
                "hasEmail": "mailto:ankley.gerald@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cavallin et al 2015 Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/314/Cavallin%20et%20al%202015%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-14",
            "references": [
                "https://doi.org/10.1016/j.aquatox.2015.10.002"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dasroption of Heavy metals from water using pyrolized biochar",
            "description": "Removal of copper and lead metal ions from water using pyrolized plant materials. Method can be used to develop a low cost point-of-use device for cleaning contaminated water. \n\nThis dataset is associated with the following publication:\nDeMessie, B., E. Sahle-Demessie , and G. Sorial. Cleaning Water Contaminated With Heavy Metal Ions Using Pyrolyzed Banana Peel Adsorbents.   Separation Science and Technology. Marcel Dekker Incorporated, New York, NY, USA, 50(16): 2448-2457, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-0000-309",
            "keyword": [
                "copper and lead ions",
                "adsorption equilibrium",
                "removal efficiency",
                "pyrolyzed banana peel",
                "heavy metal",
                "kinetics"
            ],
            "contactPoint": {
                "fn": "Endalkac Sahle-Demessie",
                "hasEmail": "mailto:sahle-demessie.endalkachew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cleaning Water from Cu(II) using Pyrolized B.P..xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/309/Cleaning%20Water%20from%20Cu%28II%29%20using%20Pyrolized%20B.P..xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "ZetaPotential_bananaPeel.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/309/ZetaPotential_bananaPeel.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-07-24",
            "references": [
                "https://doi.org/10.1080/01496395.2015.1064134"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "SFBR Synoptic Study",
            "description": "The data set consists of fecal indicator bacteria and microbial source tracking marker concentrations in water and sediments across multiple seasons.  Samples were collected during baseflow from a variety of watershed classifications. Portions of this dataset are inaccessible because: Researchers are still working on manuscripts out of this data set and can't be released at this time. They can be accessed through the following means: Contacting corresponding author for product. Format: The data set will contain environmental parameters, fecal indicator bacteria concentrations and DNA source tracking markers. \n\nThis dataset is associated with the following publication:\nBradshaw, J.K., B. Snyder, A. Oladeinde, D. Spidle, M. Berrang, R. Meinersmann, B. Oakley, R. Sidle, K. Sullivan , and M. Molina. Characterizing relationships among fecal indicator bacteria, microbial source tracking markers, and associated waterborne pathogen occurrence in stream water and sediments in a mixed land use watershed.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 101: 498-509, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390078",
            "keyword": [
                "synoptic sampling",
                "agricultural watersheds",
                "pathogens",
                "fecal indicator bacteria",
                "sediments",
                "storm events",
                "Risk Assessment"
            ],
            "contactPoint": {
                "fn": "Marirosa Molina",
                "hasEmail": "mailto:molina.marirosa@epa.gov"
            },
            "distribution": [
                {
                    "title": "SFBR_Synoptic_Study_2013_WY_Master_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390078/SFBR_Synoptic_Study_2013_WY_Master_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-02-14",
            "references": [
                "https://doi.org/10.1016/j.watres.2016.05.014"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Stoichiometry of excreta and excretion rates of a stream-dwelling plethodontid salamander",
            "description": "Stoichiometry of excreta and excretion rates of a stream-dwelling plethodontid salamander in Cincinnati, OH, USA. \n\nThis dataset is associated with the following publication:\nMilanovich , J., and M. Hopton. Stoichiometry of excreta in larval stream salamanders: implications regarding the ecological roles of salamanders.   FUNCTIONAL ECOLOGY. Blackwell Publishing, Malden, MA, USA,  00, (2012).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-kh1q-282",
            "keyword": [
                "Eurycea cirrigera",
                "nitrogen",
                "phosphorus",
                "urea",
                "Plethodontidae",
                "fish",
                "amphibians",
                "salamanders",
                "stoichiometry",
                "land use",
                "stable isotopes",
                "headwater streams",
                "nutrients"
            ],
            "contactPoint": {
                "fn": "Matthew Hopton",
                "hasEmail": "mailto:hopton.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Milanovich_Hopton_2016_Copiea.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/282/Milanovich_Hopton_2016_Copiea.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2011-08-31",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Asian longhorned beetle complicates the relationship between taxonomic diversity and pest vulnerability in street tree assemblages",
            "description": "Urban foresters routinely emphasise the importance of taxonomic diversity to reduce the vulnerability of tree assemblages to invasive pests, but it is unclear to what extent diversity reduces vulnerability to polyphagous (i.e. generalist) pests. Drawing on field data from seven communities in metropolitan Cincinnati, Ohio, USA, we tested the hypothesis that communities with higher diversity would exhibit lower vulnerability to the polyphagous Asian longhorned beetle, which currently threatens the region. Based on street tree compositions and the beetle\u2019s host preferences, Asian longhorned beetle threatened up to 35.6% of individual street trees and 47.5% of the total basal area across the study area, but we did not see clear connections between taxonomic diversity and beetle vulnerability among study communities. For example, the city of Fairfield was among the least diverse communities but had the lowest proportion of trees vulnerable to Asian longhorned beetle, whereas the city of Wyoming exhibited high diversity and high vulnerability. On the other hand, Forest Park aligned with our original hypothesis, as it was characterised by low diversity and high vulnerability. Our results demonstrate that relatively high taxonomic diversity in street tree assemblages does not necessarily lead to reduced vulnerability to a polyphagous pest. Considering the threats posed by polyphagous pests, selecting a set of relatively pest resistant trees known to perform well in urban areas may promote long-term stability better than following simple heuristics for maximising taxonomic diversity, but further study is warranted. \n\nThis dataset is associated with the following publication:\nBerland , A., and M. Hopton. Asian longhorned beetle complicates the relationship between taxonomic diversity and pest vulnerability in street tree assemblages.   Arboricultural Journal: The International Journal of Urban Forestry. Taylor & Francis Group, London,  UK, 38(1): 28-40, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-8gts-285",
            "keyword": [
                "Asian longhorned beetle",
                "diversity",
                "invasive pests",
                "ecosystem services",
                "Green Infrastructure",
                "street trees",
                "biological diversity",
                "stormwater management"
            ],
            "contactPoint": {
                "fn": "Matthew Hopton",
                "hasEmail": "mailto:hopton.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Berland_Hopton_2016_ArboricJournal_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/285/Berland_Hopton_2016_ArboricJournal_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-07-14",
            "references": [
                "https://doi.org/10.1080/03071375.2016.1157305"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "National assessment of Tree City USA participation according to geography and socioeconomic characteristics",
            "description": "Tree City USA is a national program that recognizes municipal commitment to community forestry. In return for meeting program requirements, Tree City USA participants expect social, economic, and/or environmental benefits. Understanding the geographic distribution and socioeconomic characteristics of Tree City USA communities at the national scale can offer insights into the motivations or barriers to program participation, and provide context for community forestry research at finer scales. In this study, researchers assessed patterns in Tree City USA participation for all U.S. communities with more than 2,500 people according to geography, community population size, and socioeconomic characteristics, such as income, education, and race. Nationally, 23.5% of communities studied were Tree City USA participants, and this accounted for 53.9% of the total population in these communities. Tree City USA participation rates varied substantially by U.S. region, but in each region participation rates were higher in larger communities, and long-term participants tended to be larger communities than more recent enrollees. In logistic regression models, owner occupancy rates were significant negative predictors of Tree City USA participation, education and percent white population were positive predictors in many U.S. regions, and inconsistent patterns were observed for income and population age. The findings indicate that communities with smaller populations, lower education levels, and higher minority populations are underserved regionally by Tree City USA, and future efforts should identify and overcome barriers to participation in these types of communities. \n\nThis dataset is associated with the following publication:\nBerland , A., D. Herrmann , and M. Hopton. National Assessment of Tree City USA Participation According to Geography andSocioeconomic Characteristics.   Arboriculture & Urban Forestry. International Society of Arboriculture, Champaign, IL, USA, 42(2): 120-130, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-8gts-286",
            "keyword": [
                "Arbor Day Foundation",
                "community forestry",
                "Green Infrastructure",
                "municipal management",
                "ecosystem services",
                "street trees",
                "biological diversity",
                "stormwater management"
            ],
            "contactPoint": {
                "fn": "Matthew Hopton",
                "hasEmail": "mailto:hopton.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Berland_etal_2016_AUF_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/286/Berland_etal_2016_AUF_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-03-04",
            "references": [
                "http://auf.isa-arbor.com/articles.asp?JournalID=1&VolumeID=42&IssueID=2"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "HF183/BFDrev and HumM2 qPCR data",
            "description": "Concentration estimates for HF183/BFDrev and HumM2 qPCR genetic markers in raw sewage collected from 54 geographic locations across the United States. \n\nThis dataset is associated with the following publication:\nBoehm, A., J. Soller, and O. Shanks. Human-Associated Fecal qPCR Measurements and Predicted Risk of Gastrointestinal Illness in Recreational Waters Contaminated with Raw Sewage.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 2: 270-275, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-c5b8-98",
            "keyword": [
                "qPCR",
                "Microbial Source Tracking",
                "QMRA",
                "Fecal Pollution"
            ],
            "contactPoint": {
                "fn": "Orin Shanks",
                "hasEmail": "mailto:shanks.orin@epa.gov"
            },
            "distribution": [
                {
                    "title": "Boehm et al 2015_MST qPCR Data Set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/98/Boehm%20et%20al%202015_MST%20qPCR%20Data%20Set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-07-07",
            "references": [
                "http://pubs.acs.org/doi/pdf/10.1021/acs.estlett.5b00219"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "H002 (Cu), H003 (PVC), H072 (Cu), H079 (PVC)",
            "description": "Whole-genome sequences of four strains closely related to members of the Mycobacterium chelonae group, isolated from biofilms in a drinking water distribution system simulator. \n\nThis dataset is associated with the following publication:\nGomez-Alvarez, V., and R. Revetta. Whole-Genome Sequences of Four Strains Closely Related with Members of the Mycobacterium chelonae group, Isolated from Biofilms in a Drinking Water Distribution System Simulator.   Genome Announcements. American Society for Microbiology, Washington, DC, USA, 4(1): 1-2, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-1g1m-111",
            "keyword": [
                "Mycobacterium chelonae",
                "Polyvinyl chloride (PVC)",
                "Copper (Cu)",
                "drinking water",
                "genome",
                "chloramine",
                "sequences",
                "Mycobacterium"
            ],
            "contactPoint": {
                "fn": "Randy Revetta",
                "hasEmail": "mailto:revetta.randy@epa.gov"
            },
            "distribution": [
                {
                    "title": "Set02.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/111/Set02.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-07-01",
            "references": [
                "http://genomea.asm.org/content/4/1/e01539-15.full"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Applicability of UV resistant Bacillus pumilus spore as a human adenovirus surrogate for evaluating the effectiveness of virus inactivation in low-pressure UV treatment systems",
            "description": "Data set includes UV dose, and Bacillus pumilus spore plate counts in colony forming units. \n\nThis dataset is associated with the following publication:\nBoczek , L., E. Rhodes , J. Cashdollar, J. Ryu, J. Popovici , J. Hoelle , M. Sivaganesan , S. Hayes , M. Rodgers , and H. Ryu. Applicability of UV resistant Bacillus pumilus endospores as a human adenovirus surrogate for evaluating the effectiveness of virus inactivation in low-pressure UV treatment systems.   JOURNAL OF MICROBIOLOGICAL METHODS. Elsevier Science Ltd, New York, NY, USA, 122: 43-49, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-qvbb-102",
            "keyword": [
                "radiometer readings",
                "spore counts",
                "CFU",
                "Low-pressure UV disinfection",
                "UV resistant Bacillus pumilus spore",
                "human adenovirus surrogate"
            ],
            "contactPoint": {
                "fn": "Laura Boczek",
                "hasEmail": "mailto:boczek.laura@epa.gov"
            },
            "distribution": [
                {
                    "title": "spore paper science hub data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/102/spore%20paper%20science%20hub%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2013-07-31",
            "references": [
                "https://doi.org/10.1016/j.mimet.2016.01.012"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Characterization and optimization of cathodic conditions for H2O2 synthesis in microbial electrochemical cells",
            "description": "H2O2_COD_EPA: Measurements of hydrogen peroxide and COD concentrations for water samples from the MEC reactors.\nMEC_acclimation: raw data for current and voltage of the anode in the MEC reactor. \n\nThis dataset is associated with the following publication:\nSim, J., J. An, E. Elbeshbishy, R. Hodon, and H. Lee. Characterization and optimization of cathodic conditions for H2O2 synthesis in microbial electrochemical cells.   Bioresource Technology. Elsevier Online, New York, NY, USA, 195: 31-36, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-zkhr-96",
            "keyword": [
                "COD",
                "Hydrogen Peroxide",
                "current",
                "voltage",
                "anode",
                "microbial electrochemcial cell"
            ],
            "contactPoint": {
                "fn": "Hodon Ryu",
                "hasEmail": "mailto:ryu.hodon@epa.gov"
            },
            "distribution": [
                {
                    "title": "H2O2_COD_EPA 011515_Sci Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/96/H2O2_COD_EPA%20011515_Sci%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "MEC_acclimation_Sci Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/96/MEC_acclimation_Sci%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-14",
            "references": [
                "http://www.sciencedirect.com/science/article/pii/S0960852415008676"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Magnetic graphitic carbon nitride: its applicationin the C-& H-activation of amines.  ",
            "description": "Magnetic graphitic carbon nitride, Fe@g-C3N4, has been synthesized by adorning graphitic carbon nitride (g-C3N4) support with iron oxide via non-covalent interaction. The magnetically recyclable catalyst showed excellent reactivity for expeditious C-H activation and cyanation of amines. \n\nThis dataset is associated with the following publication:\nVerma, S., R.B. Nasir Baig, H. Changseok, M. Nadagouda , and R. Varma. Magnetic graphitic carbon nitride: its applicationin the C\u2013H activation of amines.   CHEMICAL COMMUNICATIONS. Royal Society of Chemistry, Cambridge,  UK, 51(85): 15554 - 15557, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-37q0-305",
            "keyword": [
                "Graphitic carbon nitride",
                "C-H Activation",
                "Earth-abundant materials",
                "Sustainable materials management"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.rsc.org/suppdata/c5/cc/c5cc05895c/c5cc05895c1.pdf",
                    "accessURL": "https://www.rsc.org/suppdata/c5/cc/c5cc05895c/c5cc05895c1.pdf"
                }
            ],
            "modified": "2015-10-13",
            "references": [
                "https://doi.org/10.1039/c5cc05895c"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Microbial pathogens in source and treated waters from drinking water treatment plants in the United States and implications for human health",
            "description": "Bacteria and fungi in source and treated drinking water. \n\nThis dataset is associated with the following publication:\nKing , D., S. Pfaller , M. Donohue , S. Vesper , E. Villegas , M. Ware , S. Glassmeyer , M. Vogal, E. Furlong, and D. Kolpin. Microbial pathogens in source and treated waters from drinking water treatment plants in the United States and implications for human health.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 562: 987\u2013995, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-cjt7-241",
            "keyword": [
                "mycobacteria",
                "legionella",
                "drinking water",
                "source water",
                "pharmaceuticals",
                "microorganisms",
                "Per- and polyfluoroalkyl substances"
            ],
            "contactPoint": {
                "fn": "Susan Glassmeyer",
                "hasEmail": "mailto:glassmeyer.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "PhaseIIMicro_Scihub_SPFALLER.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/241/PhaseIIMicro_Scihub_SPFALLER.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-25",
            "references": [
                "http://www.sciencedirect.com/science/article/pii/S0048969716306623"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Measured and Calculated Volumes of Wetland Depressions",
            "description": "Measured and calculated volumes of wetland depressions. \n\nThis dataset is associated with the following publication:\nWu, Q., and C. Lane. Delineation and quantification of wetland depressions in the Prairie Pothole Region of North Dakota.   WETLANDS. The Society of Wetland Scientists, McLean, VA, USA, 36(2): 215-227, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-xktc-327",
            "keyword": [
                "wetlands",
                "water storage"
            ],
            "contactPoint": {
                "fn": "Charles Lane",
                "hasEmail": "mailto:lane.charles@epa.gov"
            },
            "distribution": [
                {
                    "title": "Wu_and_Lane_Depression_Delineation_and_Quantification.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/327/Wu_and_Lane_Depression_Delineation_and_Quantification.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-01-01",
            "references": [
                "https://doi.org/10.1007/s13157-015-0731-6"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "phosphorus retention data and metadata",
            "description": "phosphorus retention in wetlands data and metadata. \n\nThis dataset is associated with the following publication:\nLane , C., and B. Autrey. Phosphorus retention of forested and emergent marsh depressional wetlands in differing land uses in Florida, USA.   Wetlands Ecology and Management. Springer Science and Business Media B.V;Formerly Kluwer Academic Publishers B.V.,   GERMANY, 24(1): 45-60, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-2fr1-281",
            "keyword": [
                "phosphorus",
                "wetlands"
            ],
            "contactPoint": {
                "fn": "Charles Lane",
                "hasEmail": "mailto:lane.charles@epa.gov"
            },
            "distribution": [
                {
                    "title": "P_retention_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/281/P_retention_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-01-01",
            "references": [
                "https://doi.org/10.1007/s11273-015-9450-2"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/281/documents/P_retention_data_dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data Sources for the Analyses ",
            "description": "Links are provided for the National Wetlands Inventory, National Hydrography Dataset, and the WorldClim-Global Climate Data source data websites. \n\nThis dataset is associated with the following publication:\nLane , C., and E. D'Amico. Identification of Putative Geographically Isolated Wetlands of the Conterminous United States.   JAWRA. American Water Resources Association, Middleburg, VA, USA,  online, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-mcvx-283",
            "keyword": [
                "geographically isolated wetlands;"
            ],
            "contactPoint": {
                "fn": "Charles Lane",
                "hasEmail": "mailto:lane.charles@epa.gov"
            },
            "distribution": [
                {
                    "title": "ID_of_pGIWs_Data.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/283/ID_of_pGIWs_Data.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "https://www.fws.gov/wetlands",
                    "accessURL": "https://www.fws.gov/wetlands"
                },
                {
                    "title": "https://nhd.usgs.gov/",
                    "accessURL": "https://nhd.usgs.gov/"
                },
                {
                    "title": "https://www.worldclim.org/",
                    "accessURL": "https://www.worldclim.org/"
                }
            ],
            "modified": "2015-10-01",
            "references": [
                "https://doi.org/10.1111/1752-1688.12421"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Multi-laboratory survey of qPCR enterococci analysis method performance in U.S. coastal and inland surface waters",
            "description": "Quantitative polymerase chain reaction (qPCR) has become a frequently used technique for quantifying enterococci in recreational surface waters, but there are several methodological options.  Here we evaluated how three method permutations, type of mastermix, sample extract dilution and use of controls in results calculation, affect method reliability among multiple laboratories with respect to sample interference.  Multiple samples from each of 22 sites representing an array of habitat types were analyzed using EPA Method 1611 and 1609 reagents with full strength and five-fold diluted extracts.  The presence of interference was assessed three ways: using sample processing and PCR amplifications controls; consistency of results across extract dilutions; and relative recovery of target genes from spiked enterococci in water sample compared to control matrices with acceptable recovery defined as 50 to 200%.  Method 1609, which is based on an environmental mastermix, was found to be superior to Method 1611, which is based on a universal mastermix. Method 1611 had over a 40% control assay failure rate with undiluted extracts and a 6% failure rate with diluted extracts.  Method 1609 failed in only 11% and 3% of undiluted and diluted extracts analyses.  Use of sample processing control assay results in the delta-delta Ct method for calculating relative target gene recoveries increased the number of acceptable recovery results.  Delta-delta tended to bias recoveries from apparent partially inhibitory samples on the high side which could help in avoiding potential underestimates of enterococci - an important consideration in a public health context.  Control assay and delta-delta recovery results were largely consistent across the range of habitats sampled, and among laboratories.  The methodological option that best balanced acceptable estimated target gene recoveries with method sensitivity and avoidance of underestimated enterococci densities was Method 1609 without extract dilution and using the delta-delta calculation method.  The applicability of this method can be extended by the analysis of diluted extracts to sites where interference is indicated but, particularly in these instances, should be confirmed by augmenting the control assays with analyses for target gene recoveries from spiked target organisms. \n\nThis dataset is associated with the following publication:\nHaugland , R., S. Siefring , M. Varma , K. Oshima , M. Sivaganesan , Y. Cao, M. Raith, J. Griffith, S. Weisberg, R. Noble, A.D. Blackwood, J. Kinzelman, T. Anan'eva, R. Bushon, E. Stelzer, V. Harwood, K. Gordon, and C. Sinigalliano. Multi-laboratory survey of qPCR enterococci analysis method performance in U.S. coastal and inland surface waters.   JOURNAL OF MICROBIOLOGICAL METHODS. Elsevier Science Ltd, New York, NY, USA, 123(1): 114-125, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-95xf-46",
            "keyword": [
                "Enterococci",
                "qPCR",
                "Interference",
                "Performance",
                "EPA Method 1609",
                "EPA Method 1611"
            ],
            "contactPoint": {
                "fn": "Richard Haugland",
                "hasEmail": "mailto:haugland.rich@epa.gov"
            },
            "distribution": [
                {
                    "title": "Metadata_20160506.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/46/Metadata_20160506.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-05-04",
            "references": [
                "https://doi.org/10.1016/j.mimet.2016.01.017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Photooxidation of farnesene mixtures in the presence of NOx: Analysis of reaction products and their implication to ambient PM2.5",
            "description": "Chemical analysis of SOA produced from the irradiation of a mixture of \u03b1/\u03b2-farnesene/NOx was conducted in a 14.5 cubic meter smog chamber. SOA collected on glass-fiber filters was solvent extracted, derivatized using BSTFA, and analyzed by GC-MS. Gas-phase products were analyzed using a combination of GC-FID and GC-MS. This analysis showed the occurrence of more than 30 SOA oxygenated species and more than 20 in the gas phase. The major SOA components measured include conjugated \u03b1 farnesene trienols, C3\u2013C7 linear dicarboxylic acids, carbonyl compounds, and hydroxy/carbonyl/carboxylic compounds. In the gas phase, the main species identified were formaldehyde, glyoxal, methylglyoxal, acetone, 2,3-dimethyl-oxirane, 2(3H)-furanone, 2-butenedioic acid, 4 oxopentanal, 4-methylenehex-5-enal, and 6-methylhept-5-en-2-one. Proposed reaction schemes are provided for selected compounds. H-atom abstraction and OH addition in \u03b1/\u03b2-farnesene oxidation seem to play an important role via the formation of unsaturated radicals containing different numbers of delocalized electrons. Allylic hydrogen abstraction and hydroperoxyalkyl radical channels might play a key role in the oxidation of \u03b1/\u03b2-farnesene. \nThe contribution of farnesene SOA products to ambient PM2.5 was investigated by analyzing PM2.5 samples collected during SOAS 2013 field study at a site in Research Triangle Park (RTP), NC. The importance of these findings was supported by the occurrence of several organic species in both field and laboratory samples, suggesting the impact of farnesene on the ambient aerosol burden, mainly in areas where farnesene emissions are high. Although, pentanedioic acid and methylsuccinic acid appear to be candidate markers for farnesene SOA, additional chamber and mechanistic studies are required to estimate the contributions of farnesene to ambient SOA. \n\nThis dataset is associated with the following publication:\nJaoui, M., M. Lewandowski , K. Docherty, E. Corse, B. Lonneman, J. Offenberg , and T. Kleindienst. Photooxidation of farnesene mixtures in the presence of NOx: Analysis of reaction products and their implication to ambient PM2.5.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 130: 190-201, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-dr84-238",
            "keyword": [
                "Sesquiterpenes",
                "Farnesene",
                "air quality",
                "Secondary Organic Aerosol",
                "air toxics",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Michael Lewandowski",
                "hasEmail": "mailto:lewandowski.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure1-3 data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/238/Figure1-3%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 1 metadata.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/238/Figure%201%20metadata.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Figure 2 metadata.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/238/Figure%202%20metadata.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Figure 3 metadata.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/238/Figure%203%20metadata.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-08-25",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2015.10.091",
                "https://pasteur.epa.gov/uploads/238/documents/GC-MS%20source%20file.zip"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Characterization of polar organosulfates in secondary organic aerosol from the unsaturated aldehydes 2-E-pentenal, 2-E-hexenal, and 3-Z-hexenal ",
            "description": "We show in the present study that the unsaturated aldehydes, 2-E-pentenal, 2-E-hexenal and 3-Z-hexenal, are biogenic volatile organic compound (BVOC) precursors for polar organosulfates with molecular weighs (MWs) 230 and 214, which are also present in ambient fine aerosol from a forested site, i.e., K-puszta, Hungary. These results complement those obtained in a previous study showing that the green leaf aldehyde 3-Z-hexenal serves as a precursor for MW 226 organosulfates. Thus, in addition to isoprene, the green leaf volatiles 2-E-hexenal and 3-Z-hexenal, emitted due to plant stress (mechanical wounding or insect attack), and 2-E-pentenal, a photolysis product of 3-Z-hexenal, should be taken into account for secondary organic aerosol and organosulfate formation. Polar organosulfates are of climatic relevance because of their hydrophilic properties and cloud effects. Extensive use was made of organic mass spectrometry (MS) and detailed interpretation of MS data (i.e., ion trap MS and accurate mass measurements) to elucidate the chemical structures of the MW 230, 214 and 170 organosulfates formed from 2-E-pentenal and indirectly from 2-E-hexenal and 3-Z-hexenal. In addition, quantum chemical calculations were performed to explain the different mass spectral behavior of 2,3-dihydroxypentanoic acid sulfate derivatives, where only the isomer with the sulfate group at C-3 results in the loss of SO3. The MW 214 organosulfates formed from 2-E-pentenal are explained by epoxidation of the double bond in the gas phase and sulfation of the epoxy group with sulfuric acid in the particle phase through the same pathway as that proposed for 2-hydroxy-2-methyl-3-sulfoxypropanoic acid from the isoprene-related \u03b1,\u03b2-unsaturated aldehyde methacrolein in previous work (Lin et al., 2013). The MW 230 organosulfates formed from 2-E-pentenal are tentatively explained by a novel pathway, which bears features of the latter pathway but introduces an additional hydroxyl group at the C-4 position. Evidence is also presented that the MW 214 positional isomer, 3hydroxy-2-sulfooxypentanoic acid is unstable and decarboxylates, giving rise to 2-hydroxy-1sulfoxybutane, a MW 170 organosulfate. Furthermore, evidence is obtained that lactic acid sulfate is generated from 2-E-pentenal. \n\nThis dataset is associated with the following publication:\nShalamzari, M., R. Vermeylen, F. Blockhuys, T. Kleindienst , M. Lewandowski , R. Szmigielski, K. Rudzinski, G. Spolnik, W. Danikiewicz, W. Maenhaut, and M. Claeys. Characterization of polar organosulfates in secondary organic aerosol from the unsaturated aldehydes 2-E-pentenal, 2-E-hexenal, and 3-Z-hexenal.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 16: 7135-7148, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-dr84-239",
            "keyword": [
                "hexenal",
                "pentenal",
                "organosulfate",
                "air quality",
                "Secondary Organic Aerosol",
                "air toxics",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Michael Lewandowski",
                "hasEmail": "mailto:lewandowski.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Sample data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/239/Sample%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-25",
            "references": [
                "http://www.atmos-chem-phys.net/16/7135/2016/"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data collected in Ostrava, Czech Republic and applied in a source apportionment model",
            "description": "These data support a published journal paper described as follows:\r\nA 14-week investigation during a warm and cold seasons was conducted to improve understanding of air\r\npollution sources that might be impacting air quality in Ostrava, the Czech Republic. Fine particulate\r\nmatter (PM2.5) samples were collected in consecutive 12-h day and night increments during spring and\r\nfall 2012 sampling campaigns. Sampling sites were strategically located to evaluate conditions in close\r\nproximity of a large steel works industrial complex, as well as away from direct influence of the\r\nindustrial complex. These samples were analyzed for metals and other elements, organic and elemental\r\n(black) carbon, and polycyclic aromatic hydrocarbons (PAHs). The PM2.5 samples were supplemented\r\nwith pollutant gases and meteorological parameters. We applied the EPA PMF v5.1 model with uncertainty estimate features to the Ostrava data set. Using the model's bootstrapping procedure and other considerations, six factors were determined to provide the optimum solution. Each model run consisted of 100 iterations to ensure that the solution represents a global minimum. The resulting factors were identified as representing coal (power plants), mixed Cl, crustal, industrial 1 (alkali metals and PAHs), industrial 2 (transition metals), and home heat/transportation. The home heating source is thought to be largely domestic boilers burning low quality fuels such as lignite, wood, and domestic waste.\r\nTransportation-related combustion emissions could not be resolved as a separate factor. Uncertainty\r\nestimates support the general conclusion that the factors identified as representing coal power and home\r\nheat/transportation dominate the percent contribution to fine mass. Apportionment of regulated individual\r\nspecies is also presented.\r\n\r\nTwo data files are provided to support the dataset. One provides the input data (concentrations and uncertainties) as used in the PMF source apportionment model. The other provides the processed data that directly support all quantitative information presented in the journal paper main text and supporting material. \n\nThis dataset is associated with the following publication:\nConner , T., L. \u010cernikovsk\u00fd, J. Nov\u00e1k, and R. Williams. Source apportionment with uncertainty estimates of fine particulate matter in Ostrava, Czech Republic using Positive Matrix Factorization.   Atmospheric Pollution Research. Turkish National Committee for Air Pollution Research and Control, Izmir,  TURKEY, 7(3): 503-512, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-n8q2-159",
            "keyword": [
                "Czech Republic",
                "steel manufacturing",
                "home heating",
                "source apportionment",
                "Fine Particulate Matter"
            ],
            "contactPoint": {
                "fn": "Teri Conner",
                "hasEmail": "mailto:conner.teri@epa.gov"
            },
            "distribution": [
                {
                    "title": "Ostrava PMF model input data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/159/Ostrava%20PMF%20model%20input%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Ostrava PMF dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/159/Ostrava%20PMF%20dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-11-17",
            "references": [
                "https://doi.org/10.1016/j.apr.2015.12.004"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "2014-12-19_PASSIVE NO2 STUDY_final data_kovalcik.xlsx",
            "description": "Nitrogen dioxide (NO2) concentrations relative to near road sites in Research Triangle area of North Carolina. \n\nThis dataset is associated with the following publication:\nSmith, L., S. Mukerjee , K. Kovalcik , E. Sams , C. Stallings , E. Hudgens , J. Scott , T. Krantz , and L. Neas. Near-road measurements for nitrogen dioxide and its association with traffic exposure zones.   Atmospheric Pollution Research. Turkish National Committee for Air Pollution Research and Control, Izmir,  TURKEY, 6: 1082-1086, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-j3vb-106",
            "keyword": [
                "air pollution",
                "Passive Samplers",
                "traffic"
            ],
            "contactPoint": {
                "fn": "Shaibal Mukerjee",
                "hasEmail": "mailto:mukerjee.shaibal@epa.gov"
            },
            "distribution": [
                {
                    "title": "2014-12-19_PASSIVE NO2 STUDY_final data_kovalcik.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/106/2014-12-19_PASSIVE%20NO2%20STUDY_final%20data_kovalcik.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-12-19",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Columbia University Puerto Rico Study.",
            "description": "Lifetime childhood asthma prevalence (LCAP) percentages in Puerto Rico Health\nRegions (HR) are substantially higher in northeastern vs. southwestern HR. Higher\naverage relative humidity in the northeast might promote mold and mite exposures\nand possibly asthma prevalence. To test this hypothesis, mold contamination, Environmental\nRelative Moldiness Index (ERMI) values were measured in floor dust\n(n = 26) and dust mite allergen concentrations in bed dust (n = 14). For this analysis,\nthe eight HR were divided into those with LCAP > 30% (n = 3) and < 30% (n = 5).\nThe average ERMI value was significantly greater (Wilcoxon Rank Sum, p < 0.001)\nin high than in low LCAP HR (14.5 vs. 9.3). The dust mite antigens Der p 1, Der f\n1, and Blo t 5 were detected in 90% of bed samples, but the concentrations were\nnot significantly different in high vs. low LCAP HR. Mold exposures might partially\nexplain the differences in LCAP HR in Puerto Rico. This dataset is not publicly accessible because: This was a study conducted by Columbia University researchers. It can be accessed through the following means: Contact:\r\nMatthew S. Perzanowski, Ph.D. \r\nAssociate Professor \r\nDepartment of Environmental Health Sciences \r\nMailman School of Public Health \r\nColumbia University \r\n(212) 305-3465. Format: This study was conducted by Columbia University.  There is no dataset format. \n\nThis dataset is associated with the following publication:\nVesper , S., H. Choi, M. Perzanowski, L. Acosta, A. Divjan, B. Bolanos-Rosero, F. Rivera-Mariani, and G. Chew. Mold populations and dust mite allergen concentrations in house dust samples from across Puerto Rico.   INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH. Carfax Publishing Limited, Basingstoke,  UK, 26(2): 198-207, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-cc2r-155",
            "keyword": [
                "mold",
                "dust mites",
                "ERMI"
            ],
            "contactPoint": {
                "fn": "Stephen Vesper",
                "hasEmail": "mailto:vesper.stephen@epa.gov"
            },
            "distribution": [],
            "modified": "2016-08-01",
            "references": [
                "https://doi.org/10.1080/09603123.2015.1089531"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The Relationship between Environmental Relative Moldiness Index Values and Asthma ",
            "description": "No data generated. This dataset is not publicly accessible because: There was no new data generated. It can be accessed through the following means: None available. Format: Since this was a review article, no new data was generated. \n\nThis dataset is associated with the following publication:\nVesper , S. The relationship between environmental relative moldiness index values and asthma.   INTERNATIONAL JOURNAL OF HYGIENE AND ENVIRONMENTAL HEALTH. Urban & Fischer Verlag Jena, Jena,  GERMANY, 219(1): 233-238, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-b2rn-287",
            "keyword": [
                "mold",
                "ERMI"
            ],
            "contactPoint": {
                "fn": "Stephen Vesper",
                "hasEmail": "mailto:vesper.stephen@epa.gov"
            },
            "distribution": [],
            "modified": "2016-09-01",
            "references": [
                "https://doi.org/10.1016/j.ijheh.2016.01.006"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A list of tables summarizing various Cmap analysis, from which the final tables in the manuscript are based on",
            "description": "Various Cmap analyses within and across species and microarray platforms conducted and summarized to generate the tables in the publication. \n\nThis dataset is associated with the following publication:\nWang , R., A. Biales , N. Garcia-Reyero, E. Perkins, D. Villeneuve, G. Ankley, and D. Bencic. Fish Connectivity Mapping: Linking Chemical Stressors by Their MOA-Driven Transcriptomic Profiles.   BMC Genomics. BioMed Central Ltd, London,  UK, 17(84): 1-20, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-s1s7-135",
            "keyword": [
                "Connectivity mapping",
                "fish",
                "Gene expression profiles",
                "ecotoxicology",
                "toxicology",
                "chemicals",
                "exposure",
                "mechanisms of action"
            ],
            "contactPoint": {
                "fn": "Ronglin Wang",
                "hasEmail": "mailto:wang.rong-lin@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cmap summary 02132015.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/135/Cmap%20summary%2002132015.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2015-05-30",
            "references": [
                "https://doi.org/10.1186/s12864-016-2406-y"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/135/documents/Cmap%20summary%2002132015.dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cytoscape file of chemical networks",
            "description": "The maximum connectivity scores of pairwise chemical conditions summarized from Cmap results in a file with Cytoscape format (http://www.cytoscape.org/).  The figures in the publication were generated from this file.  The Cytoscape file is formed from importing the eight text file therein. \n\nThis dataset is associated with the following publication:\nWang , R., A. Biales , N. Garcia-Reyero, E. Perkins, D. Villeneuve, G. Ankley, and D. Bencic. Fish Connectivity Mapping: Linking Chemical Stressors by Their MOA-Driven Transcriptomic Profiles.   BMC Genomics. BioMed Central Ltd, London,  UK, 17(84): 1-20, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-s1s7-137",
            "keyword": [
                "networks",
                "fish",
                "Gene expression profiles",
                "Connectivity mapping",
                "ecotoxicology",
                "toxicology",
                "chemicals",
                "exposure",
                "mechanisms of action"
            ],
            "contactPoint": {
                "fn": "Ronglin Wang",
                "hasEmail": "mailto:wang.rong-lin@epa.gov"
            },
            "distribution": [
                {
                    "title": "CmapCytoScapeFigures.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/137/CmapCytoScapeFigures.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2015-12-03",
            "references": [
                "https://doi.org/10.1186/s12864-016-2406-y"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/137/documents/CmapCytoscapeFigures.dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Fish connectivity mapping intermediate data files and outputs",
            "description": "RLWrankedLists.tar.gz:These lists linked to various chemical treatment conditions serve as the target collection of Cmap.  Probes of the entire microarray are sorted based on their log fold changes over control conditions.  RLWsignatures2015.tar.gz: These signatures linked to various chemical treatment conditions serve as queries in Cmap. This dataset is not publicly accessible because: too big in size. It can be accessed through the following means: located in the High Performance Computing archive /asm/FISHTOX/TAR_BALLs/fishCmap.tar.gz. Format: Fish connectivity mapping involves working with a large amount of data.  Of primary interest to other researchers and general public are probably the rank-ordered gene lists and gene signatures.  The former acts as a database-like target while the latter as queries.  Along with fish Cmap outputs, they are contained in the file fishCmap.tar.gz as RLWrankedLists.tar.gz and RLWsignatures2015.tar.gz. \n\nThis dataset is associated with the following publication:\nWang , R., A. Biales , N. Garcia-Reyero, E. Perkins, D. Villeneuve, G. Ankley, and D. Bencic. Fish Connectivity Mapping: Linking Chemical Stressors by Their MOA-Driven Transcriptomic Profiles.   BMC Genomics. BioMed Central Ltd, London,  UK, 17(84): 1-20, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-s1s7-138",
            "keyword": [
                "gene list",
                "gene signatures",
                "fish",
                "Gene expression profiles",
                "Connectivity mapping",
                "ecotoxicology",
                "toxicology",
                "chemicals",
                "exposure",
                "mechanisms of action"
            ],
            "contactPoint": {
                "fn": "Ronglin Wang",
                "hasEmail": "mailto:wang.rong-lin@epa.gov"
            },
            "distribution": [],
            "modified": "2015-11-09",
            "references": [
                "https://doi.org/10.1186/s12864-016-2406-y"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/138/documents/CmapGeneListsSignatures.dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Optimization and evaluation of a method to detect adenoviruses in river water",
            "description": "This dataset includes the recoveries of spiked adenovirus through various stages of experimental optimization procedures. \n\nThis dataset is associated with the following publication:\nMcMinn , B., A. Korajkic, and A. Grimm. Optimization and evaluation of a method to detect adenoviruses in river water.   JOURNAL OF VIROLOGICAL METHODS. Elsevier Science Ltd, New York, NY, USA, 231(1): 8-13, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-9060-315",
            "keyword": [
                "adenovirus",
                "celite",
                "secondary concentration",
                "DNA extraction"
            ],
            "contactPoint": {
                "fn": "Brian McMinn",
                "hasEmail": "mailto:mcminn.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHubDataSheet.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/315/ScienceHubDataSheet.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-14",
            "references": [
                "https://doi.org/10.1016/j.jviromet.2016.02.003"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Lumbriculus variegatus loading study",
            "description": "Results from sediment bioaccumulation tests with Lumbriculus variegatus with evaluating the effects of organism loading density. \n\nThis dataset is associated with the following publication:\nBurkhard , L., D.  Hubin-Barrows, N. Billa, T. Highland , R. Hockett , D. Mount , and T. Norberg-King. Sediment Bioaccumulation Test with Lumbriculus variegatus: Effects of Organism Loading.   ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY. Springer, New York, NY, USA, 71(7): 70-77, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-79cv-67",
            "keyword": [
                "Lumbriculus variegatus",
                "bioaccumulation",
                "sediment",
                "chemical uptake",
                "bioavailability",
                "sediment testing",
                "fish dietary studies"
            ],
            "contactPoint": {
                "fn": "Lawrence Burkhard",
                "hasEmail": "mailto:burkhard.lawrence@epa.gov"
            },
            "distribution": [
                {
                    "title": "BurkhardLawrence_Lumbriculus_Loading_Studies.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/67/BurkhardLawrence_Lumbriculus_Loading_Studies.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2015-09-15",
            "references": [
                "https://doi.org/10.1007/s00244-016-0284-6"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Larval fathead minnow swim bladder inflation following exposure to 2-mercaptobenzothiazole ",
            "description": "In this study, a hypothesized adverse outcome pathway (AOP) linking inhibition of thyroid peroxidase (TPO) activity to impaired swim bladder inflation was investigated in experiments in which fathead minnows were exposed to the TPO inhibitor 2-mercaptobenzothiazole (MBT). Results show that anterior, but not posterior, swim bladder inflation was impacted by exposure to MBT supporting the development of an AOP linking a specific thyroid-disrupting molecular initiating event to a significant phenotypic outcome. Results also suggest an alternative short-term in vivo test with larval fathead minnows that could be used to screen chemicals for thyroid disrupting activity and possibly distinguish thyroid disrupting modes of action. The dataset contains information on TPO expression, thyroid hormone concentrations, and swim bladder inflation measurements in larval fathead minnows. \n\nThis dataset is associated with the following publication:\nNelson, K., A. Schroeder , G. Ankley , B. Blackwell, C. Blanksma, S. Degitz , K. Jensen , R. Johnson , M. Kahl , D. Knapen, P. Kosian , R. Milsk, E. Randolph, T. Saari, E. Stinckens, L.  Vergauwen, and D. Villeneuve. Impaired anterior swim bladder inflation following exposure to the thyroid peroxidase inhibitor  2-Mercaptobenzothiazole  Part I: Fathead minnow.   AQUATIC TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 173: 192-203, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-hhmw-340",
            "keyword": [
                "adverse outcome pathway",
                "endocrine disruption",
                "swim bladder",
                "fish early lifestage",
                "cyprinid"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Nelson et al 2016 Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/340/Nelson%20et%20al%202016%20Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-15",
            "references": [
                "https://doi.org/10.1016/j.aquatox.2015.12.024"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Effect of exposure to wastewater treatment plant effluent on fathead minnow reproduction",
            "description": "Adult fathead minnows were exposed to dilutions of a historically estrogenic wastewater treatment plant effluent in a 21-d reproduction study. This dataset is comprised of a variety of endpoints representing key events along adverse outcome pathways linking estrogen receptor activation and other molecular initiating events to reproductive impairment. This study demonstrates the value of using an integrative approach that encompasses analytical chemistry, in vitro bioassays, and in vivo apical and pathway-based approaches with endpoints spanning from molecular- (e.g., gene expression) to organismal- (e.g., reproduction) levels of biological organization to help infer causal relationships between chemistry and potential effects on reproduction. \n\nThis dataset is associated with the following publication:\nCavallin , J., K. Jensen , M. Kahl , D. Villeneuve , K. Lee, A. Schroeder , J. Mayasich, E. Eid, K. Nelson, R. Milsk, B. Blackwell, J. Berninger , C. LaLone, C. Blanksma, T. Jicha , C. Elonen , R. Johnson , and G. Ankley. Pathway-based approaches for assessment of real-time exposure to an estrogenic wastewater treatment plant effluent on fathead minnow reproduction.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 35(3): 702-716, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-3fff-346",
            "keyword": [
                "wastewater treatment plant",
                "fish",
                "reproduction",
                "estrogens"
            ],
            "contactPoint": {
                "fn": "Gerald Ankley",
                "hasEmail": "mailto:ankley.gerald@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cavallin et al 2016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/346/Cavallin%20et%20al%202016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-16",
            "references": [
                "https://doi.org/10.1002/etc.3228"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Nanomaterials - pollutant interaction",
            "description": "Concentrations of different polyaromatic hydrocarbons in water before and after interaction with nanomaterials. The results show the capacity of engineer nanomaterials for adsorbing different organic pollutants. \n\nThis dataset is associated with the following publication:\nSahle-Demessie, E., A. Zhao, C. Han, B. Hann, and H. Grecsek. Interaction of engineered nanomaterials with hydrophobic organic pollutants..   Journal of Nanotechnology. Hindawi Publishing Corporation, New York, NY, USA, 27(28): 284003, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-bg7k-303",
            "keyword": [
                "hydrophobic pollutant adsorption",
                "engineered nanomaterials",
                "adsorption TGA/GC/MS",
                "hydrophobic pollutants",
                "ENM\u2013pollutant adsorption",
                "partitioning coefficient",
                "TGA/",
                "Engineered nanoparticles (NP)",
                "TGA/ GC/MS"
            ],
            "contactPoint": {
                "fn": "Endalkac Sahle-Demessie",
                "hasEmail": "mailto:sahle-demessie.endalkachew@epa.gov"
            },
            "distribution": [
                {
                    "title": "NP_Pesticide_Interaction.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/303/NP_Pesticide_Interaction.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "PAH Analysis by GC MS_12_13_2009.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/303/PAH%20Analysis%20by%20GC%20MS_12_13_2009.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Copy of GCMS Analysis Results N10 for Naphthalene Knm Test.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/303/Copy%20of%20GCMS%20Analysis%20Results%20N10%20for%20Naphthalene%20Knm%20Test.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Copy of GCMS Analysis Results N11 for Naphthalene Knm Test (002).xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/303/Copy%20of%20GCMS%20Analysis%20Results%20N11%20for%20Naphthalene%20Knm%20Test%20%28002%29.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-01-30",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Nanoparticle-organic pollutant interaction dataset",
            "description": "Dataset presents concentrations of organic pollutants, such as polyaromatic hydrocarbon compounds, in water samples. Water samples of known volume and concentration were allowed to equilibrate with known mass of nanoparticles. The mixture was then ultracentrifuged and sampled for analysis. \n\nThis dataset is associated with the following publication:\nSahle-Demessie, E., A. Zhao, C. Han, B. Hann, and H. Grecsek. Interaction of engineered nanomaterials with hydrophobic organic pollutants..   Journal of Nanotechnology. Hindawi Publishing Corporation, New York, NY, USA, 27(28): 284003, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-bg7k-304",
            "keyword": [
                "hydrophobic pollutant adsorption",
                "polyaromatic hydrocarbon",
                "Engineered nanoparticles (NP)",
                "hydrophobic pollutants",
                "ENM\u2013pollutant adsorption",
                "partitioning coefficient",
                "TGA/",
                "TGA/ GC/MS"
            ],
            "contactPoint": {
                "fn": "Endalkac Sahle-Demessie",
                "hasEmail": "mailto:sahle-demessie.endalkachew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Copy of GCMS Analysis Results N10 for Naphthalene Knm Test.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/304/Copy%20of%20GCMS%20Analysis%20Results%20N10%20for%20Naphthalene%20Knm%20Test.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Copy of GCMS Analysis Results N11 for Naphthalene Knm Test (002).xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/304/Copy%20of%20GCMS%20Analysis%20Results%20N11%20for%20Naphthalene%20Knm%20Test%20%28002%29.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "NP_Pesticide_Interaction.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/304/NP_Pesticide_Interaction.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Copy of GCMS Analysis Results N8 for Naphthalene Kow Test.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/304/Copy%20of%20GCMS%20Analysis%20Results%20N8%20for%20Naphthalene%20Kow%20Test.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-01-30",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Oxidative esterification via photocatalytic C-H activation",
            "description": "Direct oxidative esterification of alcohol via photocatalytic C\u2013H activation has been developed using VO@g-C3N4 catalyst; an expeditious esterification of alcohols occurs under neutral conditions using visible light as the source of energy. \n\nThis dataset is associated with the following publication:\nVarma , R., S. Verma, R.B.N. Baig, C. Han, and M. Nadagouda. Oxidative esterification via photocatalytic C-H activation.   GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge,  UK, 18: 251-254, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-37q0-308",
            "keyword": [
                "Oxidative esterification",
                "Photocatalytic C-H activation",
                "Visible light",
                "Earth-abundant materials",
                "Sustainable materials management"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.rsc.org/suppdata/c5/gc/c5gc02025e/c5gc02025e1.pdf",
                    "accessURL": "https://www.rsc.org/suppdata/c5/gc/c5gc02025e/c5gc02025e1.pdf"
                }
            ],
            "modified": "2015-12-22",
            "references": [
                "https://doi.org/10.1039/c5gc02025e"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Selective Oxidation of Alcohols Using Photoactive VO@g\u2011C3N4",
            "description": "A photoactive VO@g-C3N4 catalyst has been developed for the selective oxidation of alcohols to the corresponding aldehydes and ketones. The visible light mediated activity of the catalyst could be attributed to photoactive graphitic carbon nitrides surface. \n\nThis dataset is associated with the following publication:\nVerma, S., R.B. Nasir Baig, M. Nadagouda , and R. Varma. Selective oxidation of alcohols using photoactive VO@g-C3N4..   ACS Sustainable Chemistry & Engineering. American Chemical Society, Washington, DC, USA, 4(3): 1094-1098, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-37q0-318",
            "keyword": [
                "Photocatalyst",
                "Graphitic carbon nitride",
                "Selective oxidation",
                "Visible light",
                "Vanadium oxide",
                "Earth-abundant materials",
                "Sustainable materials management"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://s3-eu-west-1.amazonaws.com/pstorage-acs-6854636/3727291/sc5b01163_si_001.pdf",
                    "accessURL": "https://s3-eu-west-1.amazonaws.com/pstorage-acs-6854636/3727291/sc5b01163_si_001.pdf"
                }
            ],
            "modified": "2016-04-12",
            "references": [
                "https://doi.org/10.1021/acssuschemeng.5b01163"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Magnetically separable Fe3O4@DOPA\u2013Pd: a heterogeneous catalyst for aqueous Heck reaction",
            "description": "Magnetically separable Fe3O4@DOPA\u2013Pd catalyst has been synthesized via anchoring of palladium over dopamine-coated magnetite via co-ordinate interaction\r\nand the catalyst is utilized for expeditious Heck coupling in aqueous media. \n\nThis dataset is associated with the following publication:\nBaig, N., J. Leazer , and R. Varma. Magnetically Separable Fe3O4@DOPA-Pd: A Heterogeneous Catalyst for Aqueous Heck Reaction.   CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY. Springer-Verlag, New York, NY, USA, 17(7): 2073-2077, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-qc05-307",
            "keyword": [
                "Magnetically separable",
                "Heck reaction",
                "heterogeneous catalyst"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://link.springer.com/article/10.1007%2Fs10098-015-0914-0",
                    "accessURL": "https://link.springer.com/article/10.1007%2Fs10098-015-0914-0"
                }
            ],
            "modified": "2015-09-25",
            "references": [
                "https://doi.org/10.1007/s10098-015-0914-0"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Visible light mediated upgrading of biomass to biofuel",
            "description": "AgPd@g-C3N4, comprising heterogenized Ag and Pd\r\nnanoparticles on graphitic carbon nitride, g-C3N4, has been\r\nsynthesized and used for the upgrading of biofuel as exemplified\r\nby the hydrodeoxygenation of lignin-derived vanillin under\r\nphotochemical conditions using formic acid. The bimetallic\r\nframework is found to be highly active due to the synergistic\r\neffects of Ag and Pd with the graphitic carbon nitride support and\r\ntheir mutual interaction. \n\nThis dataset is associated with the following publication:\nVarma , R., M. Nadagouda , S. Verma, and R.B. Nasir Baig. Visible light mediated upgrading of biomass to biofuel.   Energy & Environmental Science. RSC Publishing, Cambridge,  UK, 18(5): 1327-1333, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-37q0-306",
            "keyword": [
                "Biomass upgrade",
                "Biofuel production",
                "Visible light",
                "Earth-abundant materials",
                "Sustainable materials management"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.rsc.org/suppdata/c5/gc/c5gc02951a/c5gc02951a1.pdf",
                    "accessURL": "https://www.rsc.org/suppdata/c5/gc/c5gc02951a/c5gc02951a1.pdf"
                }
            ],
            "modified": "2016-02-29",
            "references": [
                "https://doi.org/10.1039/c5gc02951a"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A photoactive bimetallic framework for direct aminoformylation of nitroarenes",
            "description": "A bimetallic catalyst, AgPd@g-C3N4, synthesized by reducing silver and palladium salts over graphitic carbon nitride (g-C3N4), enables the concerted reductive formylation of aromatic nitro compounds under photo-chemical conditions using formic acid, which serves the dual role of a hydrogen source and a formylating agent. \n\nThis dataset is associated with the following publication:\nBaig, R.B.N., S. Verma, M. Nadagouda , and R. Varma. A photoactive bimetallic framework for direct aminoformylation of nitroarenes.   GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge,  UK, 18(4): 1019-1022, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-37q0-321",
            "keyword": [
                "Aminoformylation",
                "Nitroarenes",
                "Bimetallic framework",
                "Earth-abundant materials",
                "Sustainable materials management"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.rsc.org/suppdata/c5/gc/c5gc02799c/c5gc02799c1.pdf",
                    "accessURL": "https://www.rsc.org/suppdata/c5/gc/c5gc02799c/c5gc02799c1.pdf"
                }
            ],
            "modified": "2016-02-16",
            "references": [
                "https://doi.org/10.1039/c5gc02799c"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Sustainable Strategy Utilizing Biomass: Visible-Light-Mediated Synthesis of gamma-Valerolactone",
            "description": "A novel sustainable approach to valued g-valerolactone was investigated.\r\nThis approach exploits the visible-light-mediated conversion of biomass-derived levulinic acid by using a bimetallic catalyst on a graphitic carbon nitride, AgPd@g-C3N4. \n\nThis dataset is associated with the following publication:\nVerma, S., R.B.N. Baig, M. Nadagouda , and R. Varma. Sustainable Strategy Utilizing Biomass: Visible-Light-Mediated Synthesis of \u03b3-Valerolactone.   ChemCatChem. Wiley-VCH, WEINHEIM,  GERMANY, 8(4): 872, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-37q0-322",
            "keyword": [
                "biomass \u00b7 heterogeneous catalysis \u00b7 levulinic acid \u00b7",
                "biomass",
                "Heterogeneous catalysis",
                "Levulinic acid",
                "Valerolactone",
                "Earth-abundant materials",
                "Sustainable materials management"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/cctc.201501352",
                    "accessURL": "https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/cctc.201501352"
                }
            ],
            "modified": "2016-04-06",
            "references": [
                "https://doi.org/10.1002/cctc.201501352"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Aerobic oxidation of alcohols in visible light on Pd-grafted Ti cluster",
            "description": "The titanium cluster with the reduced band gap has been synthesized having the palladium nanoparticles over the surface, which not only binds to the atmospheric oxygen but also catalyzes the oxidation of alcohols under visible light. \n\nThis dataset is associated with the following publication:\nVerma, S., R.B.N. Baig, M. Nadagouda, and R. Varma. Aerobic oxidation of alcohols in visible light on Pd-grafted Ti cluster.   TETRAHEDRON. Elsevier Science Ltd, New York, NY, USA, 73(38): 5577-5580, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-37q0-324",
            "keyword": [
                "Titanium cluster",
                "Heterogeneous catalysis",
                "Aerial oxidation",
                "Palladium nanoparticle",
                "Earth-abundant materials",
                "Sustainable materials management"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.sciencedirect.com/science/article/pii/S0040402016307281",
                    "accessURL": "https://www.sciencedirect.com/science/article/pii/S0040402016307281"
                }
            ],
            "modified": "2016-08-09",
            "references": [
                "https://doi.org/10.1016/j.tet.2016.07.070"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Photocatalytic C\u2212H Activation of Hydrocarbons over VO@g\u2011C3N4",
            "description": "A highly selective and sustainable method has been developed for the oxidation of methyl arenes and their analogues. The VO@g-C3N4 catalyst is very efficient in the C\u2212H activation and oxygen insertion reaction resulting in formation of the corresponding carbonyl compounds and phenols. \n\nThis dataset is associated with the following publication:\nVerma, S., R.B. Nasir Baig, M. Nadagouda , and R. Varma. Photocatalytic C\u00bfH Activation of Hydrocarbons over VO@g\u00bfC3N4.   ACS Sustainable Chemistry & Engineering. American Chemical Society, Washington, DC, USA, 4(4): 2333-2336, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-37q0-319",
            "keyword": [
                "C\u2212H activation",
                "Graphitic carbon nitride",
                "Photocatalyst",
                "Vanadium oxide",
                "Heterogeneous catalysis",
                "Earth-abundant materials",
                "Sustainable materials management"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://s3-eu-west-1.amazonaws.com/pstorage-acs-6854636/4817677/sc6b00006_si_001.pdf",
                    "accessURL": "https://s3-eu-west-1.amazonaws.com/pstorage-acs-6854636/4817677/sc6b00006_si_001.pdf"
                }
            ],
            "modified": "2016-04-08",
            "references": [
                "https://doi.org/10.1021/acssuschemeng.6b00006"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Magnetic Fe@g\u2011C3N4: A Photoactive Catalyst for the Hydrogenation of Alkenes and Alkynes",
            "description": "A photoactive catalyst, Fe@g-C3N4, has been developed for the hydrogenation of alkenes and alkynes using hydrazine hydrate as a source of hydrogen. The magnetically separable Fe@g-C3N4 eliminates the use of high pressure hydrogenation, and the reaction can be accomplished using visible light without the need for external sources of energy. \n\nThis dataset is associated with the following publication:\nBaig, N., S. Verma, R. Varma , and M. Nadagouda. Magnetic Fe@g-C3N4: A Photoactive Catalyst for the Hydrogenation of Alkenes and Alkynes.   ACS Sustainable Chemistry & Engineering. American Chemical Society, Washington, DC, USA, 4(3): 1661-1664, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-37q0-320",
            "keyword": [
                "Photocatalysis",
                "Hydrogenation",
                "Nanoferrite",
                "Graphitic carbon nitride",
                "Heterogeneous catalysis",
                "Earth-abundant materials",
                "Sustainable materials management"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://s3-eu-west-1.amazonaws.com/pstorage-acs-6854636/3709144/sc5b01610_si_001.pdf",
                    "accessURL": "https://s3-eu-west-1.amazonaws.com/pstorage-acs-6854636/3709144/sc5b01610_si_001.pdf"
                }
            ],
            "modified": "2016-04-12",
            "references": [
                "https://doi.org/10.1021/acssuschemeng.5b01610"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Titanium-based zeolitic imidazolate framework for chemical fixation of carbon dioxide",
            "description": "A titanium-based zeolitic imidazolate framework (Ti-ZIF) with high surface area and porous morphology has been synthesized and its application as a recyclable catalyst is demonstrated in the synthesis of cyclic carbonate via cycloaddition of carbon dioxide and epoxide in aqueous media. \n\nThis dataset is associated with the following publication:\nVarma, R., S. Verma, R.B.N. Baig, and M. Nadagouda. Titanium-based zeolitic imidazolate framework for chemical fixation of carbon dioxide.   GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge,  UK, 18: 4855-4858, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-37q0-323",
            "keyword": [
                "zeolitic imidazolate framework",
                "Chemical fixation",
                "carbon dioxide",
                "Earth-abundant materials",
                "Sustainable materials management"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.rsc.org/suppdata/c6/gc/c6gc01648k/c6gc01648k1.pdf",
                    "accessURL": "https://www.rsc.org/suppdata/c6/gc/c6gc01648k/c6gc01648k1.pdf"
                }
            ],
            "modified": "2016-09-12",
            "references": [
                "https://doi.org/10.1039/c6gc01648k"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Industrial Ecology Approach to MSW Methodology Data Set",
            "description": "U.S. municipal solid waste data for the year 2012. \n\nThis dataset is associated with the following publication:\nSmith , R., D. Sengupta, S. Takkellapati , and C. Lee. An industrial ecology approach to municipal solid wastemanagement: I. Methodology.   Resources, Conservation and Recycling. Elsevier Science BV, Amsterdam,  NETHERLANDS, 104: 311-316, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-wq05-109",
            "keyword": [
                "Industrial ecology",
                "MSW",
                "energy",
                "sustainability"
            ],
            "contactPoint": {
                "fn": "Raymond Smith",
                "hasEmail": "mailto:smith.raymond@epa.gov"
            },
            "distribution": [
                {
                    "title": "IndustrialEcologyApproachMSW Methodology DataSet.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/109/IndustrialEcologyApproachMSW%20Methodology%20DataSet.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-23",
            "references": [
                "https://doi.org/10.1016/j.resconrec.2015.04.005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "St. Louis River water quality assessment 2012, 2013",
            "description": "St. Louis River Area of Concern surface water nutrient (TP, TN, NOx-N, NH4-N), dissolved oxygen, and particulate (TSS, chlorophyll a) concentration data from 2012 and 2013 reported in Bellinger et al. 2016, Journal of Great Lakes Research 42:28-38. \n\nThis dataset is associated with the following publication:\nBellinger, B., J. Hoffman , T. Angradi , D. Bolgrien , M. Starry, C. Elonen , T. Jicha , L. Lehto, L. Seifert-Monson, M. Pearson , L. Anderson, and B. Hill. Water quality in the St. Louis River Area of Concern (AOC), Lake Superior: An historical perspective with assessment implications.   JOURNAL OF GREAT LAKES RESEARCH. International Association for Great Lakes Research, Ann Arbor, MI, USA, 42(1): 28-38, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-msbw-343",
            "keyword": [
                "nitrogen",
                "phosphorus",
                "total suspended solids",
                "chlorophyll a",
                "dissolved oxygen",
                "ecosystem services",
                "Area of Concern",
                "water quality",
                "monitoring and assessment",
                "Great Lakes"
            ],
            "contactPoint": {
                "fn": "Joel Hoffman",
                "hasEmail": "mailto:hoffman.joel@epa.gov"
            },
            "distribution": [
                {
                    "title": "HoffmanJoel_A-msbw_Dataset_20160916.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/343/HoffmanJoel_A-msbw_Dataset_20160916.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-08-01",
            "references": [
                "https://doi.org/10.1016/j.jglr.2015.11.008"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "SEQUENCING AND DE NOVO DRAFT ASSEMBLIES OF A FATHEAD MINNOW (Pimpehales promelas) reference genome",
            "description": "The dataset provides the URLs for accessing the genome sequence data and two draft assemblies as well as fathead minnow genotyping data associated with estimating the heterozygosity of the in-bred line. \n\nThis dataset is associated with the following publication:\nBurns, F., L. Cogburn, G. Ankley , D. Villeneuve , E. Waits , Y. Chang, V. Llaca, S. Deschamps, R. Jackson, and R. Hoke. Sequencing and De novo Draft Assemblies of the Fathead Minnow (Pimphales promelas)Reference Genome.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 35(1): 212-217, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-thtw-349",
            "keyword": [
                "genome",
                "pathfinder innovation project",
                "adverse outcome pathway",
                "computational toxicology",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.ncbi.nlm.nih.gov/nuccore/JNCD00000000",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/nuccore/JNCD00000000"
                },
                {
                    "title": "https://www.ncbi.nlm.nih.gov/assembly?LinkName=nuccore_assembly&from_uid=650319607",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/assembly?LinkName=nuccore_assembly&from_uid=650319607"
                },
                {
                    "title": "https://www.ncbi.nlm.nih.gov/assembly/GCA_000700965.1/",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/assembly/GCA_000700965.1/"
                },
                {
                    "title": "FHM Diversity Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/349/FHM%20Diversity%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-06-10",
            "references": [
                "https://doi.org/10.1002/etc.3186"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Farraj_NO2-O3 Sequential exposure study_All data",
            "description": "Cardiovascular Physiologic and Systemic Responses to Sequential Exposure to Nitrogen Dioxide and Ozone in Rats. \n\nThis dataset is associated with the following publication:\nFarraj , A., F. Malik, N. Coates , L. Walsh , D. Winsett , D. Terrell , L. Thompson, W. Cascio , and M. Hazari. Morning NO2 Exposure Sensitizes Hypertensive Rats to the Cardiovascular Effects of Same Day O3 Exposure in the Afternoon.   INHALATION TOXICOLOGY. Informa Healthcare USA, New York, NY, USA, 28(4): 170-179, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-3xsn-235",
            "keyword": [
                "Ozone",
                "nitrogen dioxide",
                "air pollution",
                "blood pressure",
                "electrocardiogram",
                "heart rate",
                "contractility",
                "heart rate variability",
                "Rats",
                "morning",
                "afternoon",
                "priming effects",
                "sequential",
                "autonomic nervous system",
                "cardiovascular"
            ],
            "contactPoint": {
                "fn": "Aimen Farraj",
                "hasEmail": "mailto:farraj.aimen@epa.gov"
            },
            "distribution": [
                {
                    "title": "AF13_NO2-O3 Sequential exposure study_All data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/235/AF13_NO2-O3%20Sequential%20exposure%20study_All%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-24",
            "references": [
                "https://doi.org/10.3109/08958378.2016.1148088"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Land use and beach closure 2004-2013 in the United States",
            "description": "The dataset contains the beach closure data and land use information around each beach in 2006 and 2011 in the United States. The original data are created by EPA and USGS and publicly available (the links are provided). \n\nThis dataset is associated with the following publication:\nWu, J., and L. Jackson. Association of land use and its change with beach closure in the United States, 2004-2013.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 571: 67-76, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-ns28-90",
            "keyword": [
                "The number of beach closure",
                "land use",
                "hydrologic unit",
                "2006",
                "2011",
                "United States",
                "2 km",
                "5 km",
                "10 km",
                "beach water quality",
                "land cover",
                "land use change",
                "urbanization",
                "ecosystem health"
            ],
            "contactPoint": {
                "fn": "Jianyong Wu",
                "hasEmail": "mailto:wu.jianyong@epa.gov"
            },
            "distribution": [
                {
                    "title": "Beach closure and land use dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/90/Beach%20closure%20and%20land%20use%20dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://watersgeo.epa.gov/beacon2/",
                    "accessURL": "https://watersgeo.epa.gov/beacon2/"
                },
                {
                    "title": "https://nhd.usgs.gov/data.html",
                    "accessURL": "https://nhd.usgs.gov/data.html"
                },
                {
                    "title": "https://www.mrlc.gov/data",
                    "accessURL": "https://www.mrlc.gov/data"
                }
            ],
            "modified": "2016-05-31",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.07.116"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/90/documents/Data%20dictonary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "ORD-017311_Data_Brown_DermPerm.xlsx",
            "description": "List of chemicals used for model evaluation, their MW, log KOW, and references for the original data source(s), the review(s) the data was collected from, and reference for log KOW as cited in the reviews. [Table SI-3 of research article]. \n\nThis dataset is associated with the following publication:\nBrown, T., J. Armitage, P. Egeghy, I. Kircanski, and J. Arnot. Dermal permeation data and models for the prioritization and screening-level exposure assessment of organic chemicals.   ENVIRONMENT INTERNATIONAL. Elsevier Science Ltd, New York, NY, USA, 94: 424-435, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-9s4x-288",
            "keyword": [
                "octanol-water partition coefficient",
                "molecular weight",
                "Human Exposure Assessment",
                "Dermal Permeation",
                "Quantitative Structure-Activity Relationship",
                "Skin Permeability Coefficient",
                "Permeation Database",
                "ExpoCast"
            ],
            "contactPoint": {
                "fn": "Peter Egeghy",
                "hasEmail": "mailto:egeghy.peter@epa.gov"
            },
            "distribution": [
                {
                    "title": "ORD-017311_Data_Brown_DermPerm.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/288/ORD-017311_Data_Brown_DermPerm.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-05-20",
            "references": [
                "http://www.sciencedirect.com/science/article/pii/S0160412016302094"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Modeling Tribal Exposures to Methyl Mercury from Fish Consumption ",
            "description": "data is from NHANES study and EPA fish intake and HG concentration in fish tissue. \n\nThis dataset is associated with the following publication:\nXue , J., V. Zartarian , B. Mintz , M. Weber , K. Bailey , and A. Geller. Modeling tribal exposures to methyl mercury from fish consumption.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 533: 102-109, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-5dv8-206",
            "keyword": [
                "mercury",
                "tribal",
                "fish consumption",
                "exposures",
                "SHEDS-Dietary"
            ],
            "contactPoint": {
                "fn": "Jianping Xue",
                "hasEmail": "mailto:xue.jianping@epa.gov"
            },
            "distribution": [
                {
                    "title": "tribal fish HG paper data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/206/tribal%20fish%20HG%20paper%20data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2015-03-04",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2015.06.070"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "EPA True NO2 ground site measurements \u2013 multiple sites, TCEQ ground site measurements of meteorological and air pollution parameters \u2013 multiple sites ,GeoTASO NO2 Vertical Column ",
            "description": "EPA True NO2 ground site measurements \u2013 multiple sites - http://www-air.larc.nasa.gov/cgi-bin/ArcView/discover-aq.tx-2013; TCEQ ground site measurements of meteorological and air pollution parameters \u2013 multiple sites - http://www-air.larc.nasa.gov/cgi-bin/ArcView/discover-aq.tx-2013; GeoTASO NO2 Vertical Column - http://www-air.larc.nasa.gov/cgi-bin/ArcView/discover-aq.tx-2013?FALCON=1. \n\nThis dataset is associated with the following publication:\nNowlan, C., X. Lu, J. Leitch, K. Chance, G. Gonz\u00e1lez Abad, C. Lu, P. Zoogman, J. Cole, T. Delker, W. Good, F. Murcray, L. Ruppert, D. Soo, M. Follette-Cook, S. Janz, M. Kowalewski, C. Loughner, K. Pickering, J. Herman, M. Beaver, R. Long, J. Szykman, L. Judd, P. Kelley, W. Luke, X. Ren, and J. Al-Saadi. Nitrogen dioxide observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument: Retrieval algorithm and measurements during DISCOVER-AQ Texas 2013.   Atmospheric Measurement Techniques. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 9(6): 2647-2668, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-8pk8-342",
            "keyword": [
                "nitrogen dioxide",
                "column density",
                "air quality from space",
                "GeoTASO",
                "True NO2"
            ],
            "contactPoint": {
                "fn": "James Szykman",
                "hasEmail": "mailto:szykman.jim@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www-air.larc.nasa.gov/cgi-bin/ArcView/discover-aq.tx-2013",
                    "accessURL": "https://www-air.larc.nasa.gov/cgi-bin/ArcView/discover-aq.tx-2013"
                },
                {
                    "title": "https://www-air.larc.nasa.gov/cgi-bin/ArcView/discover-aq.tx-2013?FALCON=1",
                    "accessURL": "https://www-air.larc.nasa.gov/cgi-bin/ArcView/discover-aq.tx-2013?FALCON=1"
                }
            ],
            "modified": "2016-09-16",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://www-air.larc.nasa.gov/cgi-bin/ArcView/discover-aq.tx-2013",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "GADEP Continuous PM2.5 mass concentration data, VIIRS Day Night Band SDR (SVDNB), MODIS Terra Level 2 water vapor profiles (infrared algorithm for atmospheric profiles for both day and night, NWS surface meteorological data",
            "description": "Data descriptions are provided at the following urls:\nGADEP Continuous PM2.5 mass concentration data - https://aqs.epa.gov/aqsweb/documents/data_mart_welcome.html\nhttps://www3.epa.gov/ttn/amtic/files/ambient/pm25/qa/QA-Handbook-Vol-II.pdf\n\nVIIRS Day Night Band SDR (SVDNB) http://www.class.ngdc.noaa.gov/saa/products/search?datatype_family=VIIRS_SDR\n\nMODIS Terra Level 2 water vapor profiles (infrared algorithm for atmospheric profiles for both day and night -MOD0&_L2;  http://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html \n\nNWS surface meteorological data - https://www.ncdc.noaa.gov/isd. \n\nThis dataset is associated with the following publication:\nWang, J., C. Aegerter, and J. Szykman. Potential Application of VIIRS Day/Night Band for Monitoring Nighttime Surface PM2.5 Air Quality From Space.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 124(0): 55-63, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-4j14-348",
            "keyword": [
                "Suomi National Polar-orbiting Partnership (S-NPP) satellite",
                "Visible Infrared Imaging Radiometer Suite (VIIRS)",
                "day-night band (DNB)",
                "particulate matter (PM)",
                "air quality monitoring at night"
            ],
            "contactPoint": {
                "fn": "James Szykman",
                "hasEmail": "mailto:szykman.jim@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://aqs.epa.gov/aqsweb/documents/data_mart_welcome.html",
                    "accessURL": "https://aqs.epa.gov/aqsweb/documents/data_mart_welcome.html"
                },
                {
                    "title": "https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html",
                    "accessURL": "https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html"
                },
                {
                    "title": "https://www.ncdc.noaa.gov/isd",
                    "accessURL": "https://www.ncdc.noaa.gov/isd"
                },
                {
                    "title": "https://eogdata.mines.edu/products/vnl/",
                    "accessURL": "https://eogdata.mines.edu/products/vnl/"
                }
            ],
            "modified": "2016-09-19",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Hance_WestForkSmithRiver_flasher_location_data",
            "description": "This entry contains two files.  The first file, \"Hance_WFSR Flasher locations.xlxs\", contains information describing the location of installed landmark 'flashers' consisting of 2\" square aluminum metal tags.  Each tag was inscribed with a number to aid field personnel in the identification of landmark location within the West Fork Smith River watershed in southern coastal Oregon. These landmarks were used to calculate stream distances between points in the watershed, including distances between tagging locations and detection events for tagged fish. \n\nA second file, named \"Hance_fish_detection_data1.xlxs\" contains information on the detection of tagged fish within the West Fork Smith River stream network.  The file includes both the location where the fish were tagged and where they were subsequently detected.  Together with the information in the WFSR flasher location dataset, these data allow estimation of the minimum distances and directions moved by juvenile coho salmon during the fall transition period.\n\nA map locator is provided in Figure 1 in the accompanying manuscript: Dalton J. Hance, Lisa M. Ganio, Kelly M. Burnett & Joseph L. Ebersole (2016) Basin-Scale Variation in the Spatial Pattern of Fall Movement of Juvenile Coho Salmon in the West Fork Smith River, Oregon, Transactions of the American Fisheries Society, 145:5, 1018-1034, DOI: 10.1080/00028487.2016.1194892\". \n\nThis dataset is associated with the following publication:\nHance, D.J., L.M. Ganio, K.M. Burnett, and J. Ebersole. Basin-Scale Variation in the Spatial Pattern of Fall Movement of Juvenile Coho Salmon in the West Fork Smith River, Oregon.   TRANSACTIONS OF THE AMERICAN FISHERIES SOCIETY. American Fisheries Society, Bethesda, MD, USA, 5(145): 1018-1034, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-fqzj-326",
            "keyword": [
                "Salmon"
            ],
            "contactPoint": {
                "fn": "Joseph Ebersole",
                "hasEmail": "mailto:ebersole.joe@epa.gov"
            },
            "distribution": [
                {
                    "title": "Hance_WFSR flasher locations.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/326/Hance_WFSR%20flasher%20locations.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Hance_fish_detection_data1.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/326/Hance_fish_detection_data1.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-14",
            "references": [
                "https://doi.org/10.1080/00028487.2016.1194892"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "National Aquatic Resource Survey Rivers and Streams Data",
            "description": "Data are from 1,000 river and stream sites across the conterminous US where consistent biological, chemical, physical and watershed data were gathered.  The sites were selected using a probability survey design so that the results provide inferences to all perennial flowing waters in the lower 48 states. \n\nThis dataset is associated with the following publication:\nOmernik, J., S. Paulsen , M. Weber , and G. Griffith. Regional patterns of total nitrogen concentrations in the National Rivers and Streams Assessment.   JOURNAL OF SOIL AND WATER CONSERVATION. Soil and Water Conservation Society,    71(3): 167-181, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-7d84-341",
            "keyword": [
                "nutrients",
                "water quality",
                "Environmental sampling",
                "ecoregions",
                "nitrogen",
                "watersheds"
            ],
            "contactPoint": {
                "fn": "Steven Paulsen",
                "hasEmail": "mailto:paulsen.steve@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys"
                }
            ],
            "modified": "2016-08-01",
            "references": [
                "https://doi.org/10.2489/jswc.71.3.167"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "National Aquatic Resource Survey data",
            "description": "Surface water monitoring data from national aquatic surveys (lakes, streams, rivers). \n\nThis dataset is associated with the following publication:\nStoddard , J., J. Van Sickle, A. Herlihy, J. Brahney, S. Paulsen , D. Peck , R. Mitchell , and A. Pollard. Continental-scale increase in stream and lake phosphorus: Are oligotrophic systems disappearing in the U.S.?.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(7): 3409-3415, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-5x6h-325",
            "keyword": [
                "phosphorus",
                "lakes",
                "streams",
                "monitoring",
                "trends"
            ],
            "contactPoint": {
                "fn": "John Stoddard",
                "hasEmail": "mailto:stoddard.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys"
                }
            ],
            "modified": "2016-09-14",
            "references": [
                "https://doi.org/10.1021/acs.est.5b05950"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Nitrous Oxide flux measurements under various amendments",
            "description": "The dataset consists of measurements of soil nitrous oxide emissions from soils under three different amendments: glucose, cellulose, and manure. Data includes the four isotopomers of nitrous oxide (14N15N16O, 15N14N16O, 14N14N18O, 14N14N16O), and the site preference. \n\nThis dataset is associated with the following publication:\nChen , H., D. Williams , P. Deshmukh , F. Birgand, B. Maxwell, and J. Walker. Probing the Biological Sources of Soil N2O Emissions by Quantum Cascade Laser-Based 15N Isotopocule Analysis.   SOIL SCIENCE SOCIETY OF AMERICA JOURNAL. Soil Science Society of America, Madison, WI, USA, 100(0): 175-181, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-9p8p-365",
            "keyword": [
                "site preference",
                "nitrous oxide",
                "crop agriculture",
                "stable isotopes"
            ],
            "contactPoint": {
                "fn": "David Williams",
                "hasEmail": "mailto:williams.davidj@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data for Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/365/Data%20for%20Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Calibration_June.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/365/Calibration_June.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Calibration_May.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/365/Calibration_May.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-21",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/365/documents/Data%20Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": " Sorption of Radionuclides to Building Materials and its Removal Using Simple Wash Solutions",
            "description": "Data corresponding to the figures in the paper. \n\nThis dataset is associated with the following publication:\nKaminski, M., C. Mertz, L. Ortega, and N. Kivenas. Sorption of Radionuclides to Building Materials and its Removal Using Simple Wash Solutions.   Journal of Environmental Chemical Engineering. Elsevier B.V., Amsterdam,  NETHERLANDS,  ., (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "A-t1gn-310",
            "keyword": [
                "Decontamination",
                "remediation",
                "radioactive contamination",
                "Ammonium",
                "Cesium-137",
                "Concrete",
                "dirty bomb",
                "radiological disperal device",
                "nuclear power plant"
            ],
            "contactPoint": {
                "fn": "Matthew Magnuson",
                "hasEmail": "mailto:magnuson.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data for A-t1gn.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/310/Data%20for%20A-t1gn.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2012-01-01",
            "references": [
                "https://doi.org/10.1016/j.jece.2016.02.004"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Wide-Area Decontamination in an Urban Environment after Radiological Dispersion: A Review and Perspectives",
            "description": "This is a literature review, so contains no original data. This dataset is not publicly accessible because: This paper is a literature review and contains no data. It can be accessed through the following means: This paper is a literature review and contains no data.  The paper contains the literature reviewed. Format: This paper is a literature review and contains no data. \n\nThis dataset is associated with the following publication:\nKaminski, M., S. Lee , and M. Magnuson. Wide-Area Decontamination in an Urban Environment after Radiological Dispersion:  A Review and Perspectives.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 305: 67-86, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "A-2ngh-311",
            "keyword": [
                "remediation",
                "nuclear fallout",
                "radioactive contamination",
                "Contamination",
                "Decontamination",
                "nuclear power plant"
            ],
            "contactPoint": {
                "fn": "Matthew Magnuson",
                "hasEmail": "mailto:magnuson.matthew@epa.gov"
            },
            "distribution": [],
            "modified": "2015-11-06",
            "references": [
                "https://doi.org/10.1016/j.jhazmat.2015.11.014"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Pulsed and Continuous UV LED Reactor for Water Treatment",
            "description": "Numerical data represented in the figures which are graphs. \n\nThis dataset is associated with the following publication:\nSpencer, M., M. Miller, J. Richwine, K. Duckworth, L. Racz, M. Grimaila, M. Magnuson , S. Willison , and R. Phillips. Pulsed and Continuous UV LED Reactor for Water Treatment.   Aqua - Journal of Water Supply Research and Technology, International Water Supply Association (London, England). Blackwell Publishing, Malden, MA, USA,  1-75, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "A-sn0q-317",
            "keyword": [
                "Ultraviolet",
                "advanced oxidation process",
                "light emitting diode",
                "reactor design"
            ],
            "contactPoint": {
                "fn": "Matthew Magnuson",
                "hasEmail": "mailto:magnuson.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Dataset for sn0q.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/317/Dataset%20for%20sn0q.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-10-01",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Chemical agent recoveries",
            "description": "Dataset shows the calculation of reported decontamination efficacies from the raw data (i.e., measured amount of chemical recovered from test coupons and positive controls) to actual decontamination efficacy for all chemicals and decontaminants. \n\nThis dataset is associated with the following publication:\nOudejans , L., J. O'Kelly, A. Evans, B. Barbara Wyrzykowska-Ceradini, A. Toauati, D. Tabor , and E. Snyder. Efficacy of decontaminant solutions for remediation on TICs on PPE materials.   JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, USA,  1-5, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-8sfg-217",
            "keyword": [
                "Decontamination",
                "efficacy",
                "PPE",
                "decontamination line",
                "doffing",
                "toxic industrial chemical",
                "chemical warfare agent"
            ],
            "contactPoint": {
                "fn": "Lukas Oudejans",
                "hasEmail": "mailto:oudejans.lukas@epa.gov"
            },
            "distribution": [
                {
                    "title": "Recovery data PPE decon w TICs.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/217/Recovery%20data%20PPE%20decon%20w%20TICs.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-20",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Diurnal Ensemble Surface Meteorology Statistics",
            "description": "Excel file containing diurnal ensemble statistics of 2-m temperature, 2-m mixing ratio and 10-m wind speed. This Excel file contains figures for Figure 2 in the paper and worksheets containing all statistics for the 14 members of the ensemble and a base simulation. \n\nThis dataset is associated with the following publication:\nGilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259\u201312,280, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-6q5f-369",
            "keyword": [
                "ensemble modeling",
                "surface meteorology statistics",
                "Figure 2",
                "2-m temperature",
                "2-m mixing ratio",
                "10-m wind speed",
                "RMSE",
                "NAM",
                "SREF",
                "probabilistic modeling",
                "WRF-CMAQ",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Robert Gilliam",
                "hasEmail": "mailto:gilliam.robert@epa.gov"
            },
            "distribution": [
                {
                    "title": "ENS_WRF_Stats_June2011.V2.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/369/ENS_WRF_Stats_June2011.V2.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2012-11-15",
            "references": [
                "https://doi.org/10.1002/2015jd023674"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Linking high resolution mass spectrometry data with exposure and toxicity forecasts to advance high-throughput environmental monitoring",
            "description": "There is a growing need in the field of exposure science for monitoring methods that rapidly screen environmental media for suspect contaminants. Measurement and analysis platforms, based on high resolution mass spectrometry (HRMS), now exist to meet this need. Here we describe results of a study that links HRMS data with exposure predictions from the U.S. EPA's ExpoCast\u2122 program and in vitro bioassay data from the U.S. interagency Tox21 consortium. Vacuum dust samples were collected from 56 households across the U.S. as part of the American Healthy Homes Survey (AHHS). Sample extracts were analyzed using liquid chromatography time-of-flight mass spectrometry (LC\u2013TOF/MS) with electrospray ionization. On average, approximately 2000 molecular features were identified per sample (based on accurate mass) in negative ion mode, and 3000 in positive ion mode. Exact mass, isotope distribution, and isotope spacing were used to match molecular features with a unique listing of chemical formulas extracted from EPA's Distributed Structure-Searchable Toxicity (DSSTox) database. A total of 978 DSSTox formulas were consistent with the dust LC\u2013TOF/molecular feature data (match score \u2265 90); these formulas mapped to 3228 possible chemicals in the database. Correct assignment of a unique chemical to a given formula required additional validation steps. Each suspect chemical was prioritized for follow-up confirmation using abundance and detection frequency results, along with exposure and bioactivity estimates from ExpoCast and Tox21, respectively. Chemicals with elevated exposure and/or toxicity potential were further examined using a mixture of 100 chemical standards. A total of 33 chemicals were confirmed present in the dust samples by formula and retention time match; nearly half of these do not appear to have been associated with house dust in the published literature. Chemical matches found in at least 10 of the 56 dust samples include Piperine, N,N-Diethyl-m-toluamide (DEET), Triclocarban, Diethyl phthalate (DEP), Propylparaben, Methylparaben, Tris(1,3-dichloro-2-propyl)phosphate (TDCPP), and Nicotine. This study demonstrates a novel suspect screening methodology to prioritize chemicals of interest for subsequent targeted analysis. The methods described here rely on strategic integration of available public resources and should be considered in future non-targeted and suspect screening assessments of environmental and biological media. \n\nThis dataset is associated with the following publication:\nRager, J.E., M. Strynar , S. Liang, R.L. McMahen, A. Richard , C.M. Grukle, J. Wambaugh , K. Isaacs , R. Judson , A. Williams , and J. Sobus. Linking high resolution mass spectrometry data with exposure and toxicity forecasts to advance high-throughput environmental monitoring.   ENVIRONMENT INTERNATIONAL. Elsevier Science Ltd, New York, NY, USA, 88: 269-280, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-dbs5-231",
            "keyword": [
                "Non-targeted; Suspect screening; Exposome; ExpoCast; ToxCast; Dust"
            ],
            "contactPoint": {
                "fn": "Jon Sobus",
                "hasEmail": "mailto:sobus.jon@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.sciencedirect.com/science/article/pii/S0160412015301112",
                    "accessURL": "https://www.sciencedirect.com/science/article/pii/S0160412015301112"
                }
            ],
            "modified": "2015-12-15",
            "references": [
                "https://doi.org/10.1016/j.envint.2015.12.008"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Biomarker analysis of liver cells exposed to surfactant-wrapped and oxidized multi-walled carbon nanotubes (MWCNTs)",
            "description": "Carbon nanotubes (CNTs) have great potential in industrial, consumer, and mechanical applications, based partly on their unique structural, optical and electronic properties. CNTs are commonly oxidized or treated with surfactants to facilitate aqueous solution processing, and these CNT surface modifications also increase possible human and ecological exposures to nanoparticle-contaminated waters. To determine the exposure outcomes of oxidized and surfactant-wrapped multiwalled carbon nanotubes (MWCNTs) on biochemical processes, metabolomics based profiling of human liver cells (C3A) was utilized. Cells were exposed to 0, 10, or 100 ng/mL of MWCNTs for 24 and 48 hr. MWCNT particle size distribution, charge, and aggregation were monitored concurrently during exposures. Following MWCNT exposure, cellular metabolites were extracted, lyophilized, and buffered for 1H NMR analysis. Acquired spectra were subjected to both multivariate and univariate analysis to determine the consequences of nanotube exposure on the metabolite profile of C3A cells. Resulting scores plots illustrated temporal and dose-dependent metabolite responses to all MWCNTs tested. Loadings plots coupled with t-test filtered spectra identified metabolites of interest. XPS analysis revealed the presence of hydroxyl and carboxyl functionalities on both MWCNTs surfaces. Metal content analysis by ICP-AES indicated that the total mass concentration of the potentially toxic impurities in the exposure experiments were extremely low (i.e. [Ni] \u2264 2 \u00d7 10\u221210 g/mL). Preliminary data suggested that MWCNT exposure causes perturbations in biochemical processes involved in cellular oxidation as well as fluxes in amino acid metabolism and fatty acid synthesis. Dose-response trajectories were apparent and spectral peaks related to both dose and MWCNT dispersion methodologies were determined. Correlations of the significant changes in metabolites will help to identify potential biomarkers associated with carbonaceous nanoparticle exposure. \n\nThis dataset is associated with the following publication:\nHenderson, M., D. Bouchard, X. Chang, S. Al-Abed, and Q. Teng. Biomarker analysis of liver cells exposed to surfactant-wrapped and oxidized multi-walled carbon nanotubes (MWCNTs).   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 565: 777\u2013786, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-j104-344",
            "keyword": [
                "carbon nanoparticles",
                "carbon nanotubes",
                "biomarker profiling",
                "metabolomics",
                "ecotoxicity"
            ],
            "contactPoint": {
                "fn": "William Henderson",
                "hasEmail": "mailto:henderson.matt@epa.gov"
            },
            "distribution": [
                {
                    "title": "ohmwntc3a24hr.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/344/ohmwntc3a24hr.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "ohmwntc3a48hr.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/344/ohmwntc3a48hr.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "sdsmwntc3a24h.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/344/sdsmwntc3a24h.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "sdsmwntc3a48hr.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/344/sdsmwntc3a48hr.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2015-12-04",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.05.025"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/344/documents/HendersonWilliam_A-j104_DataDictionary_20160916.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Anaerobic Toxicity of Cationic Silver Nanoparticles",
            "description": "Toxicity data for the impact of nano-silver on anaerobic degradation. \n\nThis dataset is associated with the following publication:\nGitipour, A., S. Thiel, K. Scheckel, and T. Tolaymat. Anaerobic Toxicity of Cationic Silver Nanoparticles.  D. Barcelo Culleres, and J. Gan  SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 557: 363-368, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-p5j7-301",
            "keyword": [
                "Nanoparticles",
                "Silver",
                "toxicity",
                "cationic",
                "anaerobic"
            ],
            "contactPoint": {
                "fn": "Thabet Tolaymat",
                "hasEmail": "mailto:tolaymat.thabet@epa.gov"
            },
            "distribution": [
                {
                    "title": "AN.TOX (data).xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/301/AN.TOX%20%28data%29.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-12-25",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.02.190"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Molecular Detection of Legionella spp. and their associations with Mycobacterium spp., Pseudomonas aeruginosa and amoeba hosts in a drinking water distribution system ",
            "description": "Quantity of Legionella spp., Mycobacterium spp., Acanthamoeba,Vermamoeba vermiformis and Pseudomonas aeruginosa were estimated using qPCR methods. \n\nThis dataset is associated with the following publication:\nLu , J., I. Struewing, E. Vereen, A.E. Kirby, K. Levy, C. Moe, and N. Ashbolt. Molecular detection of Legionella spp. and their associations with Mycobacterium spp., Pseudomonas aeruginosa and amoeba hosts in a drinking water distribution system (Journal Article).   JOURNAL OF APPLIED MICROBIOLOGY. Blackwell Publishing, Malden, MA, USA, 120(2): 509-521, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-rv1r-292",
            "keyword": [
                "legionella",
                "opportunistic parthogens",
                "Drinking water distribution system",
                "qPCR",
                "opportunistic pathogen",
                "drinking water",
                "molecular detection",
                "sequence"
            ],
            "contactPoint": {
                "fn": "Jingrang Lu",
                "hasEmail": "mailto:lu.jingrang@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data dictionary_LegionellaDistributionSystem JAM.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/292/Data%20dictionary_LegionellaDistributionSystem%20JAM.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "DataSet_LegionellaDistributionSystem JAM.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/292/DataSet_LegionellaDistributionSystem%20JAM.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-09",
            "references": [
                "https://doi.org/10.1111/jam.12996"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CERAPP: Collaborative Estrogen Receptor Activity Prediction Project",
            "description": "Data from a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) demonstrating using predictive computational models on high-throughput screening data to screen thousands of chemicals against the estrogen receptor. \n\nThis dataset is associated with the following publication:\nMansouri , K., A. Abdelaziz, A. Rybacka, A. Roncaglioni, A. Tropsha, A. Varnek, A. Zakharov, A. Worth, A. Richard , C. Grulke , D. Trisciuzzi, D. Fourches, D. Horvath, E. Benfenati , E. Muratov, E.B. Wedebye, F. Grisoni, G.F. Mangiatordi, G.M. Incisivo, H. Hong, H.W. Ng, I.V. Tetko, I. Balabin, J. Kancherla , J. Shen, J. Burton, M. Nicklaus, M. Cassotti, N.G. Nikolov, O. Nicolotti, P.L. Andersson, Q. Zang, R. Politi, R.D. Beger , R. Todeschini, R. Huang, S. Farag, S.A. Rosenberg, S. Slavov, X. Hu, and R. Judson. (Environmental Health Perspectives)  CERAPP: Collaborative Estrogen Receptor Activity Prediction Project.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA,  1-49, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-6t1n-312",
            "keyword": [
                "qsar",
                "endocrine disruption",
                "estrogen receptor",
                "ToxCast",
                "DSSTox",
                "Chemistry Dashboard",
                "Read Across"
            ],
            "contactPoint": {
                "fn": "Ann Richard",
                "hasEmail": "mailto:richard.ann@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/Sustainable_Chemistry_Data/CERAPP_QSAR_Models/",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/Sustainable_Chemistry_Data/CERAPP_QSAR_Models/"
                }
            ],
            "modified": "2016-07-01",
            "references": [
                "https://doi.org/10.1289/ehp.1510267"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Evaluation of food-relevant chemicals in the ToxCast high-throughput screening program",
            "description": "Thousands of chemicals are directly added to or come in contact with food, many of which have undergone little to no toxicological evaluation. The landscape of the food-relevant chemical universe was evaluated using cheminformatics, and subsequently the bioactivity of food-relevant chemicals across the publicly available ToxCast highthroughput screening program was assessed. In total, 8659 food-relevant chemicals were compiled including direct food additives, food contact substances, and pesticides. Of these food-relevant chemicals, 4719 had curated structure definition files amenable to defining chemical fingerprints, which were used to cluster chemicals using a selforganizing map approach. Pesticides, and direct food additives clustered apart from one another with food contact substances generally in between, supporting that these categories not only reflect different uses but also distinct chemistries. Subsequently, 1530 food-relevant chemicals were identified in ToxCast comprising 616 direct food additives, 371 food contact substances, and 543 pesticides. Bioactivity across ToxCast was filtered for cytotoxicity to identify selective chemical effects. Initiating analyses from strictly chemical-based methodology or bioactivity/cytotoxicity-driven evaluation presents unbiased approaches for prioritizing chemicals. Although bioactivity in vitro is not necessarily predictive of adverse effects in vivo, these data provide insight into chemical properties and cellular targets through which foodrelevant chemicals elicit bioactivity. \n\nThis dataset is associated with the following publication:\nKarmaus , A., D. Filer , M. Martin , and K. Houck. (FOOD AND CHEMICAL TOXICOLOGY) Evaluation of food-relevant chemicals in the ToxCast high-throughput screening program.   FOOD AND CHEMICAL TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 92: 188-196, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-x0kx-328",
            "keyword": [
                "food additive",
                "food contact substance",
                "high-throughput screening",
                "pesticide",
                "chemical safety for sustainablity",
                "chemical safety research",
                "high-throughput toxicology",
                "ToxCast",
                "computational toxicology"
            ],
            "contactPoint": {
                "fn": "Keith Houck",
                "hasEmail": "mailto:houck.keith@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/Houck_Karmaus/ToxCast_Food_Relevant/",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/Houck_Karmaus/ToxCast_Food_Relevant/"
                }
            ],
            "modified": "2016-06-30",
            "references": [
                "https://doi.org/10.1016/j.fct.2016.04.012"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Systems Toxicology of Male Reproductive Development: Profiling 774 Chemicals for Molecular Targets and Adverse Outcomes",
            "description": "Background: Trends in male reproductive health have been reported for increased rates of testicular germ cell tumors, low semen quality, cryptorchidism, and hypospadias, which have been associated with prenatal environmental chemical exposure based on human and animal studies.\n\nObjective: In the present study we aimed to identify significant correlations between environmental chemicals, molecular targets, and adverse outcomes across a broad chemical landscape with emphasis on developmental toxicity of the male reproductive system.\n\nMethods: We used U.S. EPA\u2019s animal study database (ToxRefDB) and a comprehensive literature analysis to identify 774 chemicals that have been evaluated for adverse effects on male reproductive parameters, and then used U.S. EPA\u2019s in vitro high-throughput screening (HTS) database (ToxCastDB) to profile their bioactivity across approximately 800 molecular and cellular features. \n\nResults: A phenotypic hierarchy of testicular atrophy, sperm effects, tumors, and malformations, a composite resembling the human testicular dysgenesis syndrome (TDS) hypothesis, was observed in 281 chemicals. A subset of 54 chemicals with male developmental consequences had in vitro bioactivity on molecular targets that could be condensed into 156 gene annotations in a bipartite network. \n\nConclusion: Computational modeling of available in vivo and in vitro data for chemicals that produce adverse effects on male reproductive end points revealed a phenotypic hierarchy across animal studies consistent with the human TDS hypothesis. We confirmed the known role of estrogen and androgen signaling pathways in rodent TDS, and importantly, broadened the list of molecular targets to include retinoic acid signaling, vascular remodeling proteins, G-protein coupled receptors (GPCRs), and cytochrome P450s. \n\nThis dataset is associated with the following publication:\nLeung , M., J. Phuong , N. Baker , N. Sipes , G. Klinefelter , M. Martin , K. McLaurin, W. Setzer , S. Darney , R. Judson , and T. Knudsen. (ENVIRONMENTAL HEALTH PERSPECTIVES) Systems Toxicology of Male Reproductive Development: Profiling 774 Chemicals for Molecular Targets and Adverse Outcomes.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA,  1-47, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-dncw-331",
            "keyword": [
                "Reproductive effects",
                "Children's Environmental Health",
                "virtual embryo",
                "virtual tissues",
                "virtual liver",
                "tipping points"
            ],
            "contactPoint": {
                "fn": "Thomas Knudsen",
                "hasEmail": "mailto:knudsen.thomas@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/Knudsen/Virtual_Tissues_Male_Repro_Tox/Leung%20et%20al.%202016_EHP/",
                    "accessURL": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/Knudsen/Virtual_Tissues_Male_Repro_Tox/Leung%20et%20al.%202016_EHP/"
                }
            ],
            "modified": "2016-07-01",
            "references": [
                "https://doi.org/10.1289/ehp.1510385"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "In vivo and In vitro neurochemical-based assessments of wastewater effluents from the Maumee River area of concern.",
            "description": "All primary data reported in this paper were generated by non-federal collaborators from the University of Michigan and McGill University. US EPA-ORD personnel collected and supplied water, sediment, and fish tissue samples used in these analyses and contributed to development of the manuscript, however, no data were directly generated by US EPA personnel. This dataset is not publicly accessible because: No EPA data (see comments). It can be accessed through the following means: Data set can be obtained upon request from the corresponding author. Format: n/a. \n\nThis dataset is associated with the following publication:\nArini, A., J. Cavallin , J. Berninger, R. Marfil-Vega, M. Mills , D. Villeneuve , and N. Basu. In vivo and in vitro neurochemical-based assessments of wastewater effluents from the Maumee River area of concern..   SOCIETY OF ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY JOURNAL. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 211: 9-19, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-4xh3-350",
            "keyword": [
                "adverse outcome pathway",
                "surface water",
                "aquatic ecosystems",
                "cross-species extrapolation",
                "Great Lakes Research Initiative",
                "neuroendocrine"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [],
            "modified": "2015-12-15",
            "references": [
                "http://www.sciencedirect.com/science/article/pii/S0269749115302426"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "MOD13Q1",
            "description": "Normalized Difference Vegetation Index (NDVI). \n\nThis dataset is associated with the following publication:\nShao, Y., R. Lunetta , B. Wheeler, J. Iiames , and J. Campbell. An Evaluation of Time-Series Smoothing Algorithms for Landcover Classifications Using MODIS-NDVI Multi-Temporal Data.   REMOTE SENSING OF ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 174(0): 258-265, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-kwhq-353",
            "keyword": [
                "MODIS-NDVI",
                "MODIS-NDVI Smoothing"
            ],
            "contactPoint": {
                "fn": "Ross Lunetta",
                "hasEmail": "mailto:lunetta.ross@epa.gov"
            },
            "distribution": [
                {
                    "title": "Time-Series Smoothing_rse.2016.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/353/Time-Series%20Smoothing_rse.2016.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "https://modis.gsfc.nasa.gov/",
                    "accessURL": "https://modis.gsfc.nasa.gov/"
                },
                {
                    "title": "https://nassgeodata.gmu.edu/CropScape/",
                    "accessURL": "https://nassgeodata.gmu.edu/CropScape/"
                }
            ],
            "modified": "2015-11-20",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://modis.gsfc.nasa.gov/",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Assessment of the Bioaccessibility of Micronized Copper Wood on Simulated Stomach Fluid",
            "description": "The widespread use of copper-treated lumber has increased the potential for human exposure. Moreover, there is a lack of information on the fate and behavior of copper-treated wood particles following oral ingestion. In this study, the in vitro bioaccessibility of copper from copper-treated wood dust in simulated stomach fluid and DI water was determined. Three copper-treated wood products, liquid alkali copper quaternary and two micronized copper quarternary from different manufacturers, were incubated in the extraction media then fractionated by centrifugation and filtration through 0.45 \uf06dm and 10 kDa filters. The copper concentrations from isolated fractions were measured using Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES). Total amounts of copper from each wood product were also determined using microwave-assisted acid digestion of dried wood samples and quantification using ICP-OES. The percent in vitro bioaccessible copper was between 83 and 90 % for all treated wood types. However, the percent of copper released in DI water was between 14 and 25 % for all wood products. This data suggests that copper is highly bioaccessible at low pH and may pose a potential human exposure risk upon ingestion. \n\nThis dataset is associated with the following publication:\nSantiago-Rodrigues, L., J.L. Griggs, K. Bradham , C. Nelson , T. Luxton , W. Platten , and K. Rogers. Assessment of the bioaccessibility of micronized copper wood in synthetic stomach fluid.   Environmental Nanotechnology, Monitoring and Management. Elsevier B.V., Amsterdam,  NETHERLANDS, 4: 85-92, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-tx9t-277",
            "keyword": [
                "Copper",
                "Micronized Copper",
                "Wood",
                "Bioaccessibility",
                "Synthetic stomach fluid",
                "Human Exposure"
            ],
            "contactPoint": {
                "fn": "Kim Rogers",
                "hasEmail": "mailto:rogers.kim@epa.gov"
            },
            "distribution": [
                {
                    "title": "Table S2.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/277/Table%20S2.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Table S3.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/277/Table%20S3.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-09-07",
            "references": [
                "https://doi.org/10.1016/j.enmm.2015.07.003"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Pacific Ocean buoy temperature date - TAO/TRITON database & National Buoy Data Center database",
            "description": "Pacific Ocean buoy temperature data. \n\nThis dataset is associated with the following publication:\nCarbone, F., M. Landis, C.N. Gencarelli, A. Naccarato, F. Sprovieri, F. De Simone, I.M. Hedgecock, and N. Pirrone. Sea surface temperature variation linked to elemental mercury concentrations measured on Mauna Loa.   GEOPHYSICAL RESEARCH LETTERS. American Geophysical Union, Washington, DC, USA,  online, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-47dd-363",
            "keyword": [
                "Ocean Evation"
            ],
            "contactPoint": {
                "fn": "Matthew Landis",
                "hasEmail": "mailto:landis.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.pmel.noaa.gov/tao/index.shtml",
                    "accessURL": "https://www.pmel.noaa.gov/tao/index.shtml"
                },
                {
                    "title": "https://www.ndbc.noaa.gov/",
                    "accessURL": "https://www.ndbc.noaa.gov/"
                }
            ],
            "modified": "2016-04-21",
            "references": [
                "https://doi.org/10.1002/2016gl069252"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CMAPS Study Wet Only Mercury in Precipitation Data Set from Chippiwa Lake and G.T. Graig Monitoring Sites",
            "description": "Total mercury in precipitation collected using ASPS automated wet-only instrument and analyzed by cold vapor atomic fluorescence spectroscopy. \n\nThis dataset is associated with the following publication:\nLynam, M., J.T. Dvonch, J. Barres, M. Landis , and A. Kamal. Investigating the impact of local urban sources on total atmospheric mercury wet deposition in Cleveland, Ohio, USA.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 127: 262-271, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-8939-373",
            "keyword": [
                "Mercury Deposition Network",
                "Meteorological Case Study",
                "Lake Erie"
            ],
            "contactPoint": {
                "fn": "Matthew Landis",
                "hasEmail": "mailto:landis.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Hg_event_wet_deposition.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/373/Hg_event_wet_deposition.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-09-25",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2015.12.048"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data used in Xu et al., 2016 paper entitled \"Characteristics and distributions of atmospheric mercury emitted from anthropogenic sources in Guiyang, southwestern China",
            "description": "Mercury emissions data from anthropogenic sources as described in Xu et al., 2016. \n\nThis dataset is associated with the following publication:\nXu, X., N. Liu, M. Landis, X. Feng, and G. Qiu. Characteristics and distributions of atmospheric mercury emitted from anthropogenic sources in Guiyang, southwestern China.   Acta Geochimica. Springer, Heidelburg,  GERMANY,  1-11, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-4tmv-359",
            "keyword": [
                "Atmospheric mercury",
                "Speciation",
                "Antrhopogenic Sources",
                "GEM",
                "RGM",
                "PHg"
            ],
            "contactPoint": {
                "fn": "Matthew Landis",
                "hasEmail": "mailto:landis.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Xu_et_al_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/359/Xu_et_al_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-04-08",
            "references": [
                "http://link.springer.com/article/10.1007/s11631-016-0111-9"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Carbone_et_al_2016_ambient_data - Sea surface temperature variation linked to elemental mercury concentrationsmeasured on Mauna Loa",
            "description": "This data set has two sets of gaseous elemental mercury data. The first column contains all Hg related data some of which may have been affected by the upslope events such as the emissions from the nearby volcano. The next column contain values that were flagged and excluded as being affected by the nearby volcanic events. The flagging method used to eliminate these values was developed using an episode identification scheme using SO2 data. For the years of 2002 through 2004, hourly SO2 data were used to llag the upslope values. For the years of 2005-2009, 5 minute SO2 values were used to flag upslope events.\n\nWhile SO2 and O3 data were collected by EPA as part of this study, the CO2 data were downloaded from NOAA data website along with the flag related information provided below. (http://www.esrl.noaa.gov/gmd/dv/data/index.php?parameter_name=Carbon%2BDioxide&showall=1&site=MLO). \n\nThis dataset is associated with the following publication:\nCarbone, F., M. Landis, C.N. Gencarelli, A. Naccarato, F. Sprovieri, F. De Simone, I.M. Hedgecock, and N. Pirrone. Sea surface temperature variation linked to elemental mercury concentrations measured on Mauna Loa.   GEOPHYSICAL RESEARCH LETTERS. American Geophysical Union, Washington, DC, USA,  online, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-47dd-361",
            "keyword": [
                "Ocean Evation"
            ],
            "contactPoint": {
                "fn": "Matthew Landis",
                "hasEmail": "mailto:landis.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Carbone_et_al-2016_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/361/Carbone_et_al-2016_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-04-21",
            "references": [
                "https://doi.org/10.1002/2016gl069252"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Establishing the \u201cBiological Relevance\u201d of Dipentyl Phthalate Reductions in Fetal Rat Testosterone Production and Plasma and Testis Testosterone Levels ",
            "description": "metadata sheet, data sheet for each table and figure in the published manuscript. \n\nThis dataset is associated with the following publication:\nGray , E., J. Furr , K. Tatum-Gibbs, C. Lambright , H. Sampson, B. Hannas, V. Wilson , A. Hotchkiss , and P. Foster. Establishing the Biological Relevance of Dipentyl Phthalate Reductions in Fetal Rat Testosterone Production and Plasma and Testis Testosterone Levels.   TOXICOLOGICAL SCIENCES. Society of Toxicology,    149(1): 178-91, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-9cnz-347",
            "keyword": [
                "dipentyl phthalate",
                "sexual differentiation",
                "biologically relevant hormone changes",
                "androgen signaling pathway adverse outcome pathway",
                "Phthalates",
                "reproductive development"
            ],
            "contactPoint": {
                "fn": "Leon Gray",
                "hasEmail": "mailto:gray.earl@epa.gov"
            },
            "distribution": [
                {
                    "title": "science hub data sets and metadata file.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/347/science%20hub%20data%20sets%20and%20metadata%20file.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-18",
            "references": [
                "https://doi.org/10.1093/toxsci/kfv224",
                "https://pasteur.epa.gov/uploads/347/documents/gray%20et%20al%202016%20brrt%20dpep%20tox%20sci.pdf"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/347/documents/DATA%20DICTIONARY.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data supporting Al-Abed et al., Environ. Sci.: Nano, 2016,",
            "description": "Data files representing each of the Figures and Tables published in Al-Abed et al., Environ. Sci.: Nano, 2016,\n3, 593.  The data file names identify the Figure or Table and each file contains an internal set of data definitions. \n\nThis dataset is associated with the following publication:\nAl-Abed, S.R., J. Virkutyte, J. Ortenzio , R.M. McCarrick, L. Degn, R. Zucker , N. Coates , K. Cleveland, H. Ma, S. Diamond, K. Dreher , and W. Boyes. Environmental aging alters AI(OH)3 coating of TiO2 nanoparticles enhancing their photocatalytic and phototoxicity activities.   Environmental Science: Nano. RSC Publishing, Cambridge,  UK,  N/A, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-m64f-298",
            "keyword": [
                "sunscreen",
                "environmental degredation",
                "engineered nanomaterials",
                "Engineered nanoparticles (NP)",
                "nanomaterials",
                "phototoxicity",
                "environmental transformations",
                "titanium dioxide"
            ],
            "contactPoint": {
                "fn": "William Boyes",
                "hasEmail": "mailto:boyes.william@epa.gov"
            },
            "distribution": [
                {
                    "title": "TiO2_POOL_FIG_1_EDS data from Souhail.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/298/TiO2_POOL_FIG_1_EDS%20data%20from%20Souhail.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "TiO2_POOL_FIG_2_XPS data from Souhail.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/298/TiO2_POOL_FIG_2_XPS%20data%20from%20Souhail.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "TIO2_POOL_FIG_3_EPR_data.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/298/TIO2_POOL_FIG_3_EPR_data.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "TiO2_POOL_FIG_4_PHOTOTOX data from Jayna.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/298/TiO2_POOL_FIG_4_PHOTOTOX%20data%20from%20Jayna.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "TIO2_POOL_FIG_5_FLOW_SIDE_SCATTER.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/298/TIO2_POOL_FIG_5_FLOW_SIDE_SCATTER.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "TIO2_POOL_FIG_6_FLUOR_IMAGES.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/298/TIO2_POOL_FIG_6_FLUOR_IMAGES.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "TIO2_POOL_Suppl_Fig1_SEM.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/298/TIO2_POOL_Suppl_Fig1_SEM.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "TIO2_POOL_Suppl_Fig2_TEM.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/298/TIO2_POOL_Suppl_Fig2_TEM.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "TIO2_POOL_Suppl_Fig3_EDS_graph.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/298/TIO2_POOL_Suppl_Fig3_EDS_graph.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "TiO2_POOL_Suppl_Fig4_APF_TBARS.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/298/TiO2_POOL_Suppl_Fig4_APF_TBARS.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "TIO2_POOL_Suppl_Table1_FLOW_TABLE.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/298/TIO2_POOL_Suppl_Table1_FLOW_TABLE.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "TIO2_POOL_TABLE1_WICOXON_STATS.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/298/TIO2_POOL_TABLE1_WICOXON_STATS.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "TIO2_POOL_TABLE2_AGGOLMERATION.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/298/TIO2_POOL_TABLE2_AGGOLMERATION.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-09-12",
            "references": [
                "https://doi.org/10.1039/c5en00250h"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Computational Modeling and Simulation of Genital Tubercle Development",
            "description": "Hypospadias is a developmental defect of urethral tube closure that has a complex etiology involving genetic and environmental factors, including anti-androgenic and estrogenic disrupting chemicals; however, little is known about the morphoregulatory consequences of androgen/estrogen balance during genital tubercle (GT) development. Computer models that predictively model sexual dimorphism of the GT may provide a useful resource to translate chemical-target bipartite networks and their developmental consequences across the human-relevant chemical universe. Here, we describe a multicellular agent-based model of genital tubercle (GT) development that simulates urethrogenesis from the sexually-indifferent urethral plate stage to urethral tube closure. The prototype model, constructed in CompuCell3D, recapitulates key aspects of GT morphogenesis controlled by SHH, FGF10, and androgen pathways through modulation of stochastic cell behaviors, including differential adhesion, motility, proliferation, and apoptosis. Proper urethral tube closure in the model was shown to depend quantitatively on SHH- and FGF10-induced effects on mesenchymal proliferation and epithelial apoptosis\u2014both ultimately linked to androgen signaling. In the absence of androgen, GT development was feminized and with partial androgen deficiency, the model resolved with incomplete urethral tube closure, thereby providing an in silico platform for probabilistic prediction of hypospadias risk across combinations of minor perturbations to the GT system at various stages of embryonic development. \n\nThis dataset is associated with the following publication:\nLeung , M.C.K., S. Hutson, A. Seifert, R. Spencer, and T. Knudsen. (REPRODUCTIVE TOXICOLOGY) Computational Modeling and Simulation of Genital Tubercle Development.   REPRODUCTIVE TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA,  1-11, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-dncw-339",
            "keyword": [
                "Reproductive effects",
                "reproductive development",
                "Children's Environmental Health",
                "virtual embryo",
                "virtual tissues",
                "virtual liver",
                "tipping points"
            ],
            "contactPoint": {
                "fn": "Thomas Knudsen",
                "hasEmail": "mailto:knudsen.thomas@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/Knudsen/Virtual_Tissues_Male_Repro_Tox/Leung_2016_RTX/",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/Knudsen/Virtual_Tissues_Male_Repro_Tox/Leung_2016_RTX/"
                }
            ],
            "modified": "2016-09-01",
            "references": [
                "https://doi.org/10.1016/j.reprotox.2016.05.005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data from Tiered High-Throughput Screening Approach to Identify Thyroperoxidase Inhibitors within the ToxCast Phase I and II Chemical Libraries ",
            "description": "High-throughput screening for potential thyroid-disrupting chemicals requires a system of assays to capture multiple molecular-initiating events (MIEs) that converge on perturbed thyroid hormone (TH) homeostasis. Screening for MIEs specific to TH-disrupting pathways is limited in the U.S. Environmental Protection Agency ToxCast screening assay portfolio. To fill 1 critical screening gap, the Amplex UltraRed-thyroperoxidase (AUR-TPO) assay was developed to identify chemicals that inhibit TPO, as decreased TPO activity reduces TH synthesis. The ToxCast phase I and II chemical libraries, comprised of 1074 unique chemicals, were initially screened using a single, high concentration to identify potential TPO inhibitors. Chemicals positive in the single-concentration screen were retested in concentration-response. Due to high false-positive rates typically observed with loss-of-signal assays such as AUR-TPO, we also employed 2 additional assays in parallel to identify possible sources of nonspecific assay signal loss, enabling stratification of roughly 300 putative TPO inhibitors based upon selective AUR-TPO activity. A cell-free luciferase inhibition assay was used to identify nonspecific enzyme inhibition among the putative TPO inhibitors, and a cytotoxicity assay using a human cell line was used to estimate the cellular tolerance limit. Additionally, the TPO inhibition activities of 150 chemicals were compared between the AUR-TPO and an orthogonal peroxidase oxidation assay using guaiacol as a substrate to confirm the activity profiles of putative TPO inhibitors. This effort represents the most extensive TPO inhibition screening campaign to date and illustrates a tiered screening approach that focuses resources, maximizes assay throughput, and reduces animal use. \n\nThis dataset is associated with the following publication:\nPaul-Friedman, K., E.D. Watt , M.W. Hornung , J.M. Hedge , R.S. Judson , K.M. Crofton , K.A. Houck , and S.O. Simmons. (TOXICOLOGICAL SCIENCES) Tiered High-Throughput Screening Approach to Identify Thyroperoxidase Inhibitors within the ToxCast Phase I and II Chemical Libraries.   TOXICOLOGICAL SCIENCES. Society of Toxicology,     1-59, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-z35j-97",
            "keyword": [
                "ToxCast",
                "chemical safety research",
                "chemical safety for sustainablity",
                "high-throughput toxicology",
                "Thyroperoxidase",
                "endocrine disruption"
            ],
            "contactPoint": {
                "fn": "Steven Simmons",
                "hasEmail": "mailto:simmons.steve@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figures and Tables_v10.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/97/Figures%20and%20Tables_v10.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/FriedmanPaul_K/2016_TPO_ToxCast_ToxSci",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/FriedmanPaul_K/2016_TPO_ToxCast_ToxSci"
                }
            ],
            "modified": "2016-04-01",
            "references": [
                "https://doi.org/10.1093/toxsci/kfw034"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Watershed impervious cover relative to stream location",
            "description": "Estimates of watershed (12-digit huc) impervious cover and impervious cover near streams and water body shorelines for three dates (2001, 2006, 2011) using NLCD data.  Differences between watershed impervious cover and impervious cover near streams can be used to assess the spatial pattern of impervious cover within a watershed. \n\nThis dataset is associated with the following publication:\nWickham , J., A. Neale , M. Mehaffey , T. Jarnagin , and D. Norton. Temporal Trends in Impervious Cover Relative to Stream Location..   JOURNAL OF AMERICAN WATER RESOURCES ASSOCIATION. American Water Resources Association, Middleburg, VA, USA, 52(2): 409-419, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-n03c-254",
            "keyword": [
                "Impervious cover",
                "National Land Cover Database (NLCD)",
                "Clean Water Act",
                "change detection",
                "roads",
                "spatial pattern"
            ],
            "contactPoint": {
                "fn": "James Wickham",
                "hasEmail": "mailto:wickham.james@epa.gov"
            },
            "distribution": [
                {
                    "title": "SciHub_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/254/SciHub_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "SciHub_Metadata.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/254/SciHub_Metadata.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2015-01-31",
            "references": [
                "https://www.epa.gov/enviroatlas"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/254/documents/SciHub_Metadata.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Permeable pavement study (Edison)",
            "description": "While permeable pavement is increasingly being used to control stormwater runoff, field-based, side-by-side investigations on the effects different pavement types have on nutrient concentrations present in stormwater runoff are limited.  In 2009, the U.S. EPA constructed a 0.4-ha parking lot in Edison, New Jersey, that incorporated permeable interlocking concrete pavement (PICP), pervious concrete (PC), and porous asphalt (PA).  Each permeable pavement type has four, 54.9-m2, lined sections that direct all infiltrate into 5.7-m3 tanks enabling complete volume collection and sampling.  This paper highlights the results from a 12-month period when samples were collected from 13 rainfall/runoff events and analyzed for nitrogen species, orthophosphate, and organic carbon.  Differences in infiltrate concentrations among the three permeable pavement types were assessed and compared with concentrations in rainwater samples and impervious asphalt runoff samples, which were collected as controls.  Contrary to expectations based on the literature, the PA infiltrate had significantly larger total nitrogen (TN) concentrations than runoff and infiltrate from the other two permeable pavement types, indicating that nitrogen leached from materials in the PA strata.  There was no significant difference in TN concentration between runoff and infiltrate from either PICP or PC, but TN in runoff was significantly larger than in the rainwater, suggesting meaningful inter-event dry deposition.  Similar to other permeable pavement studies, nitrate was the dominant nitrogen species in the infiltrate.  The PA infiltrate had significantly larger nitrite and ammonia concentrations than PICP and PC, and this was presumably linked to unexpectedly high pH in the PA infiltrate that greatly exceeded the optimal pH range for nitrifying bacteria.  Contrary to the nitrogen results, the PA infiltrate had significantly smaller orthophosphate concentrations than in rainwater, runoff, and infiltrate from PICP and PC, and this was attributed to the high pH in PA infiltrate possibly causing rapid precipitation of orthophosphate with metal cations.  Orthophosphate was exported from the PICP and PC, as evidenced by the significantly larger infiltrate concentrations compared with influent sources of rainwater and runoff. \n\nThis dataset is associated with the following publication:\nBrown , R., and M. Borst. Nutrient Infiltrate Concentrations from Three Permeable Pavement Types.   JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 164: 74-85, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-ghxg-275",
            "keyword": [
                "Green Infrastructure",
                "bmp",
                "stormwater management",
                "GI perrormance"
            ],
            "contactPoint": {
                "fn": "Michael Borst",
                "hasEmail": "mailto:borst.mike@epa.gov"
            },
            "distribution": [
                {
                    "title": "edison parking lot nutrient data base period.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/275/edison%20parking%20lot%20nutrient%20data%20base%20period.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-06",
            "references": [
                "http://www.ncbi.nlm.nih.gov/pubmed/26348134"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Evaluating the Accuracy of Common Runoff Estimation Methods for New Impervious Hot-Mix Asphalt",
            "description": "Excel workbook,  First sheet is data dictionary.  second sheet is the data representing the abstraction for events with short antecedent dry period (less than 24 hr). \n\nThis dataset is associated with the following publication:\nBrown , R., and M. Borst. Evaluating the Accuracy of Common Runoff Estimation Methods for New Impervious Hot-Mix Asphalt.   Journal of Sustainable Water in the Built Environment. American Society of Civil Engineers (ASCE), New York, NY, USA,  online, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-4qrm-352",
            "keyword": [
                "runoff",
                "Hot-Mix Asphalt",
                "Small Storm Hydrology Method",
                "Simple Method",
                "SCS-Curve Number Method",
                "stormwater",
                "stormwater management"
            ],
            "contactPoint": {
                "fn": "Michael Borst",
                "hasEmail": "mailto:borst.mike@epa.gov"
            },
            "distribution": [
                {
                    "title": "Borst-ScID A-4qrm.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/352/Borst-ScID%20A-4qrm.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-08-01",
            "references": [
                "https://doi.org/10.1061/jswbay.0000806"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Ensemble standar deviation of wind speed and direction of the FDDA input to WRF",
            "description": "NetCDF file of the SREF standard deviation of wind speed and direction that was used to inject variability in the FDDA input.\r\n\r\nvariable U_NDG_OLD contains standard deviation of wind speed (m/s)\r\nvariable V_NDG_OLD contains the standard deviation of wind direction (deg). This dataset is not publicly accessible because: This is a netcdf file that is 3.9Gb. It can be accessed through the following means: On the HPC system sol (2016). In the asm archive here: /asm/grc/JGR_ENSEMBLE_ScienceHub/figure1.nc. Format: Figure 1 data. This is the variability of wind speed and direction of the four dimensional data assimilation inputs. The variability includes the 14 members of the ensemble. \n\nThis dataset is associated with the following publication:\nGilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259\u201312,280, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-6q5f-374",
            "keyword": [
                "FDDA",
                "Wind Speed and direction variability",
                "WRF",
                "probabilistic modeling",
                "ensemble modeling",
                "WRF-CMAQ",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Robert Gilliam",
                "hasEmail": "mailto:gilliam.robert@epa.gov"
            },
            "distribution": [],
            "modified": "2015-07-21",
            "references": [
                "https://doi.org/10.1002/2015jd023674"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/374/documents/figure1.data.dictionary.txt",
            "describedByType": "text/plain",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figure 3",
            "description": "The Figure.tar.gz contains a directory for each WRF ensemble run. In these directories are *.csv files for each meteorology variable examined. These are comma delimited text files that contain statistics for each observation site. Also provided is an R script that reads these files (user would need to change directory pointers) and computes the variability of error and bias of the ensemble at each site and plots these for reproduction of figure 3. This dataset is not publicly accessible because: 30Mb tar, 15 Mb tar.gz. It can be accessed through the following means: On the EPA HPC system sol archive: /asm/grc/JGR_ENSEMBLE_ScienceHub/figure3.tar. Format: tar.gz file of text files that contain the surface meteorology statistics that were used to created Figure 3. Also included is a R script that will allow anyone interested to re-generate the figure. \n\nThis dataset is associated with the following publication:\nGilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259\u201312,280, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-6q5f-375",
            "keyword": [
                "variability",
                "temperature",
                "wind speed",
                "mixing ratio",
                "ensemble",
                "probabilistic modeling",
                "ensemble modeling",
                "WRF-CMAQ",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Robert Gilliam",
                "hasEmail": "mailto:gilliam.robert@epa.gov"
            },
            "distribution": [],
            "modified": "2015-09-02",
            "references": [
                "https://doi.org/10.1002/2015jd023674"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figure4",
            "description": "NetCDF files of PBL height (m), Shortwave Radiation, 10 m wind speed from WRF and Ozone from CMAQ. The data is the standard deviation of these variables for each hour of the 4 day simulation. Figure 4 is only one of the time periods: June 8, 2100 UTC. The NetCDF files have a time stamp (Times) that can be used to find this time in order to reproduce the Figure 4. Also included is a data dictionary that describes the domain and all other attributes of the model simulation. This dataset is not publicly accessible because: The file is 202Mb binary NetCDF file that is too large. It can be accessed through the following means: Archived on the US EPA HPC Sol computer system:/asm/grc/JGR_ENSEMBLE_ScienceHub/Figure4.tar.gz. Format: Tar.gz file that contains NetCDF files required to reproduce Figure 4. \n\nThis dataset is associated with the following publication:\nGilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259\u201312,280, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-6q5f-376",
            "keyword": [
                "PBL Height",
                "Ozone",
                "Solar Radiation",
                "10-m wind speed",
                "Standard deviation of the SREF Ensemble",
                "probabilistic modeling",
                "ensemble modeling",
                "WRF-CMAQ"
            ],
            "contactPoint": {
                "fn": "Robert Gilliam",
                "hasEmail": "mailto:gilliam.robert@epa.gov"
            },
            "distribution": [],
            "modified": "2015-07-22",
            "references": [
                "https://doi.org/10.1002/2015jd023674"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/376/documents/figure4.data.dictionary.txt",
            "describedByType": "text/plain",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figure5",
            "description": "This is an R statistics package script that allows the reproduction of Figure 5. The script includes the links to large NetCDF files that the figures access for O3, CO, wind speed, radiation and PBL height. It pulls the timeseries for each variable at a number of cities (lat-lon specified). \n\nThis dataset is associated with the following publication:\nGilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259\u201312,280, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-6q5f-377",
            "keyword": [
                "timeseries",
                "O3",
                "CO",
                "PBL Height",
                "Radiation",
                "wind speed",
                "probabilistic modeling",
                "ensemble modeling",
                "WRF-CMAQ",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Robert Gilliam",
                "hasEmail": "mailto:gilliam.robert@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure5.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/377/Figure5.txt",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2012-10-01",
            "references": [
                "https://doi.org/10.1002/2015jd023674"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figure6",
            "description": "R script for the reproduction of Figure6. This script accesses archived CMAQ and WRF model output on US EPA's HPC sol computer system and plots forward trajectories and ozone concentrations from major cities in the US. \n\nThis dataset is associated with the following publication:\nGilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259\u201312,280, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-6q5f-379",
            "keyword": [
                "trajectories",
                "O3",
                "ensemble modeling",
                "probabilistic modeling",
                "WRF-CMAQ",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Robert Gilliam",
                "hasEmail": "mailto:gilliam.robert@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure6.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/379/Figure6.txt",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2013-02-12",
            "references": [
                "https://doi.org/10.1002/2015jd023674"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figure 7",
            "description": "Two files provided. The ENS.tar file contains text data files (*.csv) used to create Figure 7 and Figure 8. The Figure7.txt is an R script that reads these files and generates the plots for various cities including the four published in Figure 7 and Figure 8. \n\nThis dataset is associated with the following publication:\nGilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259\u201312,280, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-6q5f-380",
            "keyword": [
                "variability",
                "O3",
                "Probablistic Evaluation",
                "probabilistic modeling",
                "ensemble modeling",
                "WRF-CMAQ",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Robert Gilliam",
                "hasEmail": "mailto:gilliam.robert@epa.gov"
            },
            "distribution": [
                {
                    "title": "ENS.city.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/380/ENS.city.tar",
                    "mediaType": "application/x-tar"
                },
                {
                    "title": "Figure7.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/380/Figure7.txt",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2015-08-03",
            "references": [
                "https://doi.org/10.1002/2015jd023674"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figure 9",
            "description": "This is a NetCDF file in ioapi format that contains the probability that ozone is above the 8 hr max O3 standard for the four days of the simulation. This dataset is not publicly accessible because: The file size is a large binary NetCDF file of 56Mb. It can be accessed through the following means: File is located on US EPA's HPC system sol file archive: /asm/grc/JGR_ENSEMBLE_ScienceHub/Figure9.nc. Format: NetCDF file that contains the O3 gridded data to reproduce Figure 9. \n\nThis dataset is associated with the following publication:\nGilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259\u201312,280, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-6q5f-381",
            "keyword": [
                "O3",
                "Probablity",
                "probabilistic modeling",
                "ensemble modeling",
                "WRF-CMAQ",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Robert Gilliam",
                "hasEmail": "mailto:gilliam.robert@epa.gov"
            },
            "distribution": [],
            "modified": "2015-07-22",
            "references": [
                "https://doi.org/10.1002/2015jd023674"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data from Phelan et al. 2016 (Water Air and Soil Pollution 227:84. DOI 10.1007/s11270-016-2762-x). \"Assessing the effects of climate change and air pollution on soil properties and plant diversity in sugar-maple-beech-yellow birch hardwood...\"",
            "description": "This dataset describes the simulations at two pilot sites in the northeast from 1900-2100 for several soil and plant community responses to climate and nitrogen deposition across a number of future scenarios. \n\nThis dataset is associated with the following publications:\nPhelan, J., S. Belyazid, C. Clark , P. Jones, and J. Cajka. Assessing the Effects of Climate Change and Air Pollution on Soil Properties and Plant Diversity in Sugar Maple-Beech-Yellow Birch Hardwood Forests in the Northeastern United States:  Model Simulations from 1900-2100.   WATER, AIR, & SOIL POLLUTION. Springer, New York, NY, USA, 227(3): 1-30, (2016).\nBelyazid, S., J. Phelan, B. Nihlgard, H. Sverdrup, C. Driscoll, I. Fernandez, J. Aherne, L.M. Teeling-Adams, S. Bailey, M. Arsenault, N. Cleavitt, B. Engstrom, R. Dennis, D. Sperduto, D. Werier, and C. Clark. Assessing the Effects of Climate Change and Air Pollution on Soil Properties and Plant Diversity in Northeastern U.S. Hardwood Forests: Model Setup and Evaluation.   WATER, AIR, & SOIL POLLUTION. Springer, New York, NY, USA, 230: 106, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-c5b9-356",
            "keyword": [
                "nitrogen",
                "nitrogen deposition",
                "critical loads",
                "air quality",
                "biogeochemical cycling",
                "ecosystem services",
                "biodiversity"
            ],
            "contactPoint": {
                "fn": "Christopher Clark",
                "hasEmail": "mailto:clark.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "Model_data_file_catalogue_FSV-Scen.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/356/Model_data_file_catalogue_FSV-Scen.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Data_Zipped.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/356/Data_Zipped.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-07-08",
            "references": [
                "https://doi.org/10.1007/s11270-016-2762-x",
                "https://doi.org/10.1007/s11270-019-4145-6"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Pb Speciation Data to Estimate Lead Bioavailability to Quail",
            "description": "Linear combination fitting data for lead speciation of soil samples evaluated through an in-vivo/in-vitro correlation for quail exposure. \n\nThis dataset is associated with the following publication:\nBeyer, W.N., N. Basta, R. Chaney, P. Henry, D. Mosby, B. Rattner, K. Scheckel , D. Sprague, and J. Weber. BIOACCESSIBILITY TESTS ACCURATELY ESTIMATE BIOAVAILABILITY OF LEAD TO QUAIL.  G.A. Burton, Jr., and C. H. Ward  ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 35(9): 2311-2319, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-66t7-383",
            "keyword": [
                "metal bioavailability",
                "synchrotron speciation",
                "ecological risk assessment",
                "soil contamination",
                "soil amendments",
                "wildlife toxicology"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "BeyeretalQuailPbPaper_LCFDate_Table3.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/383/BeyeretalQuailPbPaper_LCFDate_Table3.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-05-09",
            "references": [
                "https://doi.org/10.1002/etc.3399"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "an Integrated science based methodology",
            "description": "The data is secondary in nature.  Meaning that no data was generated as part of this review effort.  Rather, data that was available in the peer-reviewed literature was used. This dataset is not publicly accessible because: This is a review manuscript, there was not data generated under this effort. All data used was secondary data and sources of the data were identified in the manuscript. It can be accessed through the following means: there is no database. Format: there is no data base. \n\nThis dataset is associated with the following publication:\nTolaymat , T., A. El Badawy, R. Sequeira, and A. Genaidy. An integrated science-based methodology to assess potential risks and implications of engineered nanomaterials.  Diana Aga, Wonyong Choi, Andrew Daugulis, Gianluca Li Puma, Gerasimos Lyberatos, and Joo Hwa Tay  JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, USA, 298: 270-281, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-k0pj-378",
            "keyword": [
                "nanomaterials",
                "Risk",
                "Methodology"
            ],
            "contactPoint": {
                "fn": "Thabet Tolaymat",
                "hasEmail": "mailto:tolaymat.thabet@epa.gov"
            },
            "distribution": [],
            "modified": "2016-09-09",
            "references": [
                "https://doi.org/10.1016/j.jhazmat.2015.04.019"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "In vivo plasma concentration for lindane after 6 hour exposure in human skin",
            "description": "Dataset is a time course description of lindane disappearance in blood plasma after dermal exposure in human volunteers. \n\nThis dataset is associated with the following publication:\nSawyer, M.E., M.V. Evans , C. Wilson, L.J. Beesley, L. Leon, C. Eklund , E. Croom, and R. Pegram. Development of a Human Physiologically Based Pharmacokinetics (PBPK) Model For Dermal Permeability for Lindane.   TOXICOLOGY LETTERS. Elsevier Science Ltd, New York, NY, USA, 14(245): pp106-109, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-0cfz-313",
            "keyword": [
                "lindane",
                "pbpk",
                "in vivo",
                "human",
                "ExpoCast",
                "ToxCast",
                "Dermal Permeation",
                "dermal diffusion",
                "dermal lag time",
                "dermal cumulative absorption"
            ],
            "contactPoint": {
                "fn": "Marina Evans",
                "hasEmail": "mailto:evans.marina@epa.gov"
            },
            "distribution": [
                {
                    "title": "sawyer_2016_sciencehib.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/313/sawyer_2016_sciencehib.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-14",
            "references": [
                "https://doi.org/10.1016/j.toxlet.2016.01.008"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data submission for A-d25f",
            "description": "Includes 1) list of genes in the STAT5b biomarker and 2) list of accession numbers for microarray datasets used in study. \n\nThis dataset is associated with the following publication:\nOshida, K., N. Vasani, D. Waxman, and C. Corton. Disruption of STAT5b-Regulated Sexual Dimorphism of the Liver Transcriptome by Diverse Factors Is a Common Event.   PLoS ONE. Public Library of Science, San Francisco, CA, USA, 11(3): NA, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-d25f-177",
            "keyword": [
                "microarray accession numbers",
                "list of STAT5b biomarker genes",
                "liver cancer",
                "STAT5b",
                "transcriptomics",
                "androgens",
                "estrogens"
            ],
            "contactPoint": {
                "fn": "Jon Corton",
                "hasEmail": "mailto:corton.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data submission for A-d25f.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/177/Data%20submission%20for%20A-d25f.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-03-01",
            "references": [
                "https://doi.org/10.1371/journal.pone.0148308"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data submission for A-p8dg",
            "description": "Accession numbers for microarray datasets used in Oshida et al. Chemical and Hormonal Effects on STAT5b-Dependent Sexual Dimorphism of the Liver Transcriptome.  PLoS One. 2016 Mar 9;11(3):e0150284. \n\nThis dataset is associated with the following publication:\nOshida, K., D. Waxman, and C. Corton. Chemical and Hormonal Effects on STAT5b-Dependent Sexual Dimorphism of the Liver Transcriptome..   PLoS ONE. Public Library of Science, San Francisco, CA, USA, 11(3): NA, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-p8dg-181",
            "keyword": [
                "microarray accession numbers",
                "transcriptomics",
                "STAT5b",
                "constitutive activated receptor (CAR)",
                "peroxisome proliferator activated receptor alpha",
                "aryl hydrocarbon receptor",
                "growth hormone",
                "hypothalamic-pituitary-liver axis"
            ],
            "contactPoint": {
                "fn": "Jon Corton",
                "hasEmail": "mailto:corton.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data submission for A-p8dg.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/181/Data%20submission%20for%20A-p8dg.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-03-01",
            "references": [
                "https://doi.org/10.1371/journal.pone.0150284"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data submission for A-0k6f",
            "description": "List of biomarker genes used to predict estrogen receptor activity in MCF-7 cells; list of microarray accession numbers used in the study. \n\nThis dataset is associated with the following publication:\nVanduyn, N., B. Chorley , R. Tice, R. Judson , and C. Corton. Moving Toward Integrating Gene Expression Profiling into High-throughput Testing:A Gene Expression Biomarker Accurately Predicts Estrogen Receptor \u03b1 Modulation in a Microarray Compendium.   TOXICOLOGICAL SCIENCES. Society of Toxicology,    151(1): 88-103, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-0k6f-182",
            "keyword": [
                "microarray accession numbers",
                "biomarker genes",
                "estrogen receptor",
                "endocrine disruption",
                "transcriptomics",
                "microarray"
            ],
            "contactPoint": {
                "fn": "Jon Corton",
                "hasEmail": "mailto:corton.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data submission for A-0k6f.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/182/Data%20submission%20for%20A-0k6f.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-01-01",
            "references": [
                "https://doi.org/10.1093/toxsci/kfw026"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data submission for A-gf27",
            "description": "Biomarker genes used to predict AhR activity; accession numbers of microarray datasets used in the study. \n\nThis dataset is associated with the following publication:\nOshida, K., N. Vasani, W. Ward , R. Thomas , D. Applegate, F. Gonzalez, L. Aleksunes, C. Klaassen, and C. Corton. Screening a mouse liver gene expression Compendium Identifies Effectors of the Aryl Hydrocarbon reeptors (AhR).   TOXICOLOGICAL SCIENCES. Society of Toxicology,    336: 99-112, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-gf27-183",
            "keyword": [
                "microarray accession numbers",
                "biomarker genes",
                "aryl hydrocarbon receptor",
                "microarray",
                "transcriptomics",
                "liver cancer",
                "constitutive activated receptor (CAR)",
                "pregnane x receptor (PXR)",
                "peroxisome proliferator activated receptor alpha"
            ],
            "contactPoint": {
                "fn": "Jon Corton",
                "hasEmail": "mailto:corton.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data submission for A-gf27.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/183/Data%20submission%20for%20A-gf27.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-01-01",
            "references": [
                "https://doi.org/10.1016/j.tox.2015.07.005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Effect of genetic strain and gender on age-related changes in body composition of the laboratory rat.",
            "description": "Body composition data for common laboratory strains of rat as a function of age. \n\nThis dataset is associated with the following publication:\nGordon , C., K. Jarema , A. Johnstone , and P. Phillips. Effect of Genetic Strain and Gender on Age-Related Changes in Body Composition of the Laboratory Rat.   Physiology & Behavior. Elsevier B.V., Amsterdam,  NETHERLANDS, 153(1): 56-63, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-tqkb-176",
            "keyword": [
                "Genetic strain",
                "gender",
                "Aging",
                "Body composition"
            ],
            "contactPoint": {
                "fn": "Christopher Gordon",
                "hasEmail": "mailto:gordon.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "E314 Science hub Effects of Genetic Strain and aging Data for MS.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/176/E314%20Science%20hub%20Effects%20of%20Genetic%20Strain%20and%20aging%20Data%20for%20MS.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-03-11",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figure10",
            "description": "Fortran/NCARgraphics program to compute and plot RRF mean and variability:map_rrf_variability_13runs_epimax.f\r\n\r\nIoapi files needed by Fortran/NCARGraphics code:\r\nCMAQ.CONC.SREF.June2011.New.13runs.o3_8hrdm\r\nCMAQ.CONC.SREF.June2011.N50V25.New.13runs.o3_8hrdm\r\nGRIDCRO2D_060607\r\n\r\nPlotting routines \r\nmap_rrf_mean_sigma_ne_13runs_epimax.ps\r\nmap_rrf_mean_sigma_ne_13runs_epimax.ncgm. \n\nThis dataset is associated with the following publication:\nGilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259\u201312,280, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-6q5f-387",
            "keyword": [
                "Relative Response Factor",
                "O3",
                "VOCs",
                "Emissions reductions",
                "probabilistic modeling",
                "ensemble modeling",
                "WRF-CMAQ",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Robert Gilliam",
                "hasEmail": "mailto:gilliam.robert@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure10.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/387/Figure10.tar",
                    "mediaType": "application/x-tar"
                }
            ],
            "modified": "2012-11-02",
            "references": [
                "https://doi.org/10.1002/2015jd023674"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figure11",
            "description": "R script: ensemble_rrf_sigma_vs_mean_play.R\r\nData: ensemble_mean_sigma_rrf_allgrids_epismax_new_13runs.csv\r\nPlot: boxplot_ensemble_rrf_sigma_vs_mean_nowater_new_13runs_epimax.pdf. \n\nThis dataset is associated with the following publication:\nGilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259\u201312,280, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-6q5f-388",
            "keyword": [
                "RRF",
                "Ozone",
                "emissions reduction",
                "probabilistic modeling",
                "ensemble modeling",
                "WRF-CMAQ"
            ],
            "contactPoint": {
                "fn": "Robert Gilliam",
                "hasEmail": "mailto:gilliam.robert@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure11.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/388/Figure11.tar",
                    "mediaType": "application/x-tar"
                }
            ],
            "modified": "2012-11-13",
            "references": [
                "https://doi.org/10.1002/2015jd023674"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figure12",
            "description": "NCL script: cmaq_ensemble_isam_4panels_subdomain.ncl\r\n\r\nNetcdf input file for NCL script, containing ensemble means and standard deviation of ISAM SO4 and O3 contributions from IPM: test.nc\r\n\r\nPlot (ps): maps_isam_mean_std_lasthour_ipm_so4_o3_east.ps\r\n\r\nPlot (pdf): maps_isam_mean_std_lasthour_ipm_so4_o3_east.pdf\r\n\r\nPlot (ncgm): maps_isam_mean_std_lasthour_ipm_so4_o3_east.ncgm. This dataset is not publicly accessible because: This contains a dataset that is well over 1Gb, so link provided to US EPA's HPC system where all information can be retrieved. It can be accessed through the following means: /asm/grc/JGR_ENSEMBLE_ScienceHub/Figure12.tar.gz. Format: Tar file with scripts and datasets needed to reproduce Figure 12. \n\nThis dataset is associated with the following publication:\nGilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259\u201312,280, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-6q5f-389",
            "keyword": [
                "CMAQ ISAM",
                "Source Attribution",
                "ensemble modeling",
                "O3",
                "probabilistic modeling",
                "WRF-CMAQ",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Robert Gilliam",
                "hasEmail": "mailto:gilliam.robert@epa.gov"
            },
            "distribution": [],
            "modified": "2014-11-10",
            "references": [
                "https://doi.org/10.1002/2015jd023674"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Predicted median July stream/river temperature regime in New England",
            "description": "This shapefile includes the predicted thermal regime for all NHDPlus version 1 stream and river reaches in New England within the model domain based on the spatial statistical network model published in Detenbeck et al. 2016 (Detenbeck, N. E., Morrison, A., Abele, R. W. and Kopp, D. (2016), Spatial statistical network models for stream and river temperature in New England, USA. Water Resour. Res. Accepted Author Manuscript. doi:10.1002/2015WR018349). Portions of this dataset are inaccessible because: The dataset can be accessed for download via the EPA application Estuary Data Mapper, downloadable from www.epa.gov/edm. They can be accessed through the following means: The dataset can be accessed for download via the EPA application Estuary Data Mapper, downloadable from www.epa.gov/edm. Format: Shapefile with associated metadata. \n\nThis dataset is associated with the following publication:\nDetenbeck , N., A. Morrison, R. Abele , and D. Kopp. Spatial statistical network models for stream and river temperature in New England, USA.   WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 52: 6018\u20136040, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-j9kt-120",
            "keyword": [
                "water temperature",
                "spatial statistical network model",
                "New England",
                "streams",
                "rivers",
                "stormwater",
                "green infrastrucutre",
                "aquatic biota",
                "habitat"
            ],
            "contactPoint": {
                "fn": "Naomi Detenbeck",
                "hasEmail": "mailto:detenbeck.naomi@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/hesc/estuary-data-mapper-edm",
                    "accessURL": "https://www.epa.gov/hesc/estuary-data-mapper-edm"
                }
            ],
            "modified": "2016-07-17",
            "references": [
                "https://doi.org/10.1002/2015wr018349"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "New England observed and predicted median July stream/river temperature points",
            "description": "The shapefile contains points with associated observed and predicted median July stream/river temperatures in New England based on a spatial statistical network model published in Detenbeck et al. (2016): Raw stream/temperature data were received from a variety of state agencies, watershed organizations, and Federal agencies (see Detenbeck et al. 2016 for complete list: Detenbeck, N. E., Morrison, A., Abele, R. W. and Kopp, D. (2016), Spatial statistical network models for stream and river temperature in New England, USA. Water Resour. Res. Accepted Author Manuscript. doi:10.1002/2015WR018349). This dataset is not publicly accessible because: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). It can be accessed through the following means: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). Format: Shapefile. \n\nThis dataset is associated with the following publication:\nDetenbeck , N., A. Morrison, R. Abele , and D. Kopp. Spatial statistical network models for stream and river temperature in New England, USA.   WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 52: 6018\u20136040, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-j9kt-121",
            "keyword": [
                "spatial statistical network model",
                "streams",
                "water temperature",
                "rivers",
                "New England",
                "July",
                "stormwater",
                "green infrastrucutre",
                "aquatic biota",
                "habitat"
            ],
            "contactPoint": {
                "fn": "Naomi Detenbeck",
                "hasEmail": "mailto:detenbeck.naomi@epa.gov"
            },
            "distribution": [],
            "modified": "2015-09-10",
            "references": [
                "https://doi.org/10.1002/2015wr018349"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "New England observed and predicted median August stream/river temperature points",
            "description": "The shapefile contains points with associated observed and predicted median August stream/river temperatures in New England based on a spatial statistical network model published in Detenbeck et al. (2016): Raw stream/temperature data were received from a variety of state agencies, watershed organizations, and Federal agencies (see Detenbeck et al. 2016 for complete list: Detenbeck, N. E., Morrison, A., Abele, R. W. and Kopp, D. (2016), Spatial statistical network models for stream and river temperature in New England, USA. Water Resour. Res. Accepted Author Manuscript. doi:10.1002/2015WR018349). Portions of this dataset are inaccessible because: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). They can be accessed through the following means: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). Format: Shapefile. \n\nThis dataset is associated with the following publication:\nDetenbeck , N., A. Morrison, R. Abele , and D. Kopp. Spatial statistical network models for stream and river temperature in New England, USA.   WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 52: 6018\u20136040, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-j9kt-122",
            "keyword": [
                "spatial statistical network model",
                "streams",
                "rivers",
                "water temperature",
                "New England",
                "stormwater",
                "green infrastrucutre",
                "aquatic biota",
                "habitat"
            ],
            "contactPoint": {
                "fn": "Naomi Detenbeck",
                "hasEmail": "mailto:detenbeck.naomi@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/hesc/estuary-data-mapper-edm",
                    "accessURL": "https://www.epa.gov/hesc/estuary-data-mapper-edm"
                }
            ],
            "modified": "2015-09-10",
            "references": [
                "https://doi.org/10.1002/2015wr018349"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "New England observed and predicted July stream/river temperature daily range points",
            "description": "The shapefile contains points with associated observed and predicted July stream/river temperature daily ranges in New England based on a spatial statistical network model published in Detenbeck et al. (2016): Detenbeck, N. E., Morrison, A., Abele, R. W. and Kopp, D. (2016), Spatial statistical network models for stream and river temperature in New England, USA. Water Resour. Res. Accepted Author Manuscript. doi:10.1002/2015WR018349). Portions of this dataset are inaccessible because: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). They can be accessed through the following means: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). Format: Shapefile. \n\nThis dataset is associated with the following publication:\nDetenbeck , N., A. Morrison, R. Abele , and D. Kopp. Spatial statistical network models for stream and river temperature in New England, USA.   WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 52: 6018\u20136040, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-j9kt-123",
            "keyword": [
                "spatial statistical network model",
                "streams",
                "rivers",
                "water temperature",
                "New England",
                "stormwater",
                "green infrastrucutre",
                "aquatic biota",
                "habitat"
            ],
            "contactPoint": {
                "fn": "Naomi Detenbeck",
                "hasEmail": "mailto:detenbeck.naomi@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/hesc/estuary-data-mapper-edm",
                    "accessURL": "https://www.epa.gov/hesc/estuary-data-mapper-edm"
                }
            ],
            "modified": "2015-09-10",
            "references": [
                "https://doi.org/10.1002/2015wr018349"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "New England observed and predicted August stream/river temperature daily range points",
            "description": "The shapefile contains points with associated observed and predicted August stream/river temperature daily ranges in New England based on a spatial statistical network model published in Detenbeck et al. (2016): Detenbeck, N. E., Morrison, A., Abele, R. W. and Kopp, D. (2016), Spatial statistical network models for stream and river temperature in New England, USA. Water Resour. Res. Accepted Author Manuscript. doi:10.1002/2015WR018349). Portions of this dataset are inaccessible because: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). They can be accessed through the following means: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). Format: Shapefile. \n\nThis dataset is associated with the following publication:\nDetenbeck , N., A. Morrison, R. Abele , and D. Kopp. Spatial statistical network models for stream and river temperature in New England, USA.   WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 52: 6018\u20136040, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-j9kt-124",
            "keyword": [
                "spatial statistical network model",
                "streams",
                "rivers",
                "water temperature",
                "New England",
                "stormwater",
                "green infrastrucutre",
                "aquatic biota",
                "habitat"
            ],
            "contactPoint": {
                "fn": "Naomi Detenbeck",
                "hasEmail": "mailto:detenbeck.naomi@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/hesc/estuary-data-mapper-edm",
                    "accessURL": "https://www.epa.gov/hesc/estuary-data-mapper-edm"
                }
            ],
            "modified": "2015-09-10",
            "references": [
                "https://doi.org/10.1002/2015wr018349"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "New England observed and predicted growing season maximum stream/river temperature points",
            "description": "The shapefile contains points with associated observed and predicted growing season maximum stream/river temperatures in New England based on a spatial statistical network model published in Detenbeck et al. (2016): Detenbeck, N. E., Morrison, A., Abele, R. W. and Kopp, D. (2016), Spatial statistical network models for stream and river temperature in New England, USA. Water Resour. Res. Accepted Author Manuscript. doi:10.1002/2015WR018349). Portions of this dataset are inaccessible because: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). They can be accessed through the following means: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). Format: Shapefile. \n\nThis dataset is associated with the following publication:\nDetenbeck , N., A. Morrison, R. Abele , and D. Kopp. Spatial statistical network models for stream and river temperature in New England, USA.   WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 52: 6018\u20136040, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-j9kt-125",
            "keyword": [
                "spatial statistical network model",
                "rivers",
                "streams",
                "New England",
                "stormwater",
                "green infrastrucutre",
                "aquatic biota",
                "habitat"
            ],
            "contactPoint": {
                "fn": "Naomi Detenbeck",
                "hasEmail": "mailto:detenbeck.naomi@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/hesc/estuary-data-mapper-edm",
                    "accessURL": "https://www.epa.gov/hesc/estuary-data-mapper-edm"
                }
            ],
            "modified": "2015-09-10",
            "references": [
                "https://doi.org/10.1002/2015wr018349"
            ],
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                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "New England observed and predicted Julian day of maximum growing season stream/river temperature points",
            "description": "The shapefile contains points with associated observed and predicted Julian day of maximum growing season stream/river temperatures in New England based on a spatial statistical network model published in Detenbeck et al. (2016): Detenbeck, N. E., Morrison, A., Abele, R. W. and Kopp, D. (2016), Spatial statistical network models for stream and river temperature in New England, USA. Water Resour. Res. Accepted Author Manuscript. doi:10.1002/2015WR018349). Portions of this dataset are inaccessible because: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). They can be accessed through the following means: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). Format: Shapefile. \n\nThis dataset is associated with the following publication:\nDetenbeck , N., A. Morrison, R. Abele , and D. Kopp. Spatial statistical network models for stream and river temperature in New England, USA.   WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 52: 6018\u20136040, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-j9kt-126",
            "keyword": [
                "spatial statistical network model",
                "rivers",
                "streams",
                "water temperature",
                "New England",
                "stormwater",
                "green infrastrucutre",
                "aquatic biota",
                "habitat"
            ],
            "contactPoint": {
                "fn": "Naomi Detenbeck",
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            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/hesc/estuary-data-mapper-edm",
                    "accessURL": "https://www.epa.gov/hesc/estuary-data-mapper-edm"
                }
            ],
            "modified": "2015-09-10",
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                    "subOrganizationOf": {
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                    }
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            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "New England observed and predicted July stream/river temperature maximum positive daily rate of change points",
            "description": "The shapefile contains points with associated observed and predicted July stream/river temperature maximum positive daily rate of change in New England based on a spatial statistical network model published in Detenbeck et al. (2016): Detenbeck, N. E., Morrison, A., Abele, R. W. and Kopp, D. (2016), Spatial statistical network models for stream and river temperature in New England, USA. Water Resour. Res. Accepted Author Manuscript. doi:10.1002/2015WR018349). Portions of this dataset are inaccessible because: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). They can be accessed through the following means: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). Format: Shapefile. \n\nThis dataset is associated with the following publication:\nDetenbeck , N., A. Morrison, R. Abele , and D. Kopp. Spatial statistical network models for stream and river temperature in New England, USA.   WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 52: 6018\u20136040, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-j9kt-127",
            "keyword": [
                "spatial statistical network model",
                "rivers",
                "streams",
                "New England",
                "water temperature",
                "stormwater",
                "green infrastrucutre",
                "aquatic biota",
                "habitat"
            ],
            "contactPoint": {
                "fn": "Naomi Detenbeck",
                "hasEmail": "mailto:detenbeck.naomi@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/hesc/estuary-data-mapper-edm",
                    "accessURL": "https://www.epa.gov/hesc/estuary-data-mapper-edm"
                }
            ],
            "modified": "2015-09-10",
            "references": [
                "https://doi.org/10.1002/2015wr018349"
            ],
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                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "New England observed and predicted August stream/river temperature maximum positive daily rate of change points",
            "description": "The shapefile contains points with associated observed and predicted August stream/river temperature maximum positive daily rate of change in New England based on a spatial statistical network model published in Detenbeck et al. (2016): Detenbeck, N. E., Morrison, A., Abele, R. W. and Kopp, D. (2016), Spatial statistical network models for stream and river temperature in New England, USA. Water Resour. Res. Accepted Author Manuscript. doi:10.1002/2015WR018349). Portions of this dataset are inaccessible because: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). They can be accessed through the following means: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). Format: Shapefile. \n\nThis dataset is associated with the following publication:\nDetenbeck , N., A. Morrison, R. Abele , and D. Kopp. Spatial statistical network models for stream and river temperature in New England, USA.   WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 52: 6018\u20136040, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-j9kt-128",
            "keyword": [
                "spatial statistical network model",
                "rivers",
                "streams",
                "New England",
                "water temperature",
                "stormwater",
                "green infrastrucutre",
                "aquatic biota",
                "habitat"
            ],
            "contactPoint": {
                "fn": "Naomi Detenbeck",
                "hasEmail": "mailto:detenbeck.naomi@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/hesc/estuary-data-mapper-edm",
                    "accessURL": "https://www.epa.gov/hesc/estuary-data-mapper-edm"
                }
            ],
            "modified": "2015-09-10",
            "references": [
                "https://doi.org/10.1002/2015wr018349"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "New England observed and predicted July maximum negative stream/river temperature daily rate of change points",
            "description": "The shapefile contains points with associated observed and predicted July stream/river temperature maximum negative daily rate of change in New England based on a spatial statistical network model published in Detenbeck et al. (2016): Detenbeck, N. E., Morrison, A., Abele, R. W. and Kopp, D. (2016), Spatial statistical network models for stream and river temperature in New England, USA. Water Resour. Res. Accepted Author Manuscript. doi:10.1002/2015WR018349). Portions of this dataset are inaccessible because: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). They can be accessed through the following means: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). Format: Shapefile. \n\nThis dataset is associated with the following publication:\nDetenbeck , N., A. Morrison, R. Abele , and D. Kopp. Spatial statistical network models for stream and river temperature in New England, USA.   WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 52: 6018\u20136040, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-j9kt-129",
            "keyword": [
                "spatial statistical network model",
                "rivers",
                "streams",
                "water temperature",
                "New England",
                "stormwater",
                "green infrastrucutre",
                "aquatic biota",
                "habitat"
            ],
            "contactPoint": {
                "fn": "Naomi Detenbeck",
                "hasEmail": "mailto:detenbeck.naomi@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/hesc/estuary-data-mapper-edm",
                    "accessURL": "https://www.epa.gov/hesc/estuary-data-mapper-edm"
                }
            ],
            "modified": "2015-09-10",
            "references": [
                "https://doi.org/10.1002/2015wr018349"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "New England observed and predicted August stream/river temperature maximum daily rate of change points",
            "description": "The shapefile contains points with associated observed and predicted August stream/river temperature maximum negative rate of change in New England based on a spatial statistical network model published in Detenbeck et al. (2016): Detenbeck, N. E., Morrison, A., Abele, R. W. and Kopp, D. (2016), Spatial statistical network models for stream and river temperature in New England, USA. Water Resour. Res. Accepted Author Manuscript. doi:10.1002/2015WR018349). Portions of this dataset are inaccessible because: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). They can be accessed through the following means: The dataset is being made available as part of a collection of stream/river temperature model results through EPA's Estuary Data Mapper (publically available application at www.epa.gov/edm for discovering, viewing and accessing geospatial data). Format: Shapefile. \n\nThis dataset is associated with the following publication:\nDetenbeck , N., A. Morrison, R. Abele , and D. Kopp. Spatial statistical network models for stream and river temperature in New England, USA.   WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 52: 6018\u20136040, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
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            "identifier": "A-j9kt-130",
            "keyword": [
                "spatial statistical network model",
                "rivers",
                "streams",
                "New England",
                "water temperature",
                "stormwater",
                "green infrastrucutre",
                "aquatic biota",
                "habitat"
            ],
            "contactPoint": {
                "fn": "Naomi Detenbeck",
                "hasEmail": "mailto:detenbeck.naomi@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/hesc/estuary-data-mapper-edm",
                    "accessURL": "https://www.epa.gov/hesc/estuary-data-mapper-edm"
                }
            ],
            "modified": "2015-09-10",
            "references": [
                "https://doi.org/10.1002/2015wr018349"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Gene expression and chemical exposure data for larval Pimephales promelas exposed to one of  four pyrethroid pesticides.",
            "description": "Uploaded datasets are detailed exposure information (chemical concentrations and water quality parameters) for exposures conducted in a flow through diluter system with larval Pimephales promelas to four different pyrethroid pesticides.  The GEO submission URL links to the NCBI GEO database and contains gene expression data from whole larvae exposed to different concentrations of the pyrethroids across multiple experiments. \n\nThis dataset is associated with the following publication:\nBiales, A., M. Kostich, A. Batt, M. See, R. Flick, D. Gordon, J. Lazorchak, and D. Bencic. Initial Development of a Multigene Omics-Based Exposure Biomarker for Pyrethroid Pesticides.   CRITICAL REVIEWS IN ENVIRONMENTAL SCIENCE AND TECHNOLOGY. CRC Press LLC, Boca Raton, FL, USA, 179(0): 27-35, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-mcvw-158",
            "keyword": [
                "transcriptomics",
                "biomarker",
                "fish",
                "pyrethroids"
            ],
            "contactPoint": {
                "fn": "Adam Biales",
                "hasEmail": "mailto:biales.adam@epa.gov"
            },
            "distribution": [
                {
                    "title": "Table 1 - Water Quality Parameters.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/158/Table%201%20-%20Water%20Quality%20Parameters.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table 2 - Phase 1 per tank per day chemistry.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/158/Table%202%20-%20Phase%201%20per%20tank%20per%20day%20chemistry.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table 3 - P2 Chemistry Results Per Day and Per Tank.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/158/Table%203%20-%20P2%20Chemistry%20Results%20Per%20Day%20and%20Per%20Tank.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table 4  - Functional Annotation Clustering_DAVID.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/158/Table%204%20%20-%20Functional%20Annotation%20Clustering_DAVID.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table 5 - Uncalibrated eAUCs.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/158/Table%205%20-%20Uncalibrated%20eAUCs.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table 6 CALIBRATED EAUCS.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/158/Table%206%20CALIBRATED%20EAUCS.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "https://www.ncbi.nlm.nih.gov/gquery/?term=GSE84475",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/gquery/?term=GSE84475"
                }
            ],
            "modified": "2016-07-13",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supplemental Information: Phototransformation-Induced Aggregation of Functionalized Single-Walled Carbon Nanotubes: the Importance of Amorphous Carbon",
            "description": "Additional information about the carboxylated SWCNT calibration curve, AFM images, EDS results, solar simulator light and UVB lamp spectra, TEM image of\nparent carboxylated SWCNTs, XPS spectra of the dark control P3 sample and the irradiated P3 sample, and a table summarizing the kinetic parameters (PDF). \n\nThis dataset is associated with the following publication:\nHou, W., C. He, Y. Wang, D. Wang, and R. Zepp. Phototransformation-Induced Aggregation of Functionalized Single-Walled Carbon Nanotubes: The Importance of Amorphous Carbon.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(7): 3494\u20133502, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-sqvz-330",
            "keyword": [
                "calibration curve",
                "AFM images",
                "EDS results",
                "lamp spectra",
                "TEM image",
                "XPS spectra",
                "kinetic parameters",
                "SWCNTs",
                "nanomaterials",
                "phototransformations",
                "amorphous carbon"
            ],
            "contactPoint": {
                "fn": "Richard Zepp",
                "hasEmail": "mailto:zepp.richard@epa.gov"
            },
            "distribution": [
                {
                    "title": "es5b04727_si_001.pd.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/330/es5b04727_si_001.pd.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2016-02-24",
            "references": [
                "https://doi.org/10.1021/acs.est.5b04727"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Database to support \"Quanitfying groundwater dependency of riparian surface hydrologic features using the exit gradient\" by Faulkner et al. 2016.",
            "description": "Collections of publically available secondary data used to develop the conclusions described in the journal article. \n\nThis dataset is associated with the following publication:\nFaulkner , B., S. Leibowitz , T. Canfield , and J. Groves. Quantifying groundwater dependency of riparian surface hydrologic features using the exit gradient.   Hydrological Processes. John Wiley & Sons, Ltd., Indianapolis, IN, USA,  1-11, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-d25g-384",
            "keyword": [
                "exit gradient",
                "basin fill aquifer",
                "shallow groundwater management",
                "wetland management",
                "groundwater dependency of ecosystem services",
                "exit gradient; basin fill aquifer; shallow groundwater management; wetland management; groundwater dependency"
            ],
            "contactPoint": {
                "fn": "Azadeh Azadpour-Keeley",
                "hasEmail": "mailto:keeley.ann@epa.gov"
            },
            "distribution": [
                {
                    "title": "cala_owrd_science_hub.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/384/cala_owrd_science_hub.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-09-26",
            "references": [
                "https://doi.org/10.1002/hyp.10766"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Towards Universal Screening for Toxoplasmosis: Rapid, Cost-effective and Simultaneous Detection of Toxoplasma Anti-IgG, IgM and IgA Antibodies Using Very Small Serum Volumes",
            "description": "No dataset associated with this publication. This dataset is not publicly accessible because: This is a commentary and no data was generated. It can be accessed through the following means: There is no data associated with this commentary. Format: This is a commentary and no data was generated. \n\nThis dataset is associated with the following publication:\nAugustine, S. Towards Universal Screening for Toxoplasmosis: Rapid, Cost-effective and Simultaneous Detection of Toxoplasma Anti-IgG, IgM and IgA Antibodies Using Very Small Serum Volumes.   JOURNAL OF CLINICAL MICROBIOLOGY. American Society for Microbiology, Washington, DC, USA, 56(7): 1-2, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-bzkt-293",
            "keyword": [
                "Toxoplasma gondii",
                "universal screening",
                "commentary"
            ],
            "contactPoint": {
                "fn": "Swinburne Augustine",
                "hasEmail": "mailto:augustine.swinburne@epa.gov"
            },
            "distribution": [],
            "modified": "2016-09-09",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": " Effects of Cr(III) and CR(VI) on nitrification inhibition as determined by SOUR, function-specific gene expression and 16S rRNA sequence analysis of wastewater nitrifying enrichments",
            "description": "Data generated to test nitrification inhibition of chromium. \n\nThis dataset is associated with the following publication:\nKapoor, V., M. Elk, X. Li, C. Impellitteri , and J. Santodomingo. Effects of Cr(III) and CR(VI) on nitrification inhibition as determined by SOUR, function-specific gene expression and 16S rRNA sequence analysis of wastewater nitrifying enrichments.   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 147: 361-367, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-bk3v-396",
            "keyword": [
                "nitrification",
                "RNA"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [
                {
                    "title": "cDNA CN-_061715.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/396/cDNA%20CN-_061715.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-03-01",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2015.12.119"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Conference Report: The 6th International Symposium on Waterborne Pathogens ",
            "description": "A review of current literature on the occurrence of waterborne pathogens in DW systems. This dataset is not publicly accessible because: I am using published data from a journal not generated by EPA. It can be accessed through the following means: N/A. Format: no unique data has been generated. \n\nThis dataset is associated with the following publication:\nRochelle, P., P. Klonicki, G. DiGiovanni, V. Hill, Y. Akagi, and E. Villegas. Conference Report: The 6th International Symposium on Waterborne Pathogens ISWP 2015.   JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA, 107(10): 24-32, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-2283-294",
            "keyword": [
                "drinking water",
                "drinking water distribution systems",
                "cryptosporidium",
                "Naeglaria",
                "legionella",
                "waterborne pathogens"
            ],
            "contactPoint": {
                "fn": "Eric Villegas",
                "hasEmail": "mailto:villegas.eric@epa.gov"
            },
            "distribution": [],
            "modified": "2016-09-21",
            "references": [
                "https://doi.org/10.5942/jawwa.2015.107.0156"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Human infective potential of Cryptosporidium spp., Giardia duodenalis and Enterocytozoon bieneusi in urban wastewater treatment plant effluents",
            "description": "Cryptosporidiosis, giardiasis, and microsporidiosis are important waterborne diseases. In the\nstandard for wastewater treatment plant (WWTP) effluents in China and other countries, fecal\ncoliform is the only microbial indicator, raising concerns about the potential for pathogen\ntransmission through WWPT effluent reuse. In this study, we collected 50 effluent samples\n(30 L/sample) from three municipal WWTPs in Shanghai, China and analyzed for Cryptosporidium\nspp., Giardia duodenalis and Enterocytozoon bieneusi by microscopy and/or PCR. Moreover,\npropidium monoazide (PMA)-PCR was used to assess the viability of oocysts/cysts. The microscopy\nand PCR-positive rates for Cryptosporidium spp. were 62% and 40%, respectively. The occurrence\nrates of G. duodenalis were 96% by microscopy and 92\u2013100% by PCR analysis of three genetic loci.\nFurthermore, E. bieneusi was detected in 70% (35/50) of samples by PCR. Altogether, ten\nCryptosporidium species or genotypes, two G. duodenalis genotypes, and 11 E. bieneusi genotypes\nwere found, most of which were human-pathogenic. The chlorine dioxide disinfection employed in\nWWTP1 and WWTP3 failed to inactivate the residual pathogens; 93% of the samples from WWTP1 and\n83% from WWTP3 did not meet the national standard on fecal coliform levels. Thus, urban WWTP\neffluents often contain residual waterborne human pathogens. \n\nThis dataset is associated with the following publication:\nMa, J., Y. Feng, Y. Hu, E. Villegas , and L. Xiao. Human infective potential of Cryptosporidium spp., Giardia duodenalis and Enterocytozoon bieneusi in urban wastewater treatment plant effluents.   JOURNAL OF WATER AND HEALTH. IWA Publishing, London,  UK, 14(4): 411-423, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-dfnd-295",
            "keyword": [
                "giardia",
                "cryptosporidium",
                "wastewater",
                "microsporidia",
                "wastewater treatment plant",
                "occurrence",
                "water reuse"
            ],
            "contactPoint": {
                "fn": "Eric Villegas",
                "hasEmail": "mailto:villegas.eric@epa.gov"
            },
            "distribution": [
                {
                    "title": "NO EPA DATASETS WERE GENERATED IN THIS STUDY.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/295/NO%20EPA%20DATASETS%20WERE%20GENERATED%20IN%20THIS%20STUDY.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-09-21",
            "references": [
                "http://jwh.iwaponline.com/content/early/2016/01/04/wh.2016.192"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Detection and Quantification of Silver Nanoparticles at Environmentally Relevant Concentrations Using Asymmetric Flow Field\u2212Flow Fractionation Online with Single Particle Inductively Coupled Plasma Mass Spectrometry",
            "description": "The presence of silver nanoparticles (AgNPs) in aquatic environments could potentially cause adverse impacts on ecosystems and human health.  However, current understanding of the environmental fate and transport of AgNPs is still limited because their properties in complex environmental samples cannot be accurately determined.  In this study, the feasibility of using asymmetric flow field-flow fractionation (AF4) connected online with single particle inductively coupled plasma mass spectrometry (spICPMS) to detect and quantify AgNPs at environmentally relevant concentrations was investigated.  The AF4 channel had a thickness of 350 \u00b5m and its accumulation wall was a 10 kDa regenerated cellulose membrane.  A 0.02 % FL-70 surfactant solution was used as an AF4 carrier.  With 1.2 mL/min AF4 cross flow rate, 1.5 mL/min AF4 channel flow rate, and 5 ms spICPMS dwell time, the AF4\u2013spICPMS can detect and quantify 40 \u2013 80 nm AgNPs, as well as Ag-SiO2 nanoparticles (51.0 nm diameter Ag core and 21.6 nm SiO2 shell), with good recovery within 30 min.  This system was not only effective in differentiating and quantifying different types of AgNPs with similar hydrodynamic diameters, such as in mixtures containing Ag-SiO2 core-shell nanoparticles and 40 \u2013 80 nm AgNPs, but also suitable for differentiating between 40 nm AgNPs and elevated dissolved Ag content.  The study results indicate that AF4\u2013spICPMS is capable of detecting and quantifying AgNPs and other engineered metal- nanomaterials in environmental samples.  Nevertheless, further studies are needed before AF4\u2013spICPMS can become a routine analytical technique. \n\nThis dataset is associated with the following publication:\nHuynh, K.A., E. Siska, E. Heithmar, S. Tadjiki, and S. Pergantis. Detection and Quantification of Silver Nanoparticles at Environmentally Relevant Concentrations Using Asymmetric Flow Field\u2013Flow Fractionation Online with Single Particle Inductively Coupled Plasma Mass Spectrometry.   Analytical Chemistry. American Chemical Society, Washington, DC, USA, 88(9): 4909\u20134916, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-n2zk-210",
            "keyword": [
                "Silver",
                "particle size distribution",
                "Nanoparticles",
                "detection",
                "characterization",
                "environmental matrices"
            ],
            "contactPoint": {
                "fn": "Edward Heithmar",
                "hasEmail": "mailto:heithmar.ed@epa.gov"
            },
            "distribution": [
                {
                    "title": "20160407 - Revised Supporting Information_Final.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/210/20160407%20-%20Revised%20Supporting%20Information_Final.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2016-04-11",
            "references": [
                "http://pubs.acs.org/doi/abs/10.1021/acs.analchem.6b00764"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/210/documents/Data%20Dictionary%20for%20Supporting%20Information.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "High-throughput screening of chemical effects on steroidogenesis using H295R human adrenocortical carcinoma cells",
            "description": "Disruption of steroidogenesis by environmental chemicals can result in altered hormone levels causing adverse reproductive and developmental effects. A high-throughput assay using H295R human adrenocortical carcinoma cells was used to evaluate the effect of 2060 chemical samples on steroidogenesis via high-performance liquid chromatography followed by tandem mass spectrometry quantification of 10 steroid hormones, including progestagens, glucocorticoids, androgens, and estrogens. The study employed a 3 stage screening strategy. The first stage established the maximum tolerated concentration (MTC; \u2265 70% viability) per sample. The second stage quantified changes in hormone levels at the MTC whereas the third stage performed concentration-response (CR) on a subset of samples. At all stages, cells were prestimulated with 10 \u00b5M forskolin for 48\u2009h to induce steroidogenesis followed by chemical treatment for 48\u2009h. Of the 2060 chemical samples evaluated, 524 samples were selected for 6-point CR screening, based in part on significantly altering at least 4 hormones at the MTC. CR screening identified 232 chemical samples with concentration-dependent effects on 17\u03b2-estradiol and/or testosterone, with 411 chemical samples showing an effect on at least one hormone across the steroidogenesis pathway. Clustering of the concentration-dependent chemical-mediated steroid hormone effects grouped chemical samples into 5 distinct profiles generally representing putative mechanisms of action, including CYP17A1 and HSD3B inhibition. A distinct pattern was observed between imidazole and triazole fungicides suggesting potentially distinct mechanisms of action. From a chemical testing and prioritization perspective, this assay platform provides a robust model for high-throughput screening of chemicals for effects on steroidogenesis. \n\nThis dataset is associated with the following publication:\nKarmaus , A., C. Toole, D. Filer , K. Lewis, and M. Martin. (Toxicological Sciences) High-throughput screening of chemical effects on steroidogenesis using H295R human adrenocortical carcinoma cells.   TOXICOLOGICAL SCIENCES. Society of Toxicology,    150(2): 323-332, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-x0kx-385",
            "keyword": [
                "cancer",
                "steroidogenesis",
                "chemical safety for sustainablity",
                "chemical safety research",
                "high-throughput toxicology",
                "ToxCast",
                "computational toxicology"
            ],
            "contactPoint": {
                "fn": "Keith Houck",
                "hasEmail": "mailto:houck.keith@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/MartinMatt/ToxCast_Steroidogenesis/",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/MartinMatt/ToxCast_Steroidogenesis/"
                }
            ],
            "modified": "2016-04-02",
            "references": [
                "https://doi.org/10.1093/toxsci/kfw002"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Using ToxCast data to reconstruct dynamic cell state trajectories and estimate toxicological points of departure.",
            "description": "Background: High-content imaging (HCI) allows simultaneous measurement of multiple cellular phenotypic changes and is an important tool for evaluating the biological activity of chemicals.\r\nObjectives: Our goal was to analyze dynamic cellular changes using HCI to identify the \u201ctipping point\u201d at which the cells did not show recovery towards a normal phenotypic state.\r\nMethods: HCI was used to evaluate the effects of 967 chemicals (in concentrations ranging from 0.4 to 200 \u03bcM) on HepG2 cells over a 72-hr exposure period. The HCI end points included p53, c-Jun, histone H2A.x, \u03b1-tubulin, histone H3, alpha tubulin, mitochondrial membrane potential, mitochondrial mass, cell cycle arrest, nuclear size, and cell number. A computational model was developed to interpret HCI responses as cell-state trajectories.\r\nResults: Analysis of cell-state trajectories showed that 336 chemicals produced tipping points and that HepG2 cells were resilient to the effects of 334 chemicals up to the highest concentration (200 \u03bcM) and duration (72 hr) tested. Tipping points were identified as concentration-dependent transitions in system recovery, and the corresponding critical concentrations were generally between 5 and 15 times (25th and 75th percentiles, respectively) lower than the concentration that produced any significant effect on HepG2 cells. The remaining 297 chemicals require more data before they can be placed in either of these categories.\r\nConclusions: These findings show the utility of HCI data for reconstructing cell state trajectories and provide insight into the adaptation and resilience of in vitro cellular systems based on tipping points. Cellular tipping points could be used to define a point of departure for risk-based prioritization of environmental chemicals. \n\nThis dataset is associated with the following publication:\nShah , I., W. Setzer , J. Jack, K. Houck , R. Judson , T. Knudsen , J. Liu, M. Martin , D. Reif, A.M. Richard , R.S. Thomas , K. Crofton , D.J. Dix , and R.J. Kavlock. (Envir. Health Perspect.)   Using ToxCast data to reconstruct dynamic cell state trajectories and estimate toxicological points of departure.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA,  1-33, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-dncw-386",
            "keyword": [
                "ToxCast",
                "virtual embryo",
                "virtual tissues",
                "virtual liver",
                "tipping points"
            ],
            "contactPoint": {
                "fn": "Thomas Knudsen",
                "hasEmail": "mailto:knudsen.thomas@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/ShahImran/PODTipping_Point/",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/ShahImran/PODTipping_Point/"
                }
            ],
            "modified": "2016-07-01",
            "references": [
                "https://doi.org/10.1289/ehp.1409029"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Rumsey and Walker_AMT_2016_Table 1",
            "description": "Table summarizes instrument analytical detection limits, including liquid and equivalent air concentrations. \n\nThis dataset is associated with the following publication:\nRumsey, I. Application of an online ion chromatography-based instrument for gradient flux measurements of speciated nitrogen and sulfur.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 9(6): 2581-2592, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-fn3b-392",
            "keyword": [
                "detection limit",
                "MARGA",
                "nitrogen",
                "deposition",
                "bidirectional flux",
                "sulfur",
                "micrometeorology"
            ],
            "contactPoint": {
                "fn": "John Walker",
                "hasEmail": "mailto:walker.johnt@epa.gov"
            },
            "distribution": [
                {
                    "title": "Rumsey and Walker_AMT_2016_Table 1.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/392/Rumsey%20and%20Walker_AMT_2016_Table%201.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-17",
            "references": [
                "https://doi.org/10.5194/amt-9-2581-2016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Rumsey and Walker_AMT_2016_Table 2.xlsx",
            "description": "Table summarizes instrument precision assessed by collocating the two sample boxes. Precision is quantified as the standard deviation of the residuals of an orthogonal least squares regression of concentrations from the two sample boxes. This allows for an estimation of gradient precision and ultimately gradient and flux detection limits. \n\nThis dataset is associated with the following publication:\nRumsey, I. Application of an online ion chromatography-based instrument for gradient flux measurements of speciated nitrogen and sulfur.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 9(6): 2581-2592, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-fn3b-393",
            "keyword": [
                "flux detection limit",
                "gradient detection limit",
                "colocation",
                "orthogonal least squares",
                "MARGA",
                "nitrogen",
                "deposition",
                "bidirectional flux",
                "sulfur",
                "micrometeorology"
            ],
            "contactPoint": {
                "fn": "John Walker",
                "hasEmail": "mailto:walker.johnt@epa.gov"
            },
            "distribution": [
                {
                    "title": "Rumsey and Walker_AMT_2016_Table 2.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/393/Rumsey%20and%20Walker_AMT_2016_Table%202.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-17",
            "references": [
                "https://doi.org/10.5194/amt-9-2581-2016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Rumsey and Walker_AMT_2016_Figure 1.xlsx",
            "description": "Figure summarizes diurnal profiles of uncertainty in the chemical gradient and transfer velocity measurements from which fluxes are calculated. \n\nThis dataset is associated with the following publication:\nRumsey, I. Application of an online ion chromatography-based instrument for gradient flux measurements of speciated nitrogen and sulfur.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 9(6): 2581-2592, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-fn3b-399",
            "keyword": [
                "gradient uncertainty",
                "transfer velocity",
                "nitrogen",
                "deposition",
                "bidirectional flux",
                "sulfur",
                "micrometeorology"
            ],
            "contactPoint": {
                "fn": "John Walker",
                "hasEmail": "mailto:walker.johnt@epa.gov"
            },
            "distribution": [
                {
                    "title": "Rumsey and Walker_AMT_2016_Figure 1.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/399/Rumsey%20and%20Walker_AMT_2016_Figure%201.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-17",
            "references": [
                "https://doi.org/10.5194/amt-9-2581-2016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Rumsey and Walker_AMT_2016_Figure 2.xlsx",
            "description": "Figure summarizes uncertainty (error) in hourly gradient flux measurements by individual analyte. Flux uncertainty is derived from estimates of uncertainty in chemical gradients and turbulent transfer velocity. \n\nThis dataset is associated with the following publication:\nRumsey, I. Application of an online ion chromatography-based instrument for gradient flux measurements of speciated nitrogen and sulfur.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 9(6): 2581-2592, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-fn3b-400",
            "keyword": [
                "flux uncertaintly",
                "flux gradient method",
                "MARGA",
                "nitrogen",
                "deposition",
                "bidirectional flux",
                "sulfur",
                "micrometeorology"
            ],
            "contactPoint": {
                "fn": "John Walker",
                "hasEmail": "mailto:walker.johnt@epa.gov"
            },
            "distribution": [
                {
                    "title": "Rumsey and Walker_AMT_2016_Figure 2.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/400/Rumsey%20and%20Walker_AMT_2016_Figure%202.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-17",
            "references": [
                "https://doi.org/10.5194/amt-9-2581-2016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Draft genome sequence of two Shingopyxis sp. strains H107 and H115 isolated from a chloraminated drinking water distriburion system simulator",
            "description": "Draft genome sequence of two Shingopyxis sp. strains H107 and H115 isolated from a chloraminated drinking water distriburion system simulator. \n\nThis dataset is associated with the following publication:\nGomez-Alvarez, V., S. Pfaller , and R. Revetta. Draft Genome of Two Sphingopyxis sp. Strains, Dominant Members of the Bacterial Community Associated with a Drinking Water Distribution System Simulator.   Genome Announcements. American Society for Microbiology, Washington, DC, USA, 4(2): e00183-16, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-kps7-405",
            "keyword": [
                "drinkig water",
                "genome",
                "Shingopyxis",
                "antibiotic resistance",
                "genes",
                "drinking water",
                "Sphingopyxis"
            ],
            "contactPoint": {
                "fn": "Randy Revetta",
                "hasEmail": "mailto:revetta.randy@epa.gov"
            },
            "distribution": [
                {
                    "title": "H107.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/405/H107.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "H115.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/405/H115.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "https://www.ncbi.nlm.nih.gov/genbank/",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/genbank/"
                }
            ],
            "modified": "2016-02-01",
            "references": [
                "https://doi.org/10.1128/genomea.00183-16"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Bench-Scale and Pilot-Scale Treatment Technologies for the Removal of Total Dissolved Solids from Coal Mine Water: A Review.  ",
            "description": "There is no database. This dataset is not publicly accessible because: This is a review manuscript, there was not data generated under this effort. All data used was secondary data and sources of the data were identified in the manuscript. It can be accessed through the following means: there is no database. Format: There is no database. \n\nThis dataset is associated with the following publication:\nPinto, P., S. Al-Abed , D. Balz, B. Butler , R. Landy , and S. Smith. Bench-Scale and Pilot-Scale Treatment Technologies for the Removal of Total Dissolved Solids from Coal Mine Water: A Review.  Robert Kleinmann  Mine Water and the Environment. Springer-Verlag, BERLIN-HEIDELBERG,  GERMANY, 35(1): 94-112, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-rr5h-406",
            "keyword": [
                "There is no database",
                "adsorption",
                "bioremediation",
                "desalination",
                "distillation",
                "ion exchange",
                "precipitation",
                "reverse osmosis"
            ],
            "contactPoint": {
                "fn": "Souhail Al-Abed",
                "hasEmail": "mailto:al-abed.souhail@epa.gov"
            },
            "distribution": [],
            "modified": "2016-09-28",
            "references": [
                "https://doi.org/10.1007/s10230-015-0351-7"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset of Atmospheric Environment Publication in 2016, Characterization of organophosphorus flame retardants\u2019 sorption on building materials and consumer products",
            "description": "The data presented in this data file is a product of a journal publication. The dataset contains OPFR sorption concentrations on building materials and consumer products and comparison to the i-SVOC model predictions. \n\nThis dataset is associated with the following publication:\nLiu , X., M. Allen, and N. Roache. Characterization of organophosphorus flame retardants' sorption on building materials and consumer products.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 140: 333-341, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-6q5d-164",
            "keyword": [
                "TCPP",
                "TCEP",
                "TDCPP",
                "Sorption concentration",
                "OPFRs",
                "Organophosphorus flame retardants",
                "Material-air partition coefficient",
                "Material-phase diffusion coefficient",
                "Sink"
            ],
            "contactPoint": {
                "fn": "Xiaoyu Liu",
                "hasEmail": "mailto:liu.xiaoyu@epa.gov"
            },
            "distribution": [
                {
                    "title": "XiaoyuLiu_A-6q5d_Data Tables&Dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/164/XiaoyuLiu_A-6q5d_Data%20Tables%26Dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-04",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2016.06.019"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Gulf of Mexico Nutrient, carbon, CTD data",
            "description": "Gulf of Mexico cruise, nearshore and CTD data collected by the USEPA during 2002 - 2008. \n\nThis dataset is associated with the following publications:\nPauer , J., T. Feist, A. Anstead, P. DePetro, W. Melendez, J. Lehrter , M. Murrell , X. Zhang, and D. Ko. A modeling study examining the impact of nutrient boundaries on primary production on the Louisiana Continental Shelf.   ECOLOGICAL MODELLING. Elsevier Science BV, Amsterdam,  NETHERLANDS, 328: 136-147, (2016).\nFeist, T., J. Pauer , W. Melendez, J. Lehrter , P. DePetro, K. Rygwelski , D. Ko, and R. Kreis. Modeling the relative importance of nutrient and carbon loads, boundary fluxes, and sediment fluxes on Gulf of Mexico hypoxia.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(16): 88713-8721, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-76hn-404",
            "keyword": [
                "Gulf of Mexico",
                "Hypoxia",
                "nutrients",
                "CTD",
                "Nutrient loadings"
            ],
            "contactPoint": {
                "fn": "James Pauer",
                "hasEmail": "mailto:pauer.james@epa.gov"
            },
            "distribution": [
                {
                    "title": "GED GoM Nutrients for Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/404/GED%20GoM%20Nutrients%20for%20Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "EPA_GED_INSHORE for Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/404/EPA_GED_INSHORE%20for%20Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "GED GoM CTD for Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/404/GED%20GoM%20CTD%20for%20Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-27",
            "references": [
                "https://doi.org/10.1016/j.ecolmodel.2016.02.007",
                "https://doi.org/10.1021/acs.est.6b01684"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset of Building and Environment Publication in 2016, A reference method for measuring emissions of SVOCs in small chambers ",
            "description": "The data presented in this data file is a product of a journal publication. The dataset contains DEHP air concentrations in the emission test chamber. \n\nThis dataset is associated with the following publication:\nWu, Y., S. Cox, Y. Xu, Y. Liang, D. Wong, X. Liu, J. Benning, P. Clausen, Y. Zhang, C. Liu, and J. Little. A Reference Method for Measuring Emissions of SVOCs in Small Chambers.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 95: 126-132, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-pk16-188",
            "keyword": [
                "Semi-volatile organic compounds",
                "DEHP",
                "Phthalates",
                "Inter-laboratory study",
                "Reference method"
            ],
            "contactPoint": {
                "fn": "Xiaoyu Liu",
                "hasEmail": "mailto:liu.xiaoyu@epa.gov"
            },
            "distribution": [
                {
                    "title": "XiaoyuLiu_A-pk16_Data Tables&Dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/188/XiaoyuLiu_A-pk16_Data%20Tables%26Dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-12",
            "references": [
                "https://doi.org/10.1016/j.buildenv.2015.08.025"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset of Atmospheric Environment Publication in 2016, Source emission and model evaluation of formaldehyde from composite and solid wood furniture in a full-scale chamber ",
            "description": "The data presented in this data file is a product of a journal publication. The dataset contains formaldehyde air concentrations in the emission test chamber and source emission model simulation results. \n\nThis dataset is associated with the following publication:\nLiu , X., M. Mason , Z. Guo , K. Krebs , and N. Roache. Source emission and model evaluation of formaldehyde from composite and solid wood furniture in a full-scale chamber.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 122: 561-568, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-2bvs-189",
            "keyword": [
                "HCHO",
                "emission factor",
                "Formaldehyde",
                "Emissions from furnishings",
                "Source emission model",
                "Full-scale chamber",
                "First-order decay model",
                "Power-law decay model"
            ],
            "contactPoint": {
                "fn": "Xiaoyu Liu",
                "hasEmail": "mailto:liu.xiaoyu@epa.gov"
            },
            "distribution": [
                {
                    "title": "XiaoyuLiu_A-2bvs_Data Tables&Dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/189/XiaoyuLiu_A-2bvs_Data%20Tables%26Dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-12",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2015.09.062"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed",
            "description": "Changes in climate and land cover are among the principal variables affecting watershed hydrology.\nThis paper uses a cell-based model to examine the hydrologic impacts of climate and land-cover changes in the\nsemi-arid Lower Virgin River (LVR) watershed located upstream of Lake Mead, Nevada, USA. The cell-based\nmodel is developed by considering direct runoff based on the Soil Conservation Service - Curve Number (SCSCN)\nmethod and surplus runoff based on the Thornthwaite water balance theory. After calibration and validation,\nthe model is used to predict LVR discharge under future climate and land-cover changes. The hydrologic\nsimulation results reveal climate change as the dominant factor and land-cover change as a secondary factor in\nregulating future river discharge. The combined effects of climate and land-cover changes will slightly increase\nriver discharge in summer but substantially decrease discharge in winter. This impact on water resources deserves\nattention in climate change adaptation planning. \n\nThis dataset is associated with the following publication:\nChen, H., S. Tong, H. Yang, and J. Yang. Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed.   Hydrological Sciences Journal. IAHS LIMITED, Oxford,  UK, 60(10): 1739-1758, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-v6xk-362",
            "keyword": [
                "land-cover change; climate change adaptation; hydrologic impacts; cell-based modeling",
                "Regional adaptation case studies for sustainable water resources"
            ],
            "contactPoint": {
                "fn": "Yingping Yang",
                "hasEmail": "mailto:yang.jeff@epa.gov"
            },
            "distribution": [
                {
                    "title": "Lake Mead_Colorado River_ Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/362/Lake%20Mead_Colorado%20River_%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "NCDC_Monthly Climate Data_LowerVStations.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/362/NCDC_Monthly%20Climate%20Data_LowerVStations.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2015-12-09",
            "references": [
                "http://www.tandfonline.com/doi/abs/10.1080/02626667.2014.948445#preview"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Water consumption estimates of the biodiesel process in the US",
            "description": "Electronic supplementary material The online version of this\narticle (doi:10.1007/s10098-015-1032-8) contains supplementary\nmaterial, which is available to authorized users. \n\nThis dataset is associated with the following publication:\nTu, Q., M. Lu, J. Yang , and D. Scott. Water Consumption Estimates of Biodiesel Process in the US.   CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY. Springer-Verlag, New York, NY, USA, 18(2): 507-516, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-4mwc-358",
            "keyword": [
                "biodiesel",
                "Water consumption",
                "Irrigation"
            ],
            "contactPoint": {
                "fn": "Yingping Yang",
                "hasEmail": "mailto:yang.jeff@epa.gov"
            },
            "distribution": [
                {
                    "title": "Supporting Information_Final_7000_sub.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/358/Supporting%20Information_Final_7000_sub.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Tu et al (15) Wat consumption of biofuel in US.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/358/Tu%20et%20al%20%2815%29%20Wat%20consumption%20of%20biofuel%20in%20US.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2016-02-29",
            "references": [
                "http://link.springer.com/article/10.1007%2Fs10098-015-1032-8"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": " Near-road ultrafine particle and carbon monoxide measurements at North Carolina locations with and without roadside barriers",
            "description": "These data are measurement time series collected onboard multiple mobile monitoring vehicles.  The data are at a high time resolution (seconds to minutes). \n\nThis dataset is associated with the following publication:\nLin, M., G. Hagler , R. Baldauf , V. Isakov , and A. Khlystov. The Effects of Vegetation Barriers on Near-road Ultrafine Particle Number and Carbon Monoxide Concentrations.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 553: 372-379, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-djhn-218",
            "keyword": [
                "near-road",
                "vegetation",
                "mitigation",
                "air quality"
            ],
            "contactPoint": {
                "fn": "Gayle Hagler",
                "hasEmail": "mailto:hagler.gayle@epa.gov"
            },
            "distribution": [
                {
                    "title": "Hagler_SDMP_DataDictionary.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/218/Hagler_SDMP_DataDictionary.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "datasets.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/218/datasets.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-08-22",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.02.035"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data Set for Characterization of nanoparticles in wood based consumer products",
            "description": "The data include is for all of the tables and figures associated with the published journal article. \n\nThis dataset is associated with the following publication:\nPlatten, W., N. Sylvest, C. Warren, M. Arambewela, S. Harmon , K. Bradham, K. Rogers, T. Thomas, and T. Luxton. Estimating Dermal Exposure to Copper Nanoparticles from the Surfaces of Pressure-Treated Lumber and Implications for Toxicity.  D. Barcelo Culleres, and J. Gan  SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 548: 441-449, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-8w9r-391",
            "keyword": [
                "Pressure-treated Wood",
                "Nanoparticle",
                "Copper Exposure",
                "Micronized Copper Azole",
                "Ionic Copper",
                "Copper Speciation"
            ],
            "contactPoint": {
                "fn": "Todd Luxton",
                "hasEmail": "mailto:luxton.todd@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data-Set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/391/Data-Set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-12-01",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2015.12.108"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Influence of reservoir water-level fluctuations on mercury methylation downstream of the historic Black Butte mercury mine, OR.",
            "description": "The data set contains the raw data used to develop the figures and tables associated with the published manuscript. \n\nThis dataset is associated with the following publication:\nEckley , C., T. Luxton , J. McKernan , J. Goetz , and J. Goulet. Influence of Reservoir Water-Level Fluctuations on Mercury Methylation Downstream of the Historic Black Butte Mercury Mine, OR.  Michael Kersten  APPLIED GEOCHEMISTRY. Elsevier Science Ltd, New York, NY, USA, 61: 284-293, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-bp03-408",
            "keyword": [
                "mercury",
                "methylmercury",
                "reservoir",
                ": aqueous chemistry",
                "sediment",
                "mining"
            ],
            "contactPoint": {
                "fn": "Todd Luxton",
                "hasEmail": "mailto:luxton.todd@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data-Set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/408/Data-Set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-10-21",
            "references": [
                "https://doi.org/10.1016/j.apgeochem.2015.06.011"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The evaluation of hollow-fiber ultrafiltration and celite concentration of enteroviruses, adenoviruses and bacteriophage from different water matrices",
            "description": "The data to support the evaluation of hollow-fiber ultrafiltration and celite concentration of enteroviruses, adenoviruses and bacteriophage from different water matrices. \n\nThis dataset is associated with the following publication:\nRhodes , E., E. Huff, D. Hamilton, and J. Jones. The evaluation of hollow-fiber ultrafiltration and celite concentration of enteroviruses, adenoviruses and bacteriophage from different water matrices.   JOURNAL OF VIROLOGICAL METHODS. Elsevier Science Ltd, New York, NY, USA, 228(2): 31-38, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-cc2s-279",
            "keyword": [
                "Ultrafiltration",
                "Viruses",
                "Bacteriophage",
                "Water Concentration"
            ],
            "contactPoint": {
                "fn": "Eric Rhodes",
                "hasEmail": "mailto:rhodes.eric@epa.gov"
            },
            "distribution": [
                {
                    "title": "HFUF Virus Summary Table (1).xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/279/HFUF%20Virus%20Summary%20Table%20%281%29.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-06-01",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Complete Genome of Stachybotrys chartarum strain 51-11",
            "description": "Complete genome sequence of the fungus Stachybotrys chartarum.  Sequences can be used to identify genes, genetic pathways, gene clusters, genetic organization, etc. utilizing appropriate bioinformatics software. \n\nThis dataset is associated with the following publication:\nBetancourt , D., T. Dean , J. Kim, and J. Levy. Genome sequence of Stachybotrys chartarum Strain 51-11.   Genome Announcements. American Society for Microbiology, Washington, DC, USA, 3(6): 1114-1115, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-jq2s-68",
            "keyword": [
                "stachybotrys chartarum",
                "complete genome",
                "fungi",
                "genome",
                "indoor biocontaminants"
            ],
            "contactPoint": {
                "fn": "Timothy Dean",
                "hasEmail": "mailto:dean.timothy@epa.gov"
            },
            "distribution": [
                {
                    "title": "Schartarum5111_hybrid_illumina_pacbio.fasta.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/68/Schartarum5111_hybrid_illumina_pacbio.fasta.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "https://www.ncbi.nlm.nih.gov/Traces/wgs/wgsviewer.cgi?val=LDEE01&search=LDEE01000000&display=contigs",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/Traces/wgs/wgsviewer.cgi?val=LDEE01&search=LDEE01000000&display=contigs"
                }
            ],
            "modified": "2015-10-01",
            "references": [
                "https://doi.org/10.1128/genomea.01114-15"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Raw data used to generate figures 2 through 6 in Biological Responses of Raw 264.7 Macrophage Exposed to Two Strains of Stachybotrys chartarum Spores Grown on Four Different Wallboard Types manuscript.",
            "description": "Excel files containing raw data used to generate figures throughout manuscript. \n\nThis dataset is associated with the following publication:\nDean , T., D. Betancourt , J. Kim, L. Harvey, A. Evans, and B. Grace. Biological Responses of Raw 264.7 Macrophage Exposed to Two Strains of Stachybotrys chartarum Spores Grown on Four Different Wallboard Types.   INHALATION TOXICOLOGY. Taylor & Francis, Inc., Philadelphia, PA, USA, 28(7): 303-307, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-8w9q-74",
            "keyword": [
                "Raw 264.7 cells",
                "ApoTox-Glo",
                "Stachybotrys",
                "cytokine",
                "MHC Class II",
                "stachybotrys chartarum",
                "macrophage",
                "toxicity",
                "wallboard"
            ],
            "contactPoint": {
                "fn": "Timothy Dean",
                "hasEmail": "mailto:dean.timothy@epa.gov"
            },
            "distribution": [
                {
                    "title": "Biological Response Raw Data in Excel format.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/74/Biological%20Response%20Raw%20Data%20in%20Excel%20format.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-03-13",
            "references": [
                "https://doi.org/10.3109/08958378.2016.1170909"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Water quality modeling in the dead end sections of drinking water (Supplement)",
            "description": "Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to\ncalibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations in flow demands on the simulation accuracy.\nA set of three correction factors were analytically derived to adjust residence time, dispersion rate and wall demand to overcome simulation error caused by spatial aggregation approximation. The current model results show better agreement with field-measured concentrations of conservative fluoride tracer and free chlorine disinfectant than the simulations of recent advection dispersion reaction models\npublished in the literature. Accuracy of the simulated concentration profiles showed significant dependence on the spatial distribution of the flow demands compared to temporal variation. \n\nThis dataset is associated with the following publication:\nAbokifa, A., J. Yang , C. Lo, and P. Biswas. Water Quality Modeling in the Dead End Sections of Drinking Water Distribution Networks.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 18(89): 107-117, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-h9wf-367",
            "keyword": [
                "Chlorine",
                "Dead end pipe",
                "Advection dispersion",
                "Genetic algorithm",
                "Stochastic demands",
                "Spatial distribution",
                "Correction factors"
            ],
            "contactPoint": {
                "fn": "Yingping Yang",
                "hasEmail": "mailto:yang.jeff@epa.gov"
            },
            "distribution": [
                {
                    "title": "Supplementary Material_Final_YangYingping_A-h9wf_20160921.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/367/Supplementary%20Material_Final_YangYingping_A-h9wf_20160921.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Abokifa et al (16) Deadend model.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/367/Abokifa%20et%20al%20%2816%29%20Deadend%20model.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2015-12-14",
            "references": [
                "https://www.researchgate.net/publication/284233815_Water_Quality_Modeling_in_the_Dead_End_Sections_of_Drinking_Water_Distribution_Networks"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": " Metabolic and genomic analysis elucidates strain-level variation in Microbacterium spp. isolated from chromate contaminated sediment",
            "description": "The data is in the form of genomic sequences deposited in a public database, growth curves, and bioinformatic analysis of sequences. \n\nThis dataset is associated with the following publication:\nHenson, M., J. Santodomingo , P. Kourtev, R. Jensen, and D. Learman. Metabolic and genomic analysis elucidates strain-level variation in Microbacterium spp. isolated from chromate contaminated sediment.   PeerJ. PeerJ Inc., Corte Madera, CA, USA,  e1395, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-80gk-394",
            "keyword": [
                "heavy metal",
                "genomics"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [
                {
                    "title": "Henson et al dataset.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/394/Henson%20et%20al%20dataset.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2015-04-01",
            "references": [
                "https://doi.org/10.7717/peerj.1395"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Phosphate adsorption using modified iron oxide-based sorbents",
            "description": "Phosphate Removal. \n\nThis dataset is associated with the following publication:\nLalley , J., C. Han , G. RamMohan , T. Speth , J. Garland , M. Nadagouda , and D. Dionysiou. Phosphate Removal using Modified Bayoxide\u00aeE33 Adsorption Media.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, issue}: 96-107, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-51cb-351",
            "keyword": [
                "Phosphate Removal",
                "nutrients",
                "adsorption",
                "Nutrient removal/recovery"
            ],
            "contactPoint": {
                "fn": "Mallikarjuna Nadagouda",
                "hasEmail": "mailto:nadagouda.mallikarjuna@epa.gov"
            },
            "distribution": [
                {
                    "title": "Supplemental.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/351/Supplemental.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-09-19",
            "references": [
                "http://pubs.rsc.org/en/Content/ArticleLanding/2015/EW/c4ew00020j#divAbstract"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/351/documents/Supplemental.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": " Measuring nitrification inhibition in wastewater treatment systems: current state of science and fundamental research needs",
            "description": "There is no data as no experiments were conducted (literature review). \n\nThis dataset is associated with the following publication:\nLi , X., V. Kapoor , C. Impellitteri , and K. Chandran. Measuring nitrification inhibition in wastewater treatment systems: current state of science and fundamental research needs.   CRITICAL REVIEWS IN ENVIRONMENTAL SCIENCE AND TECHNOLOGY. CRC Press LLC, Boca Raton, FL, USA, 46(3): 249-289, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-79cw-397",
            "keyword": [
                "nitrification inhibition",
                "nitrification",
                "sequence"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [
                {
                    "title": "Li et al dataset.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/397/Li%20et%20al%20dataset.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-09-01",
            "references": [
                "https://doi.org/10.1080/10643389.2015.1085234"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "NLCD 2011 database",
            "description": "National Land Cover Database 2011 (NLCD 2011) is the most recent national land cover product created by the Multi-Resolution Land Characteristics (MRLC) Consortium. NLCD 2011 provides - for the first time - the capability to assess wall-to-wall, spatially explicit, national land cover changes and trends across the United States from 2001 to 2011. As with two previous NLCD land cover products NLCD 2011 keeps the same 16-class land cover classification scheme that has been applied consistently across the United States at a spatial resolution of 30 meters. NLCD 2011 is based primarily on a decision-tree classification of circa 2011 Landsat satellite data. \n\nThis dataset is associated with the following publication:\nHomer, C., J. Dewitz, L. Yang, S. Jin, P. Danielson, G. Xian, J. Coulston, N. Herold, J. Wickham , and K. Megown. Completion of the 2011 National Land Cover Database for the Conterminous United States \u2013 Representing a Decade of Land Cover Change Information.   PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING. American Society for Photogrammetry and Remote Sensing, Bethesda, MD, USA, 81(0): 345-354, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-3txd-118",
            "keyword": [
                "land cover",
                "Landsat",
                "Impervious cover",
                "Forest canopy density",
                "land cover change",
                "climate change",
                "radiative forcing",
                "snow-cover albedo",
                "snow-free albedo"
            ],
            "contactPoint": {
                "fn": "James Wickham",
                "hasEmail": "mailto:wickham.james@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.mrlc.gov/data",
                    "accessURL": "https://www.mrlc.gov/data"
                }
            ],
            "modified": "2014-10-10",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "NLCD - MODIS land cover- albedo dataset for the continental United States",
            "description": "The NLCD-MODIS land cover-albedo database integrates high-quality MODIS albedo observations with areas of homogeneous land cover from NLCD. The spatial resolution (pixel size) of the database is 480m-x-480m aligned to the standardized UGSG Albers Equal-Area projection. The spatial extent of the database is the continental United States. \n\nThis dataset is associated with the following publication:\nWickham , J., C.A. Barnes, and T. Wade. Combining NLCD and MODIS to Create a Land Cover-Albedo Dataset for the Continental United States.   REMOTE SENSING OF ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 170(0): 143-153, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-3txd-117",
            "keyword": [
                "climate change",
                "land cover change",
                "Landsat",
                "radiative forcing",
                "snow-cover albedo",
                "snow-free albedo"
            ],
            "contactPoint": {
                "fn": "James Wickham",
                "hasEmail": "mailto:wickham.james@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.mrlc.gov/data",
                    "accessURL": "https://www.mrlc.gov/data"
                }
            ],
            "modified": "2015-11-03",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://www.mrlc.gov/nlcdalbedo.php",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Systematically evaluating read-across prediction and performance using a local validity approach characterized by chemical structure and bioactivity information",
            "description": "Read-across is a popular data gap filling technique within category and analogue approaches for regulatory purposes. Acceptance of read-across remains an ongoing challenge with several efforts underway for identifying and addressing uncertainties. Here we demonstrate an algorithmic, automated approach to evaluate the utility of using in vitro bioactivity data (\u201cbioactivity descriptors\u201d, from EPA\u2019s ToxCast program) in conjunction with chemical descriptor information to derive local validity domains (specific sets of nearest neighbors) to facilitate read-across for a number of in vivo repeated dose toxicity study types. Over 3400 different chemical structure descriptors were generated for a set of 976 chemicals and supplemented with the outcomes from 821 in vitro assays. The read-across prediction for a given chemical was based on the similarity weighted endpoint outcomes of its nearest neighbors. The approach enabled a performance baseline for read-across predictions of specific study outcomes to be established. Bioactivity descriptors were often found to be more predictive of in vivo toxicity outcomes than chemical descriptors or a combination of both. This generic read across (GenRA) is intended to form a first step in systemizing read-across prediction and serves as a useful tool as part of a screening level hazard assessment for new untested chemicals. \n\nThis dataset is associated with the following publication:\nShah , I., J. Liu , R.S. Judson , R.S. Thomas , and G. Patlewicz. (Reg. Tox. Pharm.) Systematically evaluating read-across prediction and performance using a local validity approach characterized by chemical structure and bioactivity information.   REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 79: 12-24, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-6t1n-421",
            "keyword": [
                "ToxCast",
                "sustainable chemistry",
                "human health risk assessment",
                "nearest neighbors",
                "qsar",
                "bioactivity",
                "DSSTox",
                "Chemistry Dashboard",
                "Read Across"
            ],
            "contactPoint": {
                "fn": "Ann Richard",
                "hasEmail": "mailto:richard.ann@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/Comptox/NCCT_Publication_Data/ShahImran/Read_Across/",
                    "accessURL": "https://gaftp.epa.gov/Comptox/NCCT_Publication_Data/ShahImran/Read_Across/"
                }
            ],
            "modified": "2015-09-09",
            "references": [
                "https://doi.org/10.1016/j.yrtph.2016.05.008"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Analysis of the Effects of Cell Stress and Cytotoxicity on In Vitro Assay Activity Across a Diverse Chemical and Assay Space",
            "description": "Chemical toxicity can arise from disruption of specific biomolecular functions or through more generalized cell stress and cytotoxicity-mediated processes. Here, concentration-dependent responses of 1063 chemicals including pharmaceuticals, natural products, pesticidals, consumer, and industrial chemicals across a diverse battery of 821 in vitro assay endpoints from 7 high-throughput assay technology platforms were analyzed in order to better distinguish between these types of activities. Both cell-based and cell-free assays showed a rapid increase in the frequency of responses at concentrations where cell stress / cytotoxicity responses were observed in cell-based assays. Chemicals that were positive on at least two viability/cytotoxicity assays within the concentration range tested (typically up to 100 \uf06dM) activated a median of 12% of assay endpoints while those that were not cytotoxic in this concentration range activated 1.3% of the assays endpoints. The results suggest that activity can be broadly divided into: (1) specific biomolecular interactions against one or more targets (e.g., receptors or enzymes) at concentrations below which overt cytotoxicity-associated activity is observed; and (2) activity associated with cell stress or cytotoxicity, which may result from triggering of specific cell stress pathways, chemical reactivity, physico-chemical disruption of proteins or membranes, or broad low-affinity non-covalent interactions. Chemicals showing a greater number of specific biomolecular interactions are generally designed to be bioactive (pharmaceuticals or pesticidal active ingredients), while intentional food-use chemicals tended to show the fewest specific interactions. The analyses presented here provide context for use of these data in ongoing studies to predict in vivo toxicity from chemicals lacking extensive hazard assessment. \n\nThis dataset is associated with the following publication:\nJudson , R., K. Houck , M. Martin , A. Richard , T. Knudsen , I. Shah , S. Little , J. Wambaugh , W. Setzer , P. Kothiya , J. Phuong , D. Filer , D. Smith , D. Reif, D. Rotroff, N. Kleinstreuer, N. Sipes, M. Xia, R. Huang, K. Crofton , and R. Thomas. (Toxicological Sciences) Analysis of the Effects of Cell Stress and Cytotoxicity on In Vitro Assay Activity Across a Diverse Chemical and Assay Space.   TOXICOLOGICAL SCIENCES. Society of Toxicology,     1-47, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-x0kx-419",
            "keyword": [
                "cytotoxicity",
                "chemical safety for sustainablity",
                "chemical safety research",
                "high-throughput toxicology",
                "ToxCast",
                "computational toxicology"
            ],
            "contactPoint": {
                "fn": "Keith Houck",
                "hasEmail": "mailto:houck.keith@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/Judson/CytotoxBurst",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/Judson/CytotoxBurst"
                }
            ],
            "modified": "2016-08-28",
            "references": [
                "https://doi.org/10.1093/toxsci/kfw092"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Is Skin penetration a determining factor in skin sensitisation potential and potency? Refuting the notion of a LogKow threshold for Skin Sensitisation",
            "description": "t is widely accepted that substances that cannot penetrate through the skin will not be sensitizers. LogKow and molecular weight (MW) have been used to set thresholds for sensitization potential. Highly hydrophilic substances e.g. LogKow \u2264 1 are expected not to penetrate effectively to induce sensitization. To investigate whether LogKow >1 is a true requirement for sensitization, a large dataset of substances that had been evaluated for their skin sensitization potential under Registration, Evaluation, Authorisation and restriction of CHemicals (REACH), together with available measured LogKow values was compiled using the OECD eChemPortal. The incidence of sensitizers relative to non-sensitizers above and below a LogKow of 1 was explored. Reaction chemistry principles were used to explain the sensitization observed for the subset of substances with a LogKow \u22640. 1482 substances were identified with skin sensitization data and measured LogKow values. 525 substances had a measured LogKow \u2264 1, 100 of those were sensitizers. There was no significant difference in the incidence of sensitizers above and below a LogKow of 1. Reaction chemistry principles that had been established for lower MW and more hydrophobic substances were found to be still valid in rationalizing the skin sensitizers with a LogKow \u2264 0. The LogKow threshold arises from the widespread misconception that the ability to efficiently penetrate the stratum corneum is a key determinant of sensitization potential and potency. \n\nThis dataset is associated with the following publication:\nFitzpatrick, J., D. Roberts, and G. Patlewicz. (Journal of Applied Toxicology) Is skin penetration a determining factor in skin sensitisation potential and potency? Refuting the notion of a LogKow threshold for Skin Sensitisation.   JOURNAL OF APPLIED TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA,  1-11, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-6t1n-316",
            "keyword": [
                "skin sensitization",
                "DSSTox",
                "Chemistry Dashboard",
                "Read Across"
            ],
            "contactPoint": {
                "fn": "Ann Richard",
                "hasEmail": "mailto:richard.ann@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/PatlewiczGrace/LOGKOW_Skin_Sensistization/",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/PatlewiczGrace/LOGKOW_Skin_Sensistization/"
                }
            ],
            "modified": "2016-06-29",
            "references": [
                "https://doi.org/10.1002/jat.3354"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Concentrations of individual fine particulate matter components in the United States around July 4th ",
            "description": "Data used in these analyses was obtained from publically-available sources, specifically the EPA's AirNow website (https://www.epa.gov/outdoor-air-quality-data). The dataset provided includes the subset of data from AirNow that was used in our analyses. \n\nThis dataset is associated with the following publication:\nDickerson, A., A. Benson, B. Buckley, and E. Chan. Concentrations of individual fine particulate matter components in the United States around July 4th.   Air Quality, Atmosphere & Health. Springer Netherlands, NETHERLANDS,  1-10, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:062"
            ],
            "identifier": "A-qfvc-338",
            "keyword": [
                "air quality",
                "Ambient air quality",
                "Fireworks",
                "air pollution",
                "Fine Particulate Matter"
            ],
            "contactPoint": {
                "fn": "Elizabeth Chan",
                "hasEmail": "mailto:chan.elizabeth@epa.gov"
            },
            "distribution": [
                {
                    "title": "Raw speciation data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/338/Raw%20speciation%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-16",
            "references": [
                "http://link.springer.com/article/10.1007/s11869-016-0433-0"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/338/documents/Data%20Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Coastal 2010: Site Information, Hydrographic Profile, Water Chemistry",
            "description": "Data from the National Aquatic Resource Surveys:  \nThe following data are available for download as comma separated values (.csv) files. Sort the table using the pull down menus or headers to more easily locate the data. Right click on the file name and select Save Link As to save the file to your computer. Make sure to also download the companion metadata file (.txt) for the list of field labels. See the survey technical document for more information on the data analyses. \n\nThis dataset is associated with the following publications:\nYurista , P., J. Kelly , and J. Scharold. Great Lakes nearshore-offshore: Distinct water quality regions.   JOURNAL OF GREAT LAKES RESEARCH. International Association for Great Lakes Research, Ann Arbor, MI, USA, 42: 375-385, (2016).\nKelly , J., P. Yurista , M. Starry, J. Scharold , W. Bartsch , and A. Cotter. The first US National Coastal Condition Assessment survey in the Great Lakes: Development of the GIS frame and exploration of spatial variation in nearshore water quality results.   JOURNAL OF GREAT LAKES RESEARCH. International Association for Great Lakes Research, Ann Arbor, MI, USA, 41: 1060-1074, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-98sq-382",
            "keyword": [
                "nearshore",
                "offshore",
                "water quality",
                "National Coastal Condition Assessment",
                "Great Lakes"
            ],
            "contactPoint": {
                "fn": "Jill Scharold",
                "hasEmail": "mailto:scharold.jill@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys"
                }
            ],
            "modified": "2016-09-09",
            "references": [
                "https://doi.org/10.1016/j.jglr.2015.12.002",
                "https://doi.org/10.1016/j.jglr.2015.09.007"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "EPA data for EMMA of Peatland Discharge to an Alaskan Stream Journal of Hydrology 2015",
            "description": "This dataset contains primarily the EPA generated data for the EMMA (End-Member-Mixing Analysis) model that was presented in the associated J. of Hydrology (2015) publication.  Part of the data for the EMMA and all the data for the water budget  were not produced by EPA and were not included here.  EPA did the analyses for SO4, Cl, and K and these results are in this dataset.  An independent set of lab analysis was done by a non-EPA lab for K and this data is included as one quality control measure.  The field collections of the samples for all of the data were collected jointly between several EPA field scientists along with the non-EPA cooperative agreement principal investigator and primary author of the J. of Hydrology (2015) publication.  The site description data along with site locations are given in the dataset. \n\nThis dataset is associated with the following publication:\nGracz, M., M. Moffett , D. Siegel, and P. Glaser. Analyzing peatland discharge to streams in an Alaskan Watershed: An integration of end-member mixing analysis and a water balance approach.   JOURNAL OF HYDROLOGY. Elsevier Science Ltd, New York, NY, USA, 530: 667-676, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-8672-411",
            "keyword": [
                "SO4",
                "potassium K",
                "chloride",
                "end-member",
                "inter-laboratory",
                "mixing zone",
                "ecological function",
                "headwater streams",
                "peatlands",
                "wetlands",
                "stream flow",
                "EMMA",
                "Watershed",
                "functional assessment"
            ],
            "contactPoint": {
                "fn": "Mary Moffett",
                "hasEmail": "mailto:moffett.mary@epa.gov"
            },
            "distribution": [
                {
                    "title": "MoffettMary_A-8672_Dataset1_20160928_SciHub_JofHydrology2015.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/411/MoffettMary_A-8672_Dataset1_20160928_SciHub_JofHydrology2015.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-28",
            "references": [
                "https://doi.org/10.1016/j.jhydrol.2015.09.072"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data Sources for NetZero Ft Carson Model ",
            "description": "Table of values used to parameterize and evaluate the Ft Carson NetZero integrated Model with published reference sources for each value. \n\nThis dataset is associated with the following publication:\nProcter, A., O. Kaplan , and R. Araujo. Net Zero Fort Carson: Integrating Energy, Water, and Waste Strategies to Lower the Environmental Impact of a Military Base.   JOURNAL OF INDUSTRIAL ECOLOGY. Berkeley Electronic Press, Berkeley, CA, USA,  online, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-573t-291",
            "keyword": [
                "NetZero",
                "sustainability",
                "systems modeling"
            ],
            "contactPoint": {
                "fn": "Rochelle Araujo",
                "hasEmail": "mailto:araujo.rochelle@epa.gov"
            },
            "distribution": [
                {
                    "title": "Araujo SDM Data sources for NetZero Model 20160909.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/291/Araujo%20SDM%20Data%20sources%20for%20NetZero%20Model%2020160909.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2015-10-15",
            "references": [
                "http://onlinelibrary.wiley.com/doi/10.1111/jiec.12359/abstract"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data Fusion approach for spatial analysis of speciated PM2.5 across time",
            "description": "speciated pm2.5 monitoring data and total pm2.5 monitoring data. \n\nThis dataset is associated with the following publication:\nRundel, C., E. Schliep, A. Gelfand, and D. Holland. A data fusion approach for spatial analysis of speciated PM2:5 across time.   Annals of Applied Statistics. Institute of Mathematical Statistics, Beachwood, OH, USA, 26(0): 515-526, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-70s4-214",
            "keyword": [
                "downscaling",
                "speciated fine particulate matter"
            ],
            "contactPoint": {
                "fn": "David Holland",
                "hasEmail": "mailto:holland.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "paper_data.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/214/paper_data.tar",
                    "mediaType": "application/x-tar"
                }
            ],
            "modified": "2016-09-14",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Mild Thyroid Hormone Insufficiency During Development Compromises Activity-Dependent Neuroplasticity in the Hippocampus of Adult Male Rats",
            "description": "behavioral measures of learning and memory in adult offspring of rats treated with thyroid hormone synthesis inhibitor, propylthiouracil.\nElectrophysiological measures of 'memory' in form of plasticity model known as long term potentiation (LTP)\nMolecular changes induced by LTP. \n\nThis dataset is associated with the following publication:\nGilbert , M., K. Sanchez-Huerta, and C. Wood. Mild Thyroid Hormone Insufficiency During Development Compromises Activity-Dependent Neuroplasticity in the Hippocampus of Adult Make Rats.   ENDOCRINOLOGY. Endocrine Society,    157(2): 774-87, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-v42b-403",
            "keyword": [
                "fear conditioning",
                "spatial learning",
                "neuroplasticity",
                "brain development",
                "developmental hypothyroidism",
                "LTP",
                "BDNF",
                "neurotrophins",
                "activity-dependent plasticity",
                "hippocampus",
                "CSS",
                "children's health",
                "brain",
                "thyroid"
            ],
            "contactPoint": {
                "fn": "Mary Gilbert",
                "hasEmail": "mailto:gilbert.mary@epa.gov"
            },
            "distribution": [
                {
                    "title": "M0710_BDNF LTP Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/403/M0710_BDNF%20LTP%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-10-27",
            "references": [
                "https://doi.org/10.1210/en.2015-1643"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Enhancing climate adaptation capacity for drinking water treatment facilities (supplement)",
            "description": "Historical water quality data of the Ohio River. \n\nThis dataset is associated with the following publication:\nLevine, A., J. Yang , and J. Goodrich. Enhancing climate Adaptation Capacity for Drinking Water Treatment Facilities.   Journal of Water and Climate Change. IWA Publishing, London,  UK, 7(3): 1-13, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-qfvd-417",
            "keyword": [
                "climate adaptation",
                "coagulation",
                "conventional treatment",
                "resilience",
                "surface water"
            ],
            "contactPoint": {
                "fn": "Yingping Yang",
                "hasEmail": "mailto:yang.jeff@epa.gov"
            },
            "distribution": [
                {
                    "title": "Enhancing Climate Adaptation Capacity for Drinking Water Treatment Facilities.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/417/Enhancing%20Climate%20Adaptation%20Capacity%20for%20Drinking%20Water%20Treatment%20Facilities.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2016-07-03",
            "references": [
                "https://doi.org/10.2166/wcc.2016.011"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Impact of water quality on chlorine demand of corroding copper (Supplement)",
            "description": "Copper is widely used in drinking water premise plumbing system materials. In buildings such as\r\nhospitals, large and complicated plumbing networks make it difficult to maintain good water quality.\r\nSustaining safe disinfectant residuals throughout a building to protect against waterborne pathogens\r\nsuch as Legionella is particularly challenging since copper and other reactive distribution system materials\r\ncan exert considerable demands. The objective of this work was to evaluate the impact of pH and\r\northophosphate on the consumption of free chlorine associated with corroding copper pipes over time. A\r\ncopper test-loop pilot system was used to control test conditions and systematically meet the study\r\nobjectives. Chlorine consumption trends attributed to abiotic reactions with copper over time were\r\ndifferent for each pH condition tested, and the total amount of chlorine consumed over the test runs\r\nincreased with increasing pH. Orthophosphate eliminated chlorine consumption trends with elapsed\r\ntime (i.e., chlorine demand was consistent across entire test runs). Orthophosphate also greatly reduced\r\nthe total amount of chlorine consumed over the test runs. Interestingly, the total amount of chlorine\r\nconsumed and the consumption rate were not pH dependent when orthophosphate was present. The\r\nfindings reflect the complex and competing reactions at the copper pipe wall including corrosion,\r\noxidation of Cu(I) minerals and ions, and possible oxidation of Cu(II) minerals, and the change in chlorine\r\nspecies all as a function of pH. The work has practical applications for maintaining chlorine residuals in\r\npremise plumbing drinking water systems including large buildings such as hospitals. \n\nThis dataset is associated with the following publication:\nLytle , D., and J. Liggett. Impact of Water Quality on Chlorine Demand of Corroding Copper.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 92: 11-21, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-3ffg-425",
            "keyword": [
                "Oxidant demand",
                "Chlorine",
                "Copper",
                "Orthophosphate",
                "drinking water"
            ],
            "contactPoint": {
                "fn": "Darren Lytle",
                "hasEmail": "mailto:lytle.darren@epa.gov"
            },
            "distribution": [
                {
                    "title": "Copper chlorine.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/425/Copper%20chlorine.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "chlorine paper data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/425/chlorine%20paper%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-01-15",
            "references": [
                "https://doi.org/10.1016/j.watres.2016.01.032"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Volatile and semivolatile organic compounds in laboratory peat fire emissions",
            "description": "Supporting information Tables S3 and S4 list emission factors in g/kg of speciated volatile and particulate organic compounds emitted from peat burning. Peat samples were acquired from Alligator River (AR) and Pocosin Lakes (PL) National Wildlife Refuges. \n\nThis dataset is associated with the following publication:\nGeorge , I., R. Black, J. Walker , C. Geron , J. Aurell , M. Hays , W. Preston, and B. Gullett. Volatile and semivolatile organic compounds in laboratory peat fire emissions.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 132: 163-170, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-qrg3-41",
            "keyword": [
                "biomass burning",
                "smoldering combustion",
                "particulate mass",
                "volatile organic compounds",
                "polycyclic aromatic hydrocarbons",
                "particulate matter"
            ],
            "contactPoint": {
                "fn": "Ingrid George",
                "hasEmail": "mailto:george.ingrid@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.sciencedirect.com/science/article/pii/S1352231016301388",
                    "accessURL": "https://www.sciencedirect.com/science/article/pii/S1352231016301388"
                }
            ],
            "modified": "2015-12-17",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The Full-Scale Implementation of an Innovative (Supplemental)",
            "description": "Across the United States, high levels of ammonia in drinking water\r\nsources can be found. Although ammonia in water does not pose\r\na direct health concern, ammonia nitrification can cause a number\r\nof issues and reduce the effectiveness of some treatment processes.\r\nAn innovative biological ammonia-removal drinking water\r\ntreatment process was developed and, after the success of a pilot\r\nstudy, a full-scale treatment system using the process was built in\r\na small Iowa community. The treatment plant included a unique\r\naeration contactor design that is able to consistently reduce\r\nammonia from 3.3 mg of nitrogen/L to nearly nondetectable after\r\na biofilm acclimation period. Close system monitoring was\r\nperformed to avoid excess nitrite release during acclimation, and\r\nphosphate was added to enhance biological activity on the basis\r\nof pilot study findings. The treatment system is robust, reliable,\r\nand relatively simple to operate. The operations and effectiveness\r\nof the treatment plant were documented in the study. \n\nThis dataset is associated with the following publication:\nLytle , D., D. Williams , C. Muhlen , M. Pham , K. Kelty , M. Wildman, G. Lang, M. Wilcox, and M. Kohne. The Full-Scale Implementation of an Innovative Biological Ammonia Treatment Process.   Journal AWWA. American Water Works Association, Denver, CO, USA, 107(12): E648-E665, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-nzss-420",
            "keyword": [
                "ammonia",
                "biological treatment",
                "drinking water",
                "nitrification"
            ],
            "contactPoint": {
                "fn": "Darren Lytle",
                "hasEmail": "mailto:lytle.darren@epa.gov"
            },
            "distribution": [
                {
                    "title": "jaw201512lytle_es.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/420/jaw201512lytle_es.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2015-12-01",
            "references": [
                "https://doi.org/10.5942/jawwa.2015.107.0176"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Comparison of Bottomless Lift Nets and Breder Traps for Sampling Salt-Marsh Nekton",
            "description": "Data set contains: the length of mummichogs (Fundulus heteroclitus) caught on lift nets and Breder traps from May to September 2002; the sizes of green crabs caught in the lift nets and Breder traps during same time frame; the mean density and sample size data for each sampling time and each site (3 sites total) for total nekton sampled and total nekton minus shrimp. \n\nThis dataset is associated with the following publication:\nRaposa, K., and M. Chintala. Comparison of Bottomless Lift Nets and Breder Traps for Sampling Salt-Marsh Nekton.   TRANSACTIONS OF THE AMERICAN FISHERIES SOCIETY. American Fisheries Society, Bethesda, MD, USA, 145(1): 163-172, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-2z38-424",
            "keyword": [
                "Mummichog",
                "Lift Net",
                "Breder trap",
                "Green crab",
                "Fundulus heteroclitus",
                "Carcinus maenas",
                "Narragansett Bay",
                "Salt marsh",
                "nekton",
                "sampling methods"
            ],
            "contactPoint": {
                "fn": "Marnita Chintala",
                "hasEmail": "mailto:chintala.marty@epa.gov"
            },
            "distribution": [
                {
                    "title": "Raposa and Chintala data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/424/Raposa%20and%20Chintala%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-21",
            "references": [
                "https://doi.org/10.1080/00028487.2015.1111254"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "GRE Enzymes for Vector Analysis",
            "description": "Microbial enzyme data that were collected during the 2004-2006 EMAP-GRE program. These data were then used by Moorhead et al (2016) in their ecoenzyme vector analysis paper. \n\nThis dataset is associated with the following publication:\nMoorhead, D., R. Sinsabaugh, B. Hill , and M. Weintraub. Vector analysis of ecoenzyme activities reveal constraints on coupled C, N and P dynamics.   SOIL BIOLOGY AND BIOCHEMISTRY. Elsevier Science Ltd, New York, NY, USA, 93: 1-7, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-76hm-174",
            "keyword": [
                "microbial ecoenzymes",
                "nutrient limitation",
                "vector analysis"
            ],
            "contactPoint": {
                "fn": "Brian Hill",
                "hasEmail": "mailto:hill.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "GRE_VECTOR.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/174/GRE_VECTOR.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-08-10",
            "references": [
                "https://doi.org/10.1016/j.soilbio.2015.10.019"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/174/documents/GRE%20Vectors%20Data%20Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Optimized UDP-glucuronosyltransferase (UGT) activity assay for trout liver S9 fractions",
            "description": "This publication provides an optimized UGT assay for trout liver S9 fractions which can be used to perform in vitro-in vivo extrapolations of measured UGT activity. \n\nThis dataset is associated with the following publication:\nLadd, M., P. Fitzsimmons , and J. Nichols. Optimization of a UDP-glucuronosyltransferase assay for trout liver S9 fractions: Activity enhancement by alamethicin, a pore-forming peptide.   XENOBIOTICA. Taylor & Francis, Inc., Philadelphia, PA, USA, 46(12): 1066-1075, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-0p2p-89",
            "keyword": [
                "S9 fractions",
                "UDP glucuronosyltransferase",
                "rainbow trout",
                "alamethicin"
            ],
            "contactPoint": {
                "fn": "John Nichols",
                "hasEmail": "mailto:nichols.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "Ladd et al., 2016, Science Hub Data Summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/89/Ladd%20et%20al.%2C%202016%2C%20Science%20Hub%20Data%20Summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-09-30",
            "references": [
                "https://doi.org/10.3109/00498254.2016.1149634"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "SRHA calibration curve",
            "description": "an UV calibration curve for SRHA quantitation. \n\nThis dataset is associated with the following publication:\nChang, X., and D. Bouchard. Surfactant-Wrapped Multiwalled Carbon Nanotubes in Aquatic Systems: Surfactant Displacement in the Presence of Humic Acid.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(0): 9214-9222, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-83bs-140",
            "keyword": [
                "humic acid; uv",
                "MWCNTs; nanomaterials; surfactant; ENMs; humic acid"
            ],
            "contactPoint": {
                "fn": "Dermont Bouchard",
                "hasEmail": "mailto:bouchard.dermont@epa.gov"
            },
            "distribution": [
                {
                    "title": "SRHA calibration curve.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/140/SRHA%20calibration%20curve.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-07-02",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for pilot-scale low level hydrogen peroxide tests using humidifiers",
            "description": "Dataset includes data from each experiment conducted in the pilot-scale testing.  Each sheet of the Excel file pertains to each test. A data dictionary is included in the first sheet.  In each sheet there are microbiological data (colony forming units) for each test and positive control coupon used in the study. Also shown is the calculation of decontamination efficacy (log10 reduction). \n\nThis dataset is associated with the following publication:\nWood, J., W. Calfee, S. Ryan, L. Mickelsen, M. Clayton, and V. Rastogi. A Simple Decontamination Approach Using Hydrogen Peroxide Vapor for Bacillus anthracis Spore Inactivation.   JOURNAL OF APPLIED MICROBIOLOGY. Blackwell Publishing, Malden, MA, USA, 121(6): 1603-1615, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "A-73nd-242",
            "keyword": [
                "Bacillus anthracis",
                "Decontamination",
                "hydrogen peroxide vapor",
                "bacterial spores",
                "antimicrobial"
            ],
            "contactPoint": {
                "fn": "Joseph Wood",
                "hasEmail": "mailto:wood.joe@epa.gov"
            },
            "distribution": [
                {
                    "title": "COMMANDER data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/242/COMMANDER%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-09-11",
            "references": [
                "http://onlinelibrary.wiley.com/doi/10.1111/jam.13284/full"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Lab-scale hydrogen peroxide data from ECBC",
            "description": "Data from small lab scale tests conducted at ECBC.  It contains efficacy data as well as data on env conditions such as temperature, RH, and hydrogen peroxide vapor concentration. \n\nThis dataset is associated with the following publication:\nWood, J., W. Calfee, S. Ryan, L. Mickelsen, M. Clayton, and V. Rastogi. A Simple Decontamination Approach Using Hydrogen Peroxide Vapor for Bacillus anthracis Spore Inactivation.   JOURNAL OF APPLIED MICROBIOLOGY. Blackwell Publishing, Malden, MA, USA, 121(6): 1603-1615, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "A-73nd-244",
            "keyword": [
                "Bacillus anthracis",
                "Decontamination",
                "hydrogen peroxide vapor",
                "bacterial spores",
                "antimicrobial"
            ],
            "contactPoint": {
                "fn": "Joseph Wood",
                "hasEmail": "mailto:wood.joe@epa.gov"
            },
            "distribution": [
                {
                    "title": "ECBC results summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/244/ECBC%20results%20summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-08-13",
            "references": [
                "http://onlinelibrary.wiley.com/doi/10.1111/jam.13284/full"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CAIRSENSE-Atlanta Low Cost Sensor Evaluation Versus Reference Monitors",
            "description": "Short time interval comparisons of low cost sensor response and corresponding Federal Reference or Federal Equivalent Monitors at an NCOR site located in proximity to Atlanta, Georgia. Portions of this dataset are inaccessible because: The data were integrated using R.  Currently there is no means of reporting \"R: database in the science hub. Data are still being reviewed as part of the journal publication process.  Release prior to journal acceptance could result in external parties inappropriately using the data (including sensor manufacturers who might use such data without a full understanding of its meaning). They can be accessed through the following means: Direct transfer from the Principal Investigator upon journal publication. Format: The dataset was created in R and represents an extensive short time resolution of thousands of lines of air quality measurements.  In addition, the data have been integrated into a manuscript which has yet to be published.  The manuscript was cleared  through STICs but has not yet rec'd journal based peer review acceptance. \n\nThis dataset is associated with the following publication:\nJiao, W., G. Hagler, R. Williams, R. Sharpe, R. Brown, D. Garver, R. Judge, M. Caudill, J. Rickard, M. Davis, L. Weinstock, S. Zimmer-Dauphinee, and K. Buckley. Community Air Sensor Network (CAIRSENSE) project: Evaluation of low-cost sensor performance in a suburban environment in the southeastern United States.   Atmospheric Measurement Techniques. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 9: 5282-5292, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-hx3v-157",
            "keyword": [
                "criteria air polluants",
                "low cost air quality sensors"
            ],
            "contactPoint": {
                "fn": "Ronald Williams",
                "hasEmail": "mailto:williams.ronald@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science Data Hub CAIRSENSE Atlanta Data Set -Reduced.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/157/Science%20Data%20Hub%20CAIRSENSE%20Atlanta%20Data%20Set%20-Reduced.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-04-01",
            "references": [
                "https://doi.org/10.5194/amt-9-5281-2016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/157/documents/Science%20Hub%20Data%20Dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Flow list and test results",
            "description": "These data accompany the manuscript 'Critical Review of Elementary Flows in LCA Data'. Each file presents a subgroup of the elementary flows (data used for analysis) and all the analysis results. Files are separated by flow types. The 'Element or Compound' types contained over 115,000 flows and was broken into three files (a, b,and c).  A guide to the file contents and explanation of flow types are provided in the 'CriticalReviewofElementaryFlows_Data_Guide' file. \n\nThis dataset is associated with the following publication:\nEdelen, A., W. Ingwersen, C. Rodriguez, R. Alvarenga, A.R. de Almeida, and G. Wernet. Critical Review of Elementary Flows in LCA data.   INTERNATIONAL JOURNAL OF LIFE CYCLE ASSESSMENT. Ecomed Verlagsgesellschaft AG, Landsberg,  GERMANY,  01-13, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-p2p0-450",
            "keyword": [
                "nomenclature",
                "critical review",
                "life cycle assessment",
                "life cycle inventory data",
                "interoperability"
            ],
            "contactPoint": {
                "fn": "Wesley Ingwersen",
                "hasEmail": "mailto:ingwersen.wesley@epa.gov"
            },
            "distribution": [
                {
                    "title": "Biological_Analysis.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/450/Biological_Analysis.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
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                {
                    "title": "Element or Compound_flow by source.xlsx",
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                {
                    "title": "Element or Compound_Linked identifier_a.xlsx",
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                {
                    "title": "Element or Compound_Metadata_a.xlsx",
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                    "title": "Element or Compound_Metadata_c.xlsx",
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                },
                {
                    "title": "Energy_Analysis.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/450/Energy_Analysis.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Fossil and Nuclear Fuels_Analysis.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/450/Fossil%20and%20Nuclear%20Fuels_Analysis.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Groups_Chemicals_Analysis_.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/450/Groups_Chemicals_Analysis_.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Land_Analysis.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/450/Land_Analysis.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Other_Analysis.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/450/Other_Analysis.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Water_Analysis.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/450/Water_Analysis.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-11-22",
            "references": [
                "https://doi.org/10.1007/s11367-017-1354-3",
                "https://pasteur.epa.gov/uploads/450/documents/CriticalReviewofElementaryFlows_DataGuide.xlsx"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/450/documents/CriticalReviewofElementaryFlows_DataDictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Ozone-induced systemic and pulmonary effects are diminished in adrenalectomized rats",
            "description": "This data set is an excel file pertaining to the study that examined ozone-induced systemic and pulmonary effects in rats that underwent SHAM surgery (control), adrenal demedullation or total bilateral adrenalectomy. Different pages of the spreadsheet shows individual animal data for markers of lung injury and inflammation, body weights, whole body plethysmography measurements, levels of circulating hormones and lipids, and circulating white blood cell count as well as platelet count. \n\nThis dataset is associated with the following publication:\nMiller, D., S. Snow, M. Schladweiler , J. Richards , A. Ghio , A. Ledbetter , and U. Kodavanti. Acute Ozone-Induced Pulmonary and Systemic Metabolic Effects are Diminished in Adrenalectomized Rats#.   TOXICOLOGICAL SCIENCES. Society of Toxicology,    150(2): 312-22, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-xsjt-216",
            "keyword": [
                "Ozone",
                "adrenalectomy",
                "Stress Response",
                "HPA-axis",
                "lung injury"
            ],
            "contactPoint": {
                "fn": "Urmila Kodavanti",
                "hasEmail": "mailto:kodavanti.urmila@epa.gov"
            },
            "distribution": [
                {
                    "title": "Miller et al ToxSci 2016 Science hub data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/216/Miller%20et%20al%20ToxSci%202016%20Science%20hub%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-22",
            "references": [
                "https://doi.org/10.1093/toxsci/kfv331"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/216/documents/Miller%20et%20al%20ToxSci%202016%20Science%20hub%20data.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Locomotor activity and tissues levels following acute administration of lambda- and gamma-cyhalothrin in rats",
            "description": "raw motor activity counts and tissue levels. \n\nThis dataset is associated with the following publication:\nMoser, G., Z. Liu, C. Schlosser, T. Spanogle, A. Chandrasekaran, and K. Mcdaniel. Locomotor activity and tissue levels following acute administration of lambda- and gamma-cyhalothrin in rats.   TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 313: 97-103, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-t4bx-249",
            "keyword": [
                "cyhalothrin",
                "pyrethroids",
                "neurotoxicity",
                "motor activity",
                "toxicokineticscyhalothrin",
                "toxicokinetics"
            ],
            "contactPoint": {
                "fn": "Virginia Moser",
                "hasEmail": "mailto:moser.ginger@epa.gov"
            },
            "distribution": [
                {
                    "title": "science hub data summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/249/science%20hub%20data%20summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-29",
            "references": [
                "https://doi.org/10.1016/j.taap.2016.10.020"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Tox_esterase_2016",
            "description": "individual values for liver detoxification for each human sample and for each chemical. \n\nThis dataset is associated with the following publication:\nMoser, G., and S. Padilla. Esterase detoxification of acetylcholinesterase inhibitors using human liver samples in vitro.   TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA,  11-20, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-str5-59",
            "keyword": [
                "pesticides",
                "detoxification",
                "esterases"
            ],
            "contactPoint": {
                "fn": "Virginia Moser",
                "hasEmail": "mailto:moser.ginger@epa.gov"
            },
            "distribution": [
                {
                    "title": "all human data for scihub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/59/all%20human%20data%20for%20scihub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-05-12",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Neurophysiological assessment of auditory, peripheral nerve, somatosensory, and visual system function after developmental exposure to gasoline, E15, and E85 vapors.",
            "description": "Visual, auditory, somatosensory, and peripheral nerve evoked responses. \n\nThis dataset is associated with the following publication:\nHerr , D., D. Freeborn , L. Degn , S.A. Martin, J. Ortenzio, L. Pantlin, C. Hamm , and W. Boyes. Neurophysiological Assessment of Auditory, Peripheral Nerve, Somatosensory, and Visual System Function After Developmental Exposure to Gasoline, E15 and E85 Vapors.   NEUROTOXICOLOGY AND TERATOLOGY. Elsevier Science Ltd, New York, NY, USA, 54: 78-88, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-98sp-145",
            "keyword": [
                "visual evoked potentials",
                "somatosensory evoked potentials",
                "peripheral nerve evoked potentials",
                "brainstem auditory evoked responses",
                "biofuels",
                "E0",
                "E15",
                "E85",
                "vapors",
                "neurophysiology"
            ],
            "contactPoint": {
                "fn": "David Herr",
                "hasEmail": "mailto:herr.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "A-98sp_BiofuelsE0E15E85_Data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/145/A-98sp_BiofuelsE0E15E85_Data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-06-07",
            "references": [
                "https://doi.org/10.1016/j.ntt.2015.12.006"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Ohmic resistance affects microbial community and electrochemical kinetics in a multi-anode microbial electrochemical cell ",
            "description": "A-3txf_sequence summary.xksx: Abundance of contigs or unique sequences for each biofilm samples from anodes in the MEC reactor\nHodon Waterloo final_fasta_working.docx: Raw sequences with their identification numbers\nRNA S1_MEC.docx: Representative sequences with their ID number and taxonomy. \n\nThis dataset is associated with the following publication:\nSantodomingo, J., H. Ryu, B. Dhar, and H. Lee. Ohmic resistance affects microbial community and electrochemical kinetics in a multi-anode microbial electrochemical cell.   JOURNAL OF POWER SOURCES. Elsevier Science Ltd, New York, NY, USA, 331: 315-321, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-3txf-448",
            "keyword": [
                "Abundance",
                "Raw sequences",
                "Fasta file",
                "Anode potential",
                "Half-saturation anode potential",
                "Microbial electrochemical cells",
                "Multi-anode",
                "Ohmic energy loss"
            ],
            "contactPoint": {
                "fn": "Hodon Ryu",
                "hasEmail": "mailto:ryu.hodon@epa.gov"
            },
            "distribution": [
                {
                    "title": "Hodon Waterloo final_fasta_working.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/448/Hodon%20Waterloo%20final_fasta_working.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "RNA S1_MEC.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/448/RNA%20S1_MEC.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-11-17",
            "references": [
                "http://www.sciencedirect.com/science/article/pii/S0378775316312174"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Sediment Resuspension Data",
            "description": "The full report on sediment resuspension in drinking water storage tanks and a link to an animation of results. \n\nThis dataset is associated with the following publication:\nHo, C., R. Murray , J. Christian, E. Ching, J. Slavin, J. Ortega, and L. Rossman. Sediment Resuspension and Transport in Water Distribution Storage Tanks.   JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA, 108(6): ., (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "A-69pf-148",
            "keyword": [
                "homeland security",
                "water security",
                "water quality",
                "storage tanks",
                "water distribution",
                "drinking water",
                "sediments",
                "modeling",
                "CFD"
            ],
            "contactPoint": {
                "fn": "Regan Murray",
                "hasEmail": "mailto:murray.regan@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.sandia.gov/cfd-water/sediment-resuspension-in-water-distribution-storage-tanks/",
                    "accessURL": "https://www.sandia.gov/cfd-water/sediment-resuspension-in-water-distribution-storage-tanks/"
                }
            ],
            "modified": "2016-04-01",
            "references": [
                "https://doi.org/10.5942/jawwa.2016.108.0077"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "USEEIO Elementary Flows and Life Cycle Impact Assessment (LCIA) Characterization Factors",
            "description": "This file contains all the elementary flows (defined in ISO 14044) used in the USEEIO model. The elementary flows come from a draft master list used by USEPA modified from the openLCA 1.4 software master list with original flows added. The characterization factors come from the openLCA 1.5.4 method pack or directly from TRACI 2.1 for the TRACI categories, or for the Non-TRACI categories, are originals used simply to sum up all types of resource use of a given type. \n\nThis dataset is associated with the following publication:\nYang, Y., W. Ingwersen, T. Hawkins, and D. Meyer. USEEIO: A new and transparent United States environmentally extended input-output model.   JOURNAL OF CLEANER PRODUCTION. Elsevier Science Ltd, New York, NY, USA, 158: 308-318, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-sj4g-458",
            "keyword": [
                "life cycle impact assessment method",
                "elementary flows",
                "life cycle assessment",
                "life cycle inventory data",
                "sustainability",
                "input-output data"
            ],
            "contactPoint": {
                "fn": "Wesley Ingwersen",
                "hasEmail": "mailto:ingwersen.wesley@epa.gov"
            },
            "distribution": [
                {
                    "title": "USEEIO_ElementaryFlows&LCIAFactors.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/458/USEEIO_ElementaryFlows%26LCIAFactors.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-12-07",
            "references": [
                "https://doi.org/10.1016/j.jclepro.2017.04.150"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data to support \"Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations & Biological Condition\"",
            "description": "Spreadsheets are included here to support the manuscript \"Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition\". \n\nThis dataset is associated with the following publication:\nGolden , H., C. Lane , A. Prues, and E. D'Amico. Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition.   JAWRA. American Water Resources Association, Middleburg, VA, USA, 52(5): 1251-1274, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-7pvt-162",
            "keyword": [
                "riparian buffer",
                "Watershed",
                "watershed management",
                "nutrients",
                "boosted regression tree",
                "Index of Biotic Integrity",
                "statistical model"
            ],
            "contactPoint": {
                "fn": "Heather Golden",
                "hasEmail": "mailto:golden.heather@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHubData_080416.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/162/ScienceHubData_080416.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2014-11-10",
            "references": [
                "http://onlinelibrary.wiley.com/doi/10.1111/1752-1688.12447/abstract"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "USEEIO Satellite Files",
            "description": "These files contain the environmental data as particular emissions or resources associated with a BEA sectors that are used in the USEEIO model. They are organized by the emission or resources type, as described in the manuscript. The main files (without SI) show the final \"satellite tables\" in the 'Exchanges' sheet which have emissions or resource use per USD for 2013. The other sheets in these files provide meta data for the create of the tables, including general information, sources, etc. The 'export' sheet is used for saving the satellite table for csv export. The data dictionary describes the fields in this sheet. The supporting files provide all the details data transformation and organization for the development of the satellite tables. \n\nThis dataset is associated with the following publication:\nYang, Y., W. Ingwersen, T. Hawkins, and D. Meyer. USEEIO: A new and transparent United States environmentally extended input-output model.   JOURNAL OF CLEANER PRODUCTION. Elsevier Science Ltd, New York, NY, USA, 158: 308-318, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-sj4g-455",
            "keyword": [
                "satellite tables",
                "greenhouse gas emissions",
                "water use",
                "energy use",
                "criteria air pollutant emissions",
                "toxic releases",
                "mineral extraction",
                "land use",
                "nutrient releases",
                "life cycle assessment",
                "life cycle inventory data",
                "sustainability",
                "input-output data"
            ],
            "contactPoint": {
                "fn": "Wesley Ingwersen",
                "hasEmail": "mailto:ingwersen.wesley@epa.gov"
            },
            "distribution": [
                {
                    "title": "USEEIO_Satellite_Tables.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/455/USEEIO_Satellite_Tables.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-12-01",
            "references": [
                "https://doi.org/10.1016/j.jclepro.2017.04.150"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/455/documents/USEEIO%20Data%20Dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Mutagenicity of Whole Biodiesel Extracts in Salmonella",
            "description": "Description is in the data set. \n\nThis dataset is associated with the following publication:\nMutlu, E., S. Warren , P. Matthews, C. King , L. Walsh , A. Kligerman, J. Schmid , D. Janek, I. Kooter, B. Linak , I. Gilmour , and D. DeMarini. Health Effects of Soy-Biodiesel Emissions: Mutagenicity-Emission Factors.   INHALATION TOXICOLOGY. Informa Healthcare USA, New York, NY, USA, 27(11): 585-596, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-fbgk-440",
            "keyword": [
                "Mutagenicity",
                "biodiesel",
                "organic extracts",
                "PM",
                "Combustion Emissions",
                "Complex Mixtures"
            ],
            "contactPoint": {
                "fn": "David Demarini",
                "hasEmail": "mailto:demarini.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science Hub Biodiesel Whole Extract data set.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/440/Science%20Hub%20Biodiesel%20Whole%20Extract%20data%20set.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2016-02-12",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Liver steatosis study_PFAA treated mouse gene array data",
            "description": "This file contains a link for Gene Expression Omnibus and the GSE designations for the publicly available gene expression data used in the study and reflected in Figures 6 and 7 for the Das et al., 2016 paper. \n\nThis dataset is associated with the following publication:\nDas, K., C. Wood, M. Lin, A.A. Starkov, C. Lau, K.B. Wallace, C. Corton, and B. Abbott. Perfluoroalky acids-induced liver steatosis:  Effects on genes controlling lipid homeostasis.   TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 378: 32-52, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-1zct-43",
            "keyword": [
                "lipid synthesis",
                "lipid catabolism",
                "perfluorinated chemicals",
                "steatosis",
                "PFOA",
                "PFNA",
                "PFHxS",
                "hepatotoxicity"
            ],
            "contactPoint": {
                "fn": "Barbara Abbott",
                "hasEmail": "mailto:abbott.barbara@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data set 2 Gene MicroArray analysis Das et al 2016.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/43/Data%20set%202%20Gene%20MicroArray%20analysis%20Das%20et%20al%202016.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-05-04",
            "references": [
                "https://doi.org/10.1016/j.tox.2016.12.007"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Liver steatosis study_PFAA treated Wild type and PPAR KO mouse data",
            "description": "Data set 1 consists of the experimental data for the Wild Type and PPAR KO animal study and includes data used to prepare Figures 1-4 and Table 1 of the Das et al, 2016 paper. \n\nThis dataset is associated with the following publication:\nDas, K., C. Wood, M. Lin, A.A. Starkov, C. Lau, K.B. Wallace, C. Corton, and B. Abbott. Perfluoroalky acids-induced liver steatosis:  Effects on genes controlling lipid homeostasis.   TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 378: 32-52, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-1zct-42",
            "keyword": [
                "body weight",
                "liver weight",
                "liver/body weight ratio",
                "cell size",
                "DNA content",
                "lipid",
                "triglyceride",
                "PCR",
                "perfluorinated chemicals",
                "steatosis",
                "PFOA",
                "PFNA",
                "PFHxS",
                "hepatotoxicity"
            ],
            "contactPoint": {
                "fn": "Barbara Abbott",
                "hasEmail": "mailto:abbott.barbara@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data set 1 WT and KO data Das et al 2016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/42/Data%20set%201%20WT%20and%20KO%20data%20Das%20et%20al%202016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-05-04",
            "references": [
                "https://doi.org/10.1016/j.tox.2016.12.007"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Scenarios for low carbon and low water electric power plant operations: implications for upstream water use",
            "description": "The dataset includes all data used in the creation of figures and graphs in the paper: \"Scenarios for low carbon and low water electric power plant operations: implications for upstream water use.\"   Data includes regional electricity mixes, full life cycle water use, and water use for each life cycle stage.  These encompass a range of scenarios out to 2050, and should not be used as predictions, forecasts or official baselines.  The scenarios and results are for research purposes only, and do not represent current or future U.S. EPA policies or regulations. \n\nThis dataset is associated with the following publication:\nDodder , R., J. Barnwell , and W. Yelverton. Scenarios for low carbon and low water electric power plant operations: implications for upstream water use.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(21): 11460-11470, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-2v70-79",
            "keyword": [
                "water",
                "water-",
                "energy",
                "energy system",
                "energy modeling"
            ],
            "contactPoint": {
                "fn": "Rebecca Dodder",
                "hasEmail": "mailto:dodder.rebecca@epa.gov"
            },
            "distribution": [
                {
                    "title": "Water-energy_Dodder_ScienceHub_v2.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/79/Water-energy_Dodder_ScienceHub_v2.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://pubs.acs.org/doi/suppl/10.1021/acs.est.6b03048",
                    "accessURL": "https://pubs.acs.org/doi/suppl/10.1021/acs.est.6b03048"
                }
            ],
            "modified": "2016-05-18",
            "references": [
                "https://doi.org/10.1021/acs.est.6b03048"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supporting Information",
            "description": "This is the supporting information for the journal article. \n\nThis dataset is associated with the following publication:\nRankin, K., S. Mabury, T. Jenkins, and J. Washington. A North American and global survey of perfluoroalkyl substances in surface soils: Distribution patterns and mode of occurrence.   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 161: 333\u2013341, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-qjqm-141",
            "keyword": [
                "PFOA PFOS background soils"
            ],
            "contactPoint": {
                "fn": "John Washington",
                "hasEmail": "mailto:washington.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "160721 American-Global Soil PFASs SI.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/141/160721%20American-Global%20Soil%20PFASs%20SI.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "https://www.sciencedirect.com/science/article/pii/S0045653516308803",
                    "accessURL": "https://www.sciencedirect.com/science/article/pii/S0045653516308803"
                }
            ],
            "modified": "2016-05-02",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2016.06.109"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Link to paper",
            "description": "Link to the paper. \n\nThis dataset is associated with the following publication:\nNaile, J., A.W. Garrison, J. Avants, and J. Washington. Isomers/enantiomers of perfluorocarboxylic acids: Method development and detection in environmental samples.   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 144: 1722-1728, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-v6xj-276",
            "keyword": [
                "Perfluorocarboxylic acids",
                "PFCAs",
                "PFOA",
                "Isomers",
                "Chiral",
                "Enantiomers",
                "Enantioselectivity"
            ],
            "contactPoint": {
                "fn": "John Washington",
                "hasEmail": "mailto:washington.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.sciencedirect.com/science/article/pii/S0045653515302708",
                    "accessURL": "https://www.sciencedirect.com/science/article/pii/S0045653515302708"
                }
            ],
            "modified": "2016-02-29",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supporting Info",
            "description": "Supporting Information. \n\nThis dataset is associated with the following publication:\nWashington , J., T. Jenkins, and E. Weber. Identification of Unsaturated and 2H Polyfluorocarboxylate Homologous Series and Their Detection in Environmental Samples and as Polymer Degradation Products.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 49(22): 13256-13263, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-t4bw-87",
            "keyword": [
                "uPFOA HPFOA uPFCA HPFCA"
            ],
            "contactPoint": {
                "fn": "John Washington",
                "hasEmail": "mailto:washington.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "151008 uPFOA Changes Accepted SI.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/87/151008%20uPFOA%20Changes%20Accepted%20SI.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2015-10-08",
            "references": [
                "https://doi.org/10.1021/acs.est.5b03379"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supporting Info",
            "description": "Supporting Info. \n\nThis dataset is associated with the following publication:\nWashington , J., and T. Jenkins. Abiotic Hydrolysis of Fluorotelomer-Based Polymers as a Source of Perfluorocarboxylates at the Global Scale.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 49(24): 14129-14135, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-8938-86",
            "keyword": [
                "FTP PFOA"
            ],
            "contactPoint": {
                "fn": "John Washington",
                "hasEmail": "mailto:washington.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "151027 WashingtonJenkinsFTPHydrolysisES&TSuppInfo.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/86/151027%20WashingtonJenkinsFTPHydrolysisES%26TSuppInfo.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2015-10-27",
            "references": [
                "https://doi.org/10.1021/acs.est.5b03686"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Future United States Domestic Water Demand  ",
            "description": "Population projections, estimated per capita consumption rate, and estimated total annual water demand to 2100 for four future projections based off the IPCC SRES climate scenarios.  The estimates for water use are based Bayesian regression analysis on 1985, 1990, 1995, 2005 and 2010 water use from USGS. \n\nThis dataset is associated with the following publication:\nPickard, B., M. Nash, J. Baynes, and M. Mehaffey. Planning for community resilience to future United States domestic water demand.   LANDSCAPE AND URBAN PLANNING. Elsevier Science Ltd, New York, NY, USA, 158: 75-86, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-xgz3-193",
            "keyword": [
                "Population",
                "Future Scenarios",
                "Per Capita Use",
                "Baysian Regression",
                "EnviroAtlas",
                "Domestic Water",
                "ecosystem services",
                "Landscape Ecology"
            ],
            "contactPoint": {
                "fn": "Megan Mehaffey",
                "hasEmail": "mailto:mehaffey.megan@epa.gov"
            },
            "distribution": [
                {
                    "title": "LUP_Demand final datas and regressions.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/193/LUP_Demand%20final%20datas%20and%20regressions.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-16",
            "references": [
                "https://doi.org/10.1016/j.landurbplan.2016.07.014"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Aquatic concentrations of chemical analytes compared to ecotoxicity estimates",
            "description": "We describe screening level estimates of potential aquatic toxicity posed by 227 chemical analytes that were measured in 25 ambient water samples collected as part of a joint USGS/USEPA drinking water plant study. Measured concentrations were compared to biological effect concentration (EC) estimates, including USEPA aquatic life criteria, effective plasma concentrations of pharmaceuticals, published toxicity data summarized in the USEPA ECOTOX database, and chemical structure-based predictions. Potential dietary exposures were estimated using a generic 3-tiered food web accumulation scenario. \n\nThis dataset is associated with the following publication:\nKostich , M., R. Flick , A. Batt , H. Mash , S. Boone , E. Furlong, D. Kolpin, and S. Glassmeyer. Aquatic concentrations of chemical analytes compared to ecotoxicity estimates.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 579: 1649-1657, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-xd2v-243",
            "keyword": [
                "water",
                "hazard ratio",
                "ecotoxicity",
                "chemical"
            ],
            "contactPoint": {
                "fn": "Mitchell Kostich",
                "hasEmail": "mailto:kostich.mitchell@epa.gov"
            },
            "distribution": [
                {
                    "title": "Tables20160526a.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/243/Tables20160526a.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "InputData20160526a.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/243/InputData20160526a.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-05-26",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.06.234"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Waterline ATS B. globigii spore water disinfection data",
            "description": "Disinfection of B. globigii spores (a non-pathogenic surrogate for B. anthracis) in clean and dirty water using the ATS-Waterline system, which uses ultraviolet light and a charged membrane filter. \n\nThis dataset is associated with the following publication:\nSilva, G., J. Szabo, V. Namboodiri, R. Krishnan, J. Rodriguez, and A. Zeigler. Evaluation of and environmentally sustainable UV-assisted water treatment system for removal of Bacillus spores in water.   WATER SCIENCE AND TECHNOLOGY. IWA Publishing, London,  UK, 18(3): 968-975, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "A-brvb-452",
            "keyword": [
                "drinking water treatment",
                "bacillus atrophaeus",
                "Bacillus anthracis",
                "Ultraviolet",
                "membrane filter",
                "homeland security"
            ],
            "contactPoint": {
                "fn": "Jeffrey Szabo",
                "hasEmail": "mailto:szabo.jeff@epa.gov"
            },
            "distribution": [
                {
                    "title": "B.globigii bacterial counts and water quallity parameters.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/452/B.globigii%20bacterial%20counts%20and%20water%20quallity%20parameters.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-11-25",
            "references": [
                "https://doi.org/10.2166/ws.2017.165"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "\u201cThe influence of control group reproduction on the statistical power of the Environmental Protection Agency\u2019s Medaka Extended One Generation Reproduction Test (MEOGRT) data for simulations\u201d Dataset",
            "description": "Excel spreadsheet that contains the raw fecundity data used to conduct power simulations specific to the MEOGRT reproductive assessment. \n\nThis dataset is associated with the following publication:\nFlynn, K., J. Swintek, and R. Johnson. The influence of control group reproduction on the statistical power of the Environmental Protection Agency&rsquo;s medaka Extended One-Generation Reproduction Test (MEOGRT).   ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY. Elsevier Science Ltd,  NY, USA, 136: 8-13, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-rv1s-446",
            "keyword": [
                "statistical power",
                "endocrine disruption",
                "fish",
                "aquatic toxicity"
            ],
            "contactPoint": {
                "fn": "Kevin Flynn",
                "hasEmail": "mailto:flynn.kevin@epa.gov"
            },
            "distribution": [
                {
                    "title": "Flynn et al 2016 Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/446/Flynn%20et%20al%202016%20Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-12-03",
            "references": [
                "http://dx.doi.org/10.1016/j.ecoenv.2016.10.024"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A demonstration of the uncertainty in predicting the estrogenic activity of individual chemicals and mixtures from an in vitro estrogen receptor transcriptional activation assay (T47D-KBluc) to the in vivo uterotrophic assay using oral exposure",
            "description": "the data set contains the figures and tables from the publication in addition to the means, standard errors of the mean and the sample sizes used in each group for every experiment.  the data set also contains a description of the genes, their function and acronyms on the QPCR arrays used in the study.  Finally, the dataset includes the histopathology reports on the uterine changes induced by the different chemicals and the criteria used by the pathologist to classify the estrogenic effects of the chemicals. \n\nThis dataset is associated with the following publication:\nConley, J., B. Hannas, V. Wilson, E. Gray, and J. Furr. A demonstration of the uncertainty in predicting the estrogenic activity of individual chemicals and mixtures from an in vitro estrogen receptor transcriptional activation assay (T47D-KBluc) to the in vivo uterotrophic assay using oral exposure.   TOXICOLOGICAL SCIENCES. Society of Toxicology,     382-395, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-280k-428",
            "keyword": [
                "estrogenic activity in vitro and in vivo",
                "uterine weight",
                "uterine histology",
                "in vitro in vivo extrapolation",
                "prediction of in vivo effects from in vitro gene expression",
                "environmental estrogens",
                "in vitro to in vivo extrapolation",
                "uterine estrogenic response"
            ],
            "contactPoint": {
                "fn": "Justin Conley",
                "hasEmail": "mailto:conley.justin@epa.gov"
            },
            "distribution": [
                {
                    "title": "Conley_IVIVE_Science hub file final 10 3 2016.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/428/Conley_IVIVE_Science%20hub%20file%20final%2010%203%202016.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-10-03",
            "references": [
                "https://doi.org/10.1093/toxsci/kfw134"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Potential Vorticity based parameterization for specification of Upper troposphere/lower stratosphere ozone in atmospheric models",
            "description": "Potential Vorticity based parameterization for specification of Upper troposphere/lower stratosphere ozone in atmospheric models - the data set consists of 3D O3 fields from the CMAQ modeling system across the northern hemisphere,  potential vorticity fields from the WRF model, and observated ozone from the WOUDC ozonesonde launches. \n\nThis dataset is associated with the following publication:\nMathur, R., J. Pleim, C. Hogrefe, M. Gan, G. Sarwar, D. Wong, J. Wang, S. McKeen, J. Xing, and J. Wang. Representing the effects of stratosphere\u2013troposphere exchange on 3-D O3 distributions in chemistry transport models using a potential vorticity-based parameterization.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 16: 10865-10877, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-ffbt-207",
            "keyword": [
                "stratosphere-troposphere exchange",
                "Ozone",
                "CMAQ",
                "Potential vorticity"
            ],
            "contactPoint": {
                "fn": "Rohit Mathur",
                "hasEmail": "mailto:mathur.rohit@epa.gov"
            },
            "distribution": [
                {
                    "title": "PV_Fig_plot_data_location_updated.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/207/PV_Fig_plot_data_location_updated.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-07-11",
            "references": [
                "https://doi.org/10.5194/acp-16-10865-2016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Phoenix Study",
            "description": "Phoenix Traffic and Mobile Data. \n\nThis dataset is associated with the following publication:\nBaldauf , R., V. Isakov , P. Deshmukh, and A. Venkatram. Influence of Solid Noise Barriers on Near-Road and On-Road Air Quality.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 129: 265-276, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-vmdh-416",
            "keyword": [
                "air quality",
                "near road",
                "noise barriers",
                "emissions",
                "traffic"
            ],
            "contactPoint": {
                "fn": "Vladilen Isakov",
                "hasEmail": "mailto:isakov.vlad@epa.gov"
            },
            "distribution": [
                {
                    "title": "Phoenix Traffic Data Analysis.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/416/Phoenix%20Traffic%20Data%20Analysis.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Phoenix Open_Barrier Data Analysis.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/416/Phoenix%20Open_Barrier%20Data%20Analysis.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-10-21",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2016.01.025"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figures",
            "description": "data for figures 1-8 in journal article \"Assessment of port-related air quality impacts: geographic analysis of population\", International Journal of Environment and Pollution, 58, 231-250, (2015). \n\nThis dataset is associated with the following publication:\nArunachalam , S., H. Brantley , T. Barzyk , G. Hagler , V. Isakov , S. Kimbrough , B. Naess, N. Rice, M. Snyder, K. Talgo, and A. Venkatram. Assessment of port-related air quality impacts: geographic analysis of population.   INTERNATIONAL JOURNAL OF ENVIRONMENT AND POLLUTION. Inderscience Enterprises Limited, Geneva,  SWITZERLAND, 58(4): 231 - 250, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-hqcc-208",
            "keyword": [
                "ports",
                "emissions",
                "air quality",
                "dispersion modeling",
                "GIS",
                "Population",
                "exposure"
            ],
            "contactPoint": {
                "fn": "Vladilen Isakov",
                "hasEmail": "mailto:isakov.vlad@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figures1to8.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/208/Figures1to8.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2014-12-18",
            "references": [
                "https://doi.org/10.1504/ijep.2015.077455"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Detroit Exposure and Aerosol Research Study",
            "description": "The DEARS represents a multipollutant spatial characterization of six neighborhoods and their residents in and around Detroit, Michigan.  Personal, residential indoor, residential outdoor, and ambient monitoring was performed.  Survey information was collected simultaneously with air quality monitoring to provide the means to examine a wide variety of exposure factors on personal exposure. \n\nThis dataset is associated with the following publication:\nLogue, J., M. Sherman, M. Lunden, N. Klepeis, R. Williams , C. Croghan , and B. Singer. Development and assessment of a physics-based simulation model to investigate residential PM2.5 infiltration across the US housing stock.   BUILDING AND ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 94(1): 21-32, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-ttfk-15",
            "keyword": [
                "DEARS",
                "personal",
                "residential",
                "particulate matter",
                "ambient",
                "air quality"
            ],
            "contactPoint": {
                "fn": "Ronald Williams",
                "hasEmail": "mailto:williams.ronald@epa.gov"
            },
            "distribution": [
                {
                    "title": "fuqdoors.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/15/fuqdoors.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "fuqETS.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/15/fuqETS.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "fuqwindowfan.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/15/fuqwindowfan.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "fuqwindows.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/15/fuqwindows.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "fuqbase.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/15/fuqbase.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "pmall.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/15/pmall.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "residence.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/15/residence.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "https://archive.epa.gov/heasd/archive-dears/web/html/info-2.html",
                    "accessURL": "https://archive.epa.gov/heasd/archive-dears/web/html/info-2.html"
                }
            ],
            "modified": "2014-11-12",
            "references": [
                "https://doi.org/10.1016/j.buildenv.2015.06.032"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/15/documents/dictionary.csv",
            "describedByType": "text/csv",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data",
            "description": "This dataset documents the source of the data analyzed in the manuscript \" Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data\" led by Dr. Ioannis Kioutsioukis of the European Commission's Joint Research Center. All of the data were contributed by non-EPA research groups from Europe. This dataset is not publicly accessible because: None of the data analyzed in this manuscript was contributed by EPA. It can be accessed through the following means: The datasets used for analysis by the external author of this manuscript were provided by researchers from more than ten non-EPA research groups from Europe participating in the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). All data used in the manuscript are stored on the web-based password-protected ENSEMBLE platform hosted by the European Commission\u2019s Joint Research Centre at http://ensemble3.jrc.it/. Interested researchers can request access to the AQMEII dataset hosted on the ENSEMBLE platform by contacting Dr. Stefano Galmarini (stefano.galmarini@jrc.ec.europa.eu). Format: N/A. \n\nThis dataset is associated with the following publication:\nKioutsioukis, I., U. Im, E. Solazzo, R. Bianconi, A. Badia, A. Balzarini, R. Baro, R. Bellasio, D. Brunner, C. Chemel, G. Curci, H. Denier va der Gon, J. Flemming, R. Forkel, L. Giordano, P. Jimenez-Guerrero, M. Hirtl, O. Jorba, A. Manders-Groot, L. Neal, J. Perez, G. Pirovano, R. San Jose, N. Savage, W. Schroder, R. Sokhi, D. Syrakov, P. Tuccella, J. Werhahn, R. Wolke, C. Hogrefe, and S. Galmarini. Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 16(24): 15629-15652, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-3n5x-494",
            "keyword": [
                "ensemble modeling ensemble averaging",
                "model intercomparison",
                "AQMEII",
                "air quality forecasting"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [],
            "modified": "2014-01-01",
            "references": [
                "https://doi.org/10.5194/acp-16-15629-2016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Excel file of salivary antibody analysis for Boqueron Beach study, Puerto Rico for six waterborne pathogens.",
            "description": "This dataset is the raw Luminex antibody responses to six common waterborne pathogens reported in MFI (Median Fluorescence Intensity) units. \n\nThis dataset is associated with the following publication:\nAugustine , S., T. Eason , K. Simmons, C. Curioso, S. Griffin , M. Ramudit, and T. Plunkett. Developing a Salivary Antibody Multiplex Immunoassay to Measure Human Exposure to Environmental Pathogens.   Journal of Visualized Experiments. JoVE, Somerville, MA, USA, 115: e54415, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-k0ph-136",
            "keyword": [
                "Multiplex",
                "immunoassay",
                "salivary antibody",
                "saliva",
                "exposure",
                "bead-based multiplexing",
                "carboxylated microspheres",
                "bead coupling",
                "coupling confirmation"
            ],
            "contactPoint": {
                "fn": "Swinburne Augustine",
                "hasEmail": "mailto:augustine.swinburne@epa.gov"
            },
            "distribution": [
                {
                    "title": "Copy of JOVE 6Ag(raw data only).xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/136/Copy%20of%20JOVE%206Ag%28raw%20data%20only%29.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-09-04",
            "references": [
                "https://doi.org/10.3791/54415"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/136/documents/Data%20dictionary_saliva%20JoVE.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Significance of dissolved methane in effluents of anaerobically treated low strength wastewater and potential for recovery as an energy product: A review",
            "description": "The data set includes estimations of energy required for processes related to the operation of Anaerobic Membrane Bioreactors. \n\nThis dataset is associated with the following publication:\nCrone, B., J. Garland, G. Sorial, and L. Vane. Significance of dissolved methane in effluents of anaerobically treated low strength wastewater and potential for recovery as an energy product: A review.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 104: 520-531, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-hx3w-371",
            "keyword": [
                "Anaerobic Treatment",
                "energy and water"
            ],
            "contactPoint": {
                "fn": "Jay Garland",
                "hasEmail": "mailto:garland.jay@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science Hub Data Submission.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/371/Science%20Hub%20Data%20Submission.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://www.sciencedirect.com/science/article/pii/S0043135416306194",
                    "accessURL": "https://www.sciencedirect.com/science/article/pii/S0043135416306194"
                }
            ],
            "modified": "2016-09-19",
            "references": [
                "https://doi.org/10.1016/j.watres.2016.08.019"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "LenoxKaplan_Role of natural gas in meeting electric sector emissions reduction strategy_dataset",
            "description": "This dataset is for an analysis that used the MARKAL linear optimization model to compare the carbon emissions profiles and system-wide global warming potential of the U.S. energy system over a series of model runs in which the power sector is required to meet a specific carbon dioxide reduction target across a number of scenarios in which the availability of natural gas changes.  Scenarios are run with carbon dioxide emissions and a range of upstream methane emission leakage rates from natural gas production along with upstream methane and carbon dioxide emissions associated with production of coal and oil. \n\nThis dataset is associated with the following publication:\nLenox , C., and O. Kaplan. Role of natural gas in meeting an electric sector emissions reduction strategy and effects on greenhouse gas emissions.   Energy Economics. Elsevier B.V., Amsterdam,  NETHERLANDS, 60: 460-468, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-nvxh-83",
            "keyword": [
                "energy system",
                "scenario analysis",
                "carbon emissions",
                "Methane",
                "natural gas",
                "energy",
                "systems analyses",
                "modeling",
                "Greenhouse gas",
                "air quality",
                "MARKAL"
            ],
            "contactPoint": {
                "fn": "Carol Lenox",
                "hasEmail": "mailto:lenox.carol@epa.gov"
            },
            "distribution": [
                {
                    "title": "LenoxKaplan NatGas EMF31 paper data tables with data dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/83/LenoxKaplan%20NatGas%20EMF31%20paper%20data%20tables%20with%20data%20dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-05-26",
            "references": [
                "https://doi.org/10.1016/j.eneco.2016.06.009"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A Reduced Form Model for Ozone Based on Two Decades of CMAQ Simulations for the Continental United States",
            "description": "File containing the locations where the gridded datasets used in the analysis presented in this manuscript are archived. The actual gridded datasets are too large to upload to sciencehub (several terabytes). \n\nThis dataset is associated with the following publication:\nPorter, P.S., S.T. Rao, C. Hogrefe, and R. Mathur. A Reduced Form Model for Ozone Based on Two Decades of CMAQ Simulations for the Continental United States.   Atmospheric Pollution Research. Turkish National Committee for Air Pollution Research and Control, Izmir,  TURKEY, 8(2): 275-284, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-6m95-260",
            "keyword": [
                "Reduced form model",
                "meteorological adjustment",
                "emission trends",
                "Air quality trends",
                "long-term CMAQ modeling"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "PorterEtAl_APR_Data_Locations.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/260/PorterEtAl_APR_Data_Locations.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2015-12-22",
            "references": [
                "https://doi.org/10.1016/j.apr.2016.09.005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "An Integrated Approach for Identifying Priority Contaminant in the Great Lakes Basin \u2013Investigations in the Lower Green Bay/Fox River and Milwaukee Estuary Areas of Concern",
            "description": "Prioritization of chemicals was performed on two Areas of Concerns in the Great Lakes\nAn integrated risk surveillance and monitoring approach was applied\nBio-effect prediction methodologies were used to identify additional biological pathways. \n\nEnvironmental assessment of complex mixtures typically requires integration of chemical and biological measurements. This study demonstrates the use of a combination of instrumental chemical analyses, effects-based monitoring, and  bio-effects prediction approaches to help identify potential hazards and priority contaminants in two Great Lakes Areas of Concern (AOCs), the Lower Green Bay/Fox River  located near Green Bay, WI, USA and the Milwaukee Estuary, located near Milwaukee, WI, USA. Fathead minnows were caged  at four sites within each AOC (eight sites total). Following 4 d of in situ exposure, tissues and biofluids were sampled and used for targeted biological effects analyses. Additionally, 4 d composite water samples were collected concurrently at each caged fish site and analyzed for 132 analytes as well as evaluated for total estrogenic and androgenic activity using cell-based bioassays. Of the analytes examined, 75 were detected in composite samples from at least one site. Based on multiple analyses, one site in the East River and another site near a paper mill discharge in the Lower Green Bay/Fox River AOC, were prioritized due to their estrogenic and androgenic activity, respectively. The water samples from other sites generally did not exhibit significant estrogenic or androgenic activity, nor was there evidence for endocrine disruption in the fish exposed at these sites as indicated by the lack of alterations in ex vivo steroid production, circulating steroid concentrations, or vitellogenin mRNA expression in males. Induction of hepatic cyp1a mRNA expression was detected at several sites, suggesting the presence of chemicals that activate the Ah receptor.  To expand the scope beyond targeted investigation of endpoints selected a priori, several bio-effects prediction approaches were employed to identify other potentially disturbed biological pathways and related chemical constituents that may warrant future monitoring at these sites. For example, several  chemicals such as diethylphthalate and naphthalene , and genes and related pathways, such as cholinergic receptor muscarinic 3 (CHRM3), estrogen receptor alpha1 (esr1), chemokine ligand 10 protein (CXCL10), tumor protein p53 (p53), and monoamine oxidase B (Maob), were identified as candidates for future assessments at these AOCs. Overall, this study demonstrates that a better prioritization of contaminants and associated hazards can be achieved through integrated evaluation of multiple lines of evidence. Such prioritization can guide more comprehensive follow-up risk assessment efforts. \n\nThis dataset is associated with the following publication:\nLi, S., D. Villeneuve, J. Berninger, B. Blackwell, J. Cavallin, M. Hughes, K. Jensen, Z. Jorgenson, M. Kahl, A. Schroeder, K. Stevens, L. Thomas, M. Weberg, and G. Ankley. An integrated approach for identifying priority contaminant in the Great Lakes Basin -Investigations in the Lower Green Bay/Fox River and Milwaukee Estuary areas of concern.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 579: 825-837, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-5tb8-418",
            "keyword": [
                "adverse outcome pathway",
                "biomarkers",
                "screening and prioritization",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/418/ScienceHub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-29",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.11.021"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Ecosystem services in the St. Louis River AOC",
            "description": "Dataset indicates the presence or absence of each ecosystems service at each coordinate Location. Also included are depth, fetch, and aquatic vegetation data. See supporting information for SAS code used to process data, sources of public spatial data, logic of GIS models used to generate presence absence assignments, GIS processing metadata, and KMZ maps (zipped file). \n\nThis dataset is associated with the following publication:\nAngradi , T., J. Launspach, D. Bolgrien , B. Bellinger, M. Starry, J. Hoffman , A. Trebitz , M. Sierszen , and T. Hollenhorst. Mapping ecosystem service indicators in a Great Lakes estuarine Area of Concern.   JOURNAL OF GREAT LAKES RESEARCH. International Association for Great Lakes Research, Ann Arbor, MI, USA, 42(3): 717-727, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-1ns3-80",
            "keyword": [
                "Ecosystems services",
                "ecosystem services",
                "Area of Concern"
            ],
            "contactPoint": {
                "fn": "Theodore Angradi",
                "hasEmail": "mailto:angradi.theodore@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science_hub_combinepointproject_2_9_16.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/80/Science_hub_combinepointproject_2_9_16.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-02-09",
            "references": [
                "https://doi.org/10.1016/j.jglr.2016.03.012",
                "https://pasteur.epa.gov/uploads/80/documents/Ecoservices_KMZ.zip"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Influence of exposure differences on city-to-city heterogeneity in PM2.5-mortality associations in U.S. Cities",
            "description": "This dataset contains information on the cluster characteristics, health effect estimates, and the meta-regression results. \n\nThis dataset is associated with the following publication:\nBaxter, L., J. Crooks, and J. Sacks. Influence of exposure differences on city-to-city heterogeneity in PM2.5-mortality associations in US cities.   ENVIRONMENTAL HEALTH. Academic Press Incorporated, Orlando, FL, USA, 16(1): 1-8, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-15dx-523",
            "keyword": [
                "Fine Particulate Matter",
                "epidemiology",
                "air pollution exposure"
            ],
            "contactPoint": {
                "fn": "Lisa Baxter",
                "hasEmail": "mailto:baxter.lisa@epa.gov"
            },
            "distribution": [
                {
                    "title": "Baxter_A-15dx_datasets.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/523/Baxter_A-15dx_datasets.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-12-20",
            "references": [
                "https://doi.org/10.1186/s12940-016-0208-y"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Quantitative Structure-Use Relationship Model Predictions to evaluate Tox21 Chemicals as Functional Substitutes and Candidate Alternatives",
            "description": "This dataset provides a prediction for all Tox21 chemicals with available QSUR descriptors across all 41 valid QSUR models developed with FUse. \n\nThis dataset is associated with the following publication:\nPhillips, K., J. Wambaugh, C. Grulke, K. Dionisio, and K. Isaacs. High-throughput screening of chemicals as functional substitutes using structure-based classification models.   GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge,  UK, 19: 1063-1074, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-wdcg-510",
            "keyword": [
                "ExpoCast",
                "functional use",
                "qsar",
                "machine learning algorithms",
                "consumer products",
                "alternatives assement",
                "high-throughput screening"
            ],
            "contactPoint": {
                "fn": "Katherine Phillips",
                "hasEmail": "mailto:phillips.katherine@epa.gov"
            },
            "distribution": [
                {
                    "title": "qsur_predictions_for_tox21_library.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/510/qsur_predictions_for_tox21_library.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-11-30",
            "references": [
                "https://doi.org/10.1039/c6gc02744j"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Functional Use Database (FUse)",
            "description": "There are five different files for this dataset:\n1. A dataset listing the reported functional uses of chemicals (FUse)\n2. All 729 ToxPrint descriptors obtained from ChemoTyper for chemicals in FUse\n3. All EPI Suite properties obtained for chemicals in FUse\n4. The confusion matrix values, similarity thresholds, and bioactivity index for each model.\n5. The functional use prediction, bioactivity index, and prediction classification (poor prediction, functional substitute, candidate alternative) for each Tox21 chemical. \n\nThis dataset is associated with the following publication:\nPhillips, K., J. Wambaugh, C. Grulke, K. Dionisio, and K. Isaacs. High-throughput screening of chemicals as functional substitutes using structure-based classification models.   GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge,  UK, 19: 1063-1074, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-wdcg-495",
            "keyword": [
                "ExpoCast",
                "functional use",
                "qsar",
                "machine learning algorithms",
                "consumer products",
                "alternatives assement",
                "high-throughput screening"
            ],
            "contactPoint": {
                "fn": "Katherine Phillips",
                "hasEmail": "mailto:phillips.katherine@epa.gov"
            },
            "distribution": [
                {
                    "title": "functional_use_database.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/495/functional_use_database.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-11-30",
            "references": [
                "https://doi.org/10.1039/c6gc02744j"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Quantitative Structure-Use Relationship (QSUR) Model Descriptors",
            "description": "This data set contains ToxPrint finger prints for all chemicals in FUse that had QSAR-ready SMILES strings as well as select physicochemical properties from the Estimation Program Interface Suite (EPI Suite) program. \n\nThis dataset is associated with the following publication:\nPhillips, K., J. Wambaugh, C. Grulke, K. Dionisio, and K. Isaacs. High-throughput screening of chemicals as functional substitutes using structure-based classification models.   GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge,  UK, 19: 1063-1074, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-wdcg-508",
            "keyword": [
                "ExpoCast",
                "functional use",
                "qsar",
                "machine learning algorithms",
                "consumer products",
                "alternatives assement",
                "high-throughput screening"
            ],
            "contactPoint": {
                "fn": "Katherine Phillips",
                "hasEmail": "mailto:phillips.katherine@epa.gov"
            },
            "distribution": [
                {
                    "title": "toxprint_structural_descriptors.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/508/toxprint_structural_descriptors.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "epi_suite_physicochemical_properties.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/508/epi_suite_physicochemical_properties.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-11-30",
            "references": [
                "https://doi.org/10.1039/c6gc02744j"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Quantitative Structure-Use Relationship Model thresholds for Model Validation, Domain of Applicability, and Candidate Alternative Selection",
            "description": "This file contains value of the model training set confusion matrix, domain of applicability evaluation based on training set to predicted chemicals structural similarity, and 75th percentile bioactivity index values for each QSUR model. \n\nThis dataset is associated with the following publication:\nPhillips, K., J. Wambaugh, C. Grulke, K. Dionisio, and K. Isaacs. High-throughput screening of chemicals as functional substitutes using structure-based classification models.   GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge,  UK, 19: 1063-1074, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-wdcg-509",
            "keyword": [
                "ExpoCast",
                "functional use",
                "qsar",
                "machine learning algorithms",
                "consumer products",
                "alternatives assement",
                "high-throughput screening"
            ],
            "contactPoint": {
                "fn": "Katherine Phillips",
                "hasEmail": "mailto:phillips.katherine@epa.gov"
            },
            "distribution": [
                {
                    "title": "qsur_model_rankings_and_thresholds.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/509/qsur_model_rankings_and_thresholds.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-11-30",
            "references": [
                "https://doi.org/10.1039/c6gc02744j"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Turkey Run Landfill Emissions Dataset",
            "description": "landfill emissions measurements for the Turkey run landfill in Georgia. \n\nThis dataset is associated with the following publication:\nDe la Cruz, F., R. Green, G. Hater, J. Chanton, E. Thoma , T. Harvey, and M. Barlaz. Comparison of Field Measurements at a New Landfill to Methane Emissions Models.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(17): 9483-9441, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-0gb7-449",
            "keyword": [
                "Methane",
                "Landfill",
                "OTM 33B",
                "Mobile Measurements"
            ],
            "contactPoint": {
                "fn": "Eben Thoma",
                "hasEmail": "mailto:thoma.eben@epa.gov"
            },
            "distribution": [
                {
                    "title": "Landfill Emissions Study Data Set and Dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/449/Landfill%20Emissions%20Study%20Data%20Set%20and%20Dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-10",
            "references": [
                "https://doi.org/10.1021/acs.est.6b00415"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "2016 Uinta Basin Pneumatic Controller Study Database",
            "description": "2016 Uinta Basin Pneumatic Controller Study Database: This study along with select figures and calculations. \n\nThis dataset is associated with the following publication:\nThoma, E., P. Deshmukh, R. Logan, M. Stovern, C. Dresser, and H. Brantley. Assessment of Uinta Basin Oil and Natural Gas Well Pad Pneumatic Controller Emissions.   Journal of Environmental Protection. Scientific Research Publishing, Inc., Irvine, CA, USA, 8(4): 394-415, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-kh1r-460",
            "keyword": [
                "Pneumatic Controller",
                "Oil and Natural Gas Production",
                "Uinta Basin",
                "Methane",
                "volatile organic compounds"
            ],
            "contactPoint": {
                "fn": "Eben Thoma",
                "hasEmail": "mailto:thoma.eben@epa.gov"
            },
            "distribution": [
                {
                    "title": "2016 Uinta Basin PC Study Summary_122016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/460/2016%20Uinta%20Basin%20PC%20Study%20Summary_122016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "QAPP-1J16-019.R1 QT16006_04 QAPP Uinta Basin PC Study WA 1-037_final.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/460/QAPP-1J16-019.R1%20QT16006_04%20QAPP%20Uinta%20Basin%20PC%20Study%20WA%201-037_final.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Canister Data.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/460/Canister%20Data.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Kimray Controller Vent Calculator.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/460/Kimray%20Controller%20Vent%20Calculator.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Alicat Viscosity correction.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/460/Alicat%20Viscosity%20correction.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-12-16",
            "references": [
                "https://doi.org/10.4236/jep.2017.84029"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Comparison of cryopreserved trout hepatocytes and liver S9 fractions as in vitro tools for bioaccumulation assessment of chemicals that undergo biotransformation in fish",
            "description": "The purpose of this study was to compare two in vitro systems, cryopreserved trout hepatocytes and trout liver S9 fractions, used to predict in vivo levels of biotransformation in fish.  This information is needed to refine modeled estimates of bioaccumulation for hydrophobic organic chemicals that undergo biotransformation.  In this effort we used trout hepatocytes to measure in vitro biotransformation of 6 polycyclic aromatic hydrocarbons (PAHs).  The results were compared to metabolism rates reported previously for trout liver S9 fractions.  Results obtained using both in vitro systems were then used to predict measured levels of hepatic clearance for the same test chemicals exhibited by isolated perfused livers.  The results of this study suggest that both in vitro systems are well suited for performing in vitro-in vivo metabolism extrapolations with fish as a means for improving modeled bioaccumulation predictions. \n\nThis dataset is associated with the following publication:\nFay, K., P. Fitzsimmons, A. Hoffman, and J. Nichols. Comparison of trout hepatocytes and liver S9 fractions  as in vitro models for predicting hepatic clearance in fish.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry,  FL, USA, 36(2): 463-471, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-b2rm-195",
            "keyword": [
                "bioaccumulation",
                "rainbow trout fish",
                "biotransformation",
                "in vitro-in vivo extrapolation",
                "fish",
                "rainbow trout"
            ],
            "contactPoint": {
                "fn": "John Nichols",
                "hasEmail": "mailto:nichols.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "Fay et al 2016_IPL_Hep_Comparison_ Science Hub Data Summary_final.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/195/Fay%20et%20al%202016_IPL_Hep_Comparison_%20Science%20Hub%20Data%20Summary_final.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-04-18",
            "references": [
                "https://doi.org/10.1002/etc.3572"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "E331 Behavior TP HF RW O3 SHC2.63",
            "description": "Human and animal studies indicate that maternal obesity can negatively impact aspects of metabolism and neurodevelopment in the offspring.  Not known, however, is whether maternal exercise can alter these adverse outcomes.  In this study, Long-Evans female rats were provided a high fat (60%; HFD) or control diet (CD) 44 days before mating and throughout gestation and lactation.  Running wheels were available to half of each diet group during the gestational period only: CD diet with (CDRW) or without (sedentary; CDSED) exercise, and HFD with (HFRW) or without (HFSED) exercise.  The offspring in this study were put on control diet after weaning and examined using a number of behavioral evaluations up to 4 months of age.  Offspring of CDRW dams weighed less than offspring from CDSED dams, as well as from HFD dams.  After weaning, the lower weight in CDRW offspring persisted in male, but not female, rats.  Male (females not tested) offspring from HFSED dams performed worse than other groups in a Morris water maze during initial spatial training as well as reversal learning; memory was not impacted.  Female, but not male, offspring from the HFSED dams showed less preference for chocolate milk during a 2-bottle choice test.  No differences were seen in tests of novel object recognition, social approach, or locomotor activity.  Thus, maternal diet and exercise produced differential effects on growth and selective behaviors in the offspring, and the data demonstrate a positive impact of maternal exercise on the offspring in that it ameliorated some deleterious behavioral effects of a maternal high fat diet. \n\nThis dataset is associated with the following publication:\nMoser, V., K. Mcdaniel, E. Wooland, P. Phillips, J. Franklin, and C. Gordon. IMPACTS OF MATERNAL DIET AND EXERCISE ON OFFSPRING BEHAVIOR AND GROWTH.   NEUROTOXICOLOGY AND TERATOLOGY. Elsevier Science Ltd, New York, NY, USA,  46-50, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-jdg3-531",
            "keyword": [
                "Maternal Diet",
                "Offspring",
                "behavior",
                "Exercise",
                "Rat"
            ],
            "contactPoint": {
                "fn": "Christopher Gordon",
                "hasEmail": "mailto:gordon.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "GordonChristopher_E331 Behavior TP HF O3 SHC 2_63_dataset_20170314 SCID A-jdg3.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/531/GordonChristopher_E331%20Behavior%20TP%20HF%20O3%20SHC%202_63_dataset_20170314%20SCID%20A-jdg3.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-24",
            "references": [
                "https://doi.org/10.1016/j.ntt.2017.07.002"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "E331 TP HF RW O3 SHC2.63 SCID: A-bvqk",
            "description": "Data for differing physiological measures of dams on high fat or control diet with/without exercise and physiological effects on male and female offspring. \n\nThis dataset is associated with the following publication:\nGordon, C., P. Phillips, A. Johnstone, J. Schmid, M. Schladweiler, A. Ledbetter, S. Snow, and U. Kodavanti. EFFECTS OF MATERNAL HIGH FAT DIET AND SEDENTARY LIFESTYLE ON SUSCEPTIBILITY OF ADULT OFFSPRING TO OZONE EXPOSURE IN RATS.   INHALATION TOXICOLOGY. Informa Healthcare USA, New York, NY, USA,  239-254, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-bvqk-530",
            "keyword": [
                "Maternal Diet",
                "Sedentary",
                "Exercise",
                "Rat",
                "pulmonary",
                "Offspring",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Christopher Gordon",
                "hasEmail": "mailto:gordon.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "GordonChristopher_E331 TP HF O3 SHC 2_63_dataset_20170309 SCID A-bvqk.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/530/GordonChristopher_E331%20TP%20HF%20O3%20SHC%202_63_dataset_20170309%20SCID%20A-bvqk.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-17",
            "references": [
                "https://doi.org/10.1080/08958378.2017.1342719"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "PM mass and elemental species concentration data for I-96 monitoring sites",
            "description": "PM2.5 (fine) and PM10-2.5 (coarse) mass concentrations for monitoring sites located 10 m, 100 m and 300 m north of Interstate I-96 in Detroit, the water-soluble and acid-soluble elemental species concentrations for each, and results of factor analysis using these data. \n\nThis dataset is associated with the following publication:\nOakes, M., J. Burke, G. Norris, K. Kovalcik, J.P. Pancras, and M. Landis. Near-road enhancement and solubility of fine and coarse particulate matter trace elements near a major interstate in Detroit, Michigan.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 145: 213-224, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-69pg-518",
            "keyword": [
                "air pollution",
                "particulate matter",
                "near road",
                "Trace metals",
                "Traffic sources",
                "Brake wear"
            ],
            "contactPoint": {
                "fn": "Janet Burke-Norris",
                "hasEmail": "mailto:burke.janet@epa.gov"
            },
            "distribution": [
                {
                    "title": "A-69pg_Data_Files.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/518/A-69pg_Data_Files.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-09-12",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2016.09.034"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for GMD article \"A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1\"",
            "description": "These data were used to generate the figures included in the following manuscript: Fahey, et al. (2017) \"A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1\". Geosci. Mod. Dev. \n\nThis dataset is associated with the following publication:\nFahey, K., A. Carlton, H. Pye, J. Baek, B. Hutzell, C. Stanier, K. Baker, W. Appel, M. Jaoui, and J. Offenberg. A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1.   Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 10: 1587-1605, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-wh7p-547",
            "keyword": [
                ": aqueous chemistry",
                "clouds",
                "CMAQ",
                "KPP",
                "sulfate",
                "SOA"
            ],
            "contactPoint": {
                "fn": "Kathleen Fahey",
                "hasEmail": "mailto:fahey.kathleen@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure-data_Fahey.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/547/Figure-data_Fahey.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-04",
            "references": [
                "https://doi.org/10.5194/gmd-10-1587-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Laboratory simulations of the atmospheric mixed layer in flow over complex terrain",
            "description": "A laboratory study of the influence of complex terrain on the interface between a well-mixed boundary layer and an elevated stratified layer was conducted in the towing-tank facility of the U.S. Environmental Protection Agency.  The height of the mixed layer in the daytime boundary layer can have a strong influence on the concentration of pollutants within this layer.  Deflections of streamlines at the height of the interface are primarily a function of hill Froude number (Fr), the ratio of mixed-layer height (zi) to terrain height (h), and the crosswind dimension of the terrain.  The magnitude of the deflections increases as Fr increases and zi / h decreases.  For mixing-height streamlines that are initially below the terrain top, the response is linear with Fr; for those initially above the terrain feature the response to Fr is more complex.  Once Fr exceeds about 2, the terrain-related response of the mixed layer interface decreases somewhat with increasing Fr (toward more neutral flow).  Deflections are also shown to increase as the crosswind dimensions of the terrain increases.  Comparisons with numerical modeling, limited field data and other laboratory measurements reported in the literature are favorable. Additionally, visual observations of dye streamers suggests that the flow structure exhibited for our elevated inversions passing over three dimensional hills is similar to that reported in the literature for continuously stratified flow over two-dimensional hills. \n\nThis dataset is associated with the following publication:\nPerry, S., and W. Snyder. Laboratory simulations of the atmospheric mixed-layer in flow over complex topography.   PHYSICS OF FLUIDS. Physics of Fluids,    29(2): 020702, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-w6n0-522",
            "keyword": [
                "atmospheric mixed layer",
                "complex terrain",
                "stratified water channel"
            ],
            "contactPoint": {
                "fn": "Steven Perry",
                "hasEmail": "mailto:perry.steven@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure 4 data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/522/Figure%204%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 6 data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/522/Figure%206%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 7 data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/522/Figure%207%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 8 data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/522/Figure%208%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 9 data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/522/Figure%209%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 10 data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/522/Figure%2010%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 11 data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/522/Figure%2011%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-10-03",
            "references": [
                "https://doi.org/10.1063/1.4974505"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/522/documents/A-w6n0-DataDictionaryMLCT-Perry-20160805.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Estimation of pyrethroid pesticide intake using regression modeling of food groups based on composite dietary samples",
            "description": "Population-based estimates of pesticide intake are needed to characterize exposure for particular demographic groups based on their dietary behaviors. Regression modeling performed on measurements of selected pesticides in composited duplicate diet samples allowed 1) estimation of pesticide intakes for a defined demographic community, and 2) comparison of dietary pesticide intakes between the composite and individual samples. Extant databases were useful for assigning individual samples to composites, but they could not provide the breadth of information needed to facilitate measurable levels in every composite. Composite sample measurements were found to be good predictors of pyrethroid pesticide levels in their individual sample constituents where sufficient measurements are available above the method detection limit. Statistical inference shows little evidence of differences between individual and composite measurements and suggests that regression modeling of food groups based on composite dietary samples may provide an effective tool for estimating dietary pesticide intake for a defined population. \n\nThis dataset is associated with the following publication:\nMichael, L., G.G. Brown, and L. Melnyk. Estimation of pyrethroid pesticide intake using regression modeling of food groups based on composite dietary samples...   Journal of Environmental Science and Health. Part B, Pesticides, Food Contaminants, and Agricultural Wastes. Marcel Dekker Incorporated, New York, NY, USA, 51(11): 751, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-4qrk-161",
            "keyword": [
                "pesticides",
                "food analysis",
                "dietary exposure",
                "community duplicat diet",
                "dietary pesticide intake",
                "regression modeling",
                "sample compositing",
                "pyrethroids"
            ],
            "contactPoint": {
                "fn": "Lisa Melnyk",
                "hasEmail": "mailto:melnyk.lisa@epa.gov"
            },
            "distribution": [
                {
                    "title": "Sets 1-4 composites pesticides & phth rev3.2.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/161/Sets%201-4%20composites%20pesticides%20%26%20phth%20rev3.2.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Bags proportions.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/161/Bags%20proportions.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Food list addins(lcm_msm 08162010).xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/161/Food%20list%20addins%28lcm_msm%2008162010%29.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2010-09-30",
            "references": [
                "https://doi.org/10.1080/03601234.2016.1198640"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Multiscale predictions of aviation-attributable PM 2.5 for US airports modeled using CMAQ with plume-in-grid and an aircraft-specific 1-D emission model ",
            "description": "NA. This dataset is not publicly accessible because: No EPA generated data was used in this work. It can be accessed through the following means: NA. Format: No EPA generated data was used in this work. \n\nThis dataset is associated with the following publication:\nWoody, M., H. Hsi-Wu Wong, J.J. West, and S. Arunachalam. Multiscale predictions of aviation-attributable PM2.5 for U.S. airports modeled using CMAQ with plume-in-grid and an aircraft-specific 1-D emission model.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 147: 384-394, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-fqzk-548",
            "keyword": [
                "CMAQ",
                "Aircraft emissions",
                "Plume-in-grid"
            ],
            "contactPoint": {
                "fn": "Matthew Woody",
                "hasEmail": "mailto:woody.matthew@epa.gov"
            },
            "distribution": [],
            "modified": "2017-02-15",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2016.10.016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Tables and figures from Gavett 2016 paper in Particle and Fibre Toxicology",
            "description": "The files in the dataset are labeled according to table or figure number as listed in the paper (Gavett et al., Particle and Fibre Toxicology, 13:17, 2016). The paper itself and an online additional file are also included. Data files from the additional file are labeled as Extra File with figures and tables labeled Table S1, Figure S1, etc. The files are all self explanatory with clearly labeled headers and notes explaining the data. Derived data can be traced back to original data by following the formula links in excel files. PDF report titles contain page numbers which reference summary tables used in the paper. \n\nThis dataset is associated with the following publication:\nGavett , S., C. Parkinson, G. Willson, C. Wood , A. Jarabek , K. Roberts, U. Kodavanti , and D. Dodd. Persistent Effects of Libby Amphibole and Amosite Asbestos Following Subchronic Inhalation in Rats.   Particle and Fibre Toxicology. BioMed Central Ltd, London,  UK, 13(1): 17, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-bvqj-228",
            "keyword": [
                "asbestos",
                "Libby amphibole",
                "amosite",
                "inflammasome",
                "inflammation",
                "Inhalation exposures"
            ],
            "contactPoint": {
                "fn": "Stephen Gavett",
                "hasEmail": "mailto:gavett.stephen@epa.gov"
            },
            "distribution": [
                {
                    "title": "Gavett 2016 PartFibToxicol persistent effects LA and AM following subchr inhal.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Gavett%202016%20PartFibToxicol%20persistent%20effects%20LA%20and%20AM%20following%20subchr%20inhal.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Gavett 2016 PartFibToxicol Addtional File 1.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Gavett%202016%20PartFibToxicol%20Addtional%20File%201.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Figure 1 two week exp BALF data Gavett 2016 PFT.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Figure%201%20two%20week%20exp%20BALF%20data%20Gavett%202016%20PFT.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figure 2 two week exp mRNA data Gavett 2016 PFT.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Figure%202%20two%20week%20exp%20mRNA%20data%20Gavett%202016%20PFT.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figure 3 two week exp BrdU data Gavett 2016 PFT.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Figure%203%20two%20week%20exp%20BrdU%20data%20Gavett%202016%20PFT.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 4 three month exp lung fiber data Gavett 2016 PFT.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Figure%204%20three%20month%20exp%20lung%20fiber%20data%20Gavett%202016%20PFT.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 5 three month exp BAL data Gavett 2016 PFT.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Figure%205%20three%20month%20exp%20BAL%20data%20Gavett%202016%20PFT.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 6 three month exp cytokine and pathway data Gavett 2016 PFT.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Figure%206%20three%20month%20exp%20cytokine%20and%20pathway%20data%20Gavett%202016%20PFT.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table 1 two week exp (p 87-94) and pathology (p 103) data Gavett 2016 PFT.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Table%201%20two%20week%20exp%20%28p%2087-94%29%20and%20pathology%20%28p%20103%29%20data%20Gavett%202016%20PFT.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Table 2 three month exp inhalation report mass conc and APS data Gavett 2016 PFT.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Table%202%20three%20month%20exp%20inhalation%20report%20mass%20conc%20and%20APS%20data%20Gavett%202016%20PFT.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Table 2 three month exp SEM data Gavett 2016 PFT.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Table%202%20three%20month%20exp%20SEM%20data%20Gavett%202016%20PFT.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table 3 1 day to 3 month pathology (p 12-13) data.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Table%203%201%20day%20to%203%20month%20pathology%20%28p%2012-13%29%20data.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Table 3 18 mo pathol (p 13, 16), Table S2 (early death p 11) and S3 (epid and test p 17-18).pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Table%203%2018%20mo%20pathol%20%28p%2013%2C%2016%29%2C%20Table%20S2%20%28early%20death%20p%2011%29%20and%20S3%20%28epid%20and%20test%20p%2017-18%29.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Extra File Table S1 CBC data Gavett 2016 PFT.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Extra%20File%20Table%20S1%20CBC%20data%20Gavett%202016%20PFT.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Extra File Figure S2 survival curves and cause of death Gavett 2016 PFT.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/228/Extra%20File%20Figure%20S2%20survival%20curves%20and%20cause%20of%20death%20Gavett%202016%20PFT.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-23",
            "references": [
                "https://doi.org/10.1186/s12989-016-0130-z"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Cyphert, J Toxicol Environ Health A, 2016: Long-Term Toxicity of Naturally Occurring Asbestos in Male Fischer 344 Rats",
            "description": "The data shown are raw values used in tables and figures published in Cyphert et al., J Toxicol Environ Health A, 2016. Besides the published paper which is included in the dataset, each file is clearly labeled with the table or figure number and 1 to 3 words indicating the subject of the table or figure. All table and figure files are excel spreadsheets which are clearly labeled with the data in columns. One word file has pathology notes used in the composition of figures 4 and 5. \n\nThis dataset is associated with the following publication:\nCyphert, J., M. McGee, A. Nyska, M. Schladweiler , U. Kodavanti , and S. Gavett. Long-Term Toxicity of Naturally Occurring Asbestos in Male Fischer 344 Rats.   JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH - PART A:  CURRENT ISSUES. Taylor & Francis, Inc., Philadelphia, PA, USA, 79(2): 49-60, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-vhj8-209",
            "keyword": [
                "Libby amphibole",
                "chrysotile",
                "tremolite",
                "ferroactinolite",
                "fibrosis",
                "carcinogenesis"
            ],
            "contactPoint": {
                "fn": "Stephen Gavett",
                "hasEmail": "mailto:gavett.stephen@epa.gov"
            },
            "distribution": [
                {
                    "title": "Gavett_A-vhj8_published paper JTEHA 2016.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/209/Gavett_A-vhj8_published%20paper%20JTEHA%202016.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Table 1 fiber size data Cyphert 2016 JTEHA.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/209/Table%201%20fiber%20size%20data%20Cyphert%202016%20JTEHA.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 1 AB buxco data Cyphert 2016 JTEHA.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/209/Figure%201%20AB%20buxco%20data%20Cyphert%202016%20JTEHA.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 1 CD flexivent data Cyphert 2016 JTEHA.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/209/Figure%201%20CD%20flexivent%20data%20Cyphert%202016%20JTEHA.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table 2 body weight survival data Cyphert 2016 JTEHA.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/209/Table%202%20body%20weight%20survival%20data%20Cyphert%202016%20JTEHA.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table 2 pathology findings Cyphert 2016 JTEHA.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/209/Table%202%20pathology%20findings%20Cyphert%202016%20JTEHA.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 2 BAL cells data Cyphert 2016 JTEHA.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/209/Figure%202%20BAL%20cells%20data%20Cyphert%202016%20JTEHA.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 3 BAL biochemistry data Cyphert 2016 JTEHA.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/209/Figure%203%20BAL%20biochemistry%20data%20Cyphert%202016%20JTEHA.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figures 4 and 5 pathology notes Cyphert 2016 JTEHA.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/209/Figures%204%20and%205%20pathology%20notes%20Cyphert%202016%20JTEHA.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-08-18",
            "references": [
                "https://doi.org/10.1080/15287394.2015.1099123"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CMAPS source apportionment",
            "description": "This dataset includes concentrations of trace inorganic elements, ions, and organic/element carbon of PM collected from two sampling sites (GT Craig and Chippewa Lake) in Cleveland as well as PM source profiles/contributions to each sampling sites. \n\nThis dataset is associated with the following publication:\nKim, Y., T. Krantz, J. Mcgee, K. Kovalcik, R. Duvall, R. Willis, A. Kamal, M. Landis, G. Norris, and I. Gilmour. Chemical Composition and Source Apportionment of Size Fractionated Particulate Matter in Cleveland, Ohio, USA.   ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 218: 1180-1190, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-ht7m-147",
            "keyword": [
                "cleveland",
                "air pollution",
                "source apportionment",
                "urban",
                "rural"
            ],
            "contactPoint": {
                "fn": "Matthew Gilmour",
                "hasEmail": "mailto:gilmour.ian@epa.gov"
            },
            "distribution": [
                {
                    "title": "Description.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/147/Description.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Dictionary.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/147/Dictionary.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Research Data for Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/147/Research%20Data%20for%20Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Research Data for Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/147/Research%20Data%20for%20Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-07-27",
            "references": [
                "https://doi.org/10.1016/j.envpol.2016.08.073"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/147/documents/Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "QSARs for Plasma Protein Binding: Source Data and Predictions",
            "description": "The dataset has all of the information used to create and evaluate 3 independent QSAR models for the fraction of a chemical unbound by plasma protein (Fub) for environmentally relevant chemicals. In vitro plasma protein values for 1245 pharmaceuticals and 406 ToxCast chemicals were collected from the literature (Obach 2008, Zhu 2013, Wetmore 2012, Wetmore 2015). The 21 descriptors calculated by MOE that were used in the models are included, as is an acid/base/neutral/zwitterions classification based on ionization percentages calculated in ADMET Predictor. Finally, the dataset includes the in silico Fub predictions for each chemical from the constructed k-nearest neighbor, support vector machine, and random forest QSAR models, as well as a consensus (average) prediction. \n\nThis dataset is associated with the following publication:\nIngle, B., R. Tornero-Velez, J. Nichols, and B. Veber. Informing the Human Plasma Protein Binding of Environmental Chemicals by Machine Learning in the Pharmaceutical Space: Applicability Domain and Limits of Predictability.   Journal of Chemical Information and Modeling. American Chemical Society, Washington, DC, USA, 56(11): 2243-2252, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-rbpk-569",
            "keyword": [
                "Environmental toxicology",
                "plasma protein binding",
                "machine learning",
                "domain of applicability",
                "quantitative structure activity relationship (QSAR)"
            ],
            "contactPoint": {
                "fn": "Rogelio Tornero-Velez",
                "hasEmail": "mailto:tornero-velez.rogelio@epa.gov"
            },
            "distribution": [
                {
                    "title": "PPB_JChemInfMod_Supp_AllData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/569/PPB_JChemInfMod_Supp_AllData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-26",
            "references": [
                "https://doi.org/10.1021/acs.jcim.6b00291"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/569/documents/DataDictionary_PPB_JCIM.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Multipollutant health effect simulations",
            "description": "Resulting betas (health effects) from a variety of copollutant epidemiologic models used to analyze the impact of exposure measurement error on health effect estimates. \n\nThis dataset is associated with the following publication:\nDionisio , K., H.H. Chang, and L. Baxter. A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models..   ENVIRONMENTAL HEALTH. Academic Press Incorporated, Orlando, FL, USA, 15: 114, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-9kdf-573",
            "keyword": [
                "Exposure modeling",
                "exposure measurement error",
                "Exposure Assessment",
                "bias",
                "copollutant"
            ],
            "contactPoint": {
                "fn": "Kathie Dionisio",
                "hasEmail": "mailto:dionisio.kathie@epa.gov"
            },
            "distribution": [
                {
                    "title": "RunSimBatchv2_2016August15.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/573/RunSimBatchv2_2016August15.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-15",
            "references": [
                "https://doi.org/10.1186/s12940-016-0186-0"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Assessing model characterization of single source secondary pollutant impacts using 2013 SENEX field study measurements",
            "description": "The dataset consists of 4 comma-separated value (csv) text files and 3 netCDF data files. Each csv file contains the observed and CMAQ modeled gas and aerosol concentrations collected during the SENEX field campaign. The netCDF files contain ground layer modeled single source contributions. The headers of each file contain the variable names for each column. An additional data dictionary with variable descriptions and units for the csv files is included with the data along with a file detailing the mapping of files to figures in the manuscript. \n\nThis dataset is associated with the following publication:\nBaker, K., and M. Woody. Assessing Model Characterization of Single Source Secondary Pollutant Impacts Using 2013 SENEX Field Study Measurements.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(7): 3833-3842, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-mw74-549",
            "keyword": [
                "CMAQ",
                "CMAQ ISAM"
            ],
            "contactPoint": {
                "fn": "Matthew Woody",
                "hasEmail": "mailto:woody.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/549/data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-09-19",
            "references": [
                "https://doi.org/10.1021/acs.est.6b05069"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Development of the crop residue and rangeland burning in the 2014 National Emissions Inventory using information from multiple sources",
            "description": "This workbook contains all the activity data, emission factor data, and ancillary data used to compute crop residue  burning and rangeland emissions for the 2014 NEI as described in the journal article (see citation) in addition to the data associated with Figures 1-5. \n\nThis dataset is associated with the following publication:\nPouliot, G., V. Rao, J. McCarty, and A. Soja. Development of the crop residue and rangeland burning in the 2014 National Emissions Inventory using information from multiple sources.   JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION. Air & Waste Management Association, Pittsburgh, PA, USA, 67(5): 613-622, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-4b8m-516",
            "keyword": [
                "2014 NEI",
                "Crop Residue Burning",
                "Rangeland Burning",
                "National Emission Inventory",
                "Cropland data Layer",
                "Hazard Mapping System"
            ],
            "contactPoint": {
                "fn": "George Pouliot",
                "hasEmail": "mailto:pouliot.george@epa.gov"
            },
            "distribution": [
                {
                    "title": "Pouliot_A-4b8m_Dataset_20170307.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/516/Pouliot_A-4b8m_Dataset_20170307.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-08-25",
            "references": [
                "https://doi.org/10.1080/10962247.2016.1268982"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Changes in Landscape Greenness and Climatic Factors over 25 Years (1989\u20132013) in the USA",
            "description": "The asci files are the probability of the NDVI trend (slope) and the direction of the NDVI trend (+/-).  These files can be mapped in ArcMap using ArcToolbox (conversion tools and asci to raster).  The asci files are for maps in Figures 1,2 and 4 in the publication.\n\nFigures.xlsx; Contains 8 Figures, each in a sheet titled same as in the publication. Except for Figure 3, all figures contain information about labeling the axis in publication. \n\nThis dataset is associated with the following publication:\nNash, M., J. Wickham, J. Christensen, and T. Wade. Changes in Landscape Greenness and Climatic Factors over 25 Years (1989\u20132013) in the USA.   Remote Sensing. MDPI AG, Basel,  SWITZERLAND, 9(3): 295, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-prrq-586",
            "keyword": [
                "long-term monitoring",
                "NDVI change",
                "USA",
                "direct factors",
                "climatic factors",
                "autoregression model"
            ],
            "contactPoint": {
                "fn": "Maliha Nash",
                "hasEmail": "mailto:nash.maliha@epa.gov"
            },
            "distribution": [
                {
                    "title": "Nash_2017_data_ScinceHOP.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/586/Nash_2017_data_ScinceHOP.zip",
                    "mediaType": "application/octet-stream"
                }
            ],
            "modified": "2017-03-21",
            "references": [
                "https://doi.org/10.3390/rs9030295"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "An integrated ecological modeling system for assessing impacts of multiple stressors on stream and riverine ecosystem services within river basins",
            "description": "We demonstrate a novel, spatially explicit assessment of the current condition of aquatic ecosystem services, with limited sensitivity analysis for the atmospheric contaminant mercury. The Integrated Ecological Modeling System (IEMS) forecasts water quality and quantity, habitat suitability for aquatic biota, fish biomasses, population densities, productivities, and contamination by methylmercury across headwater watersheds. We applied this IEMS to the Coal River Basin (CRB), West Virginia (USA), an 8-digit hydrologic unit watershed, by simulating a network of 97 stream segments using the SWAT watershed model, a watershed mercury loading model, the WASP water quality model, the PiSCES fish community estimation model, a fish habitat suitability model, the BASS fish community and bioaccumulation model, and an ecoservices post-processer. Model application was facilitated by automated data retrieval and model setup and updated model wrappers and interfaces for data transfers between these models from a prior study. This companion study evaluates baseline predictions of ecoservices provided for 1990\u20132010 for the population of streams in the CRB and serves as a foundation for future model development. \n\nThis dataset is associated with the following publication:\nJohnston , J., C. Barber , K. Wolfe , M. Galvin , M. Cyterski , and R. Parmar. An integrated ecological modeling system for assessing impacts of multiple stressors on stream and riverine ecosystem services within river basins.   ECOLOGICAL MODELLING. Elsevier Science BV, Amsterdam,  NETHERLANDS, 354: 104-114, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-612r-555",
            "keyword": [
                "integrated ecological modeling",
                "multiple stressors",
                "landuse change",
                "aquatic ecosystem services",
                "Spatially explicit exposure",
                "Forecasting",
                "Freshwater provisioning",
                "; multiple stressors"
            ],
            "contactPoint": {
                "fn": "John Johnston",
                "hasEmail": "mailto:johnston.johnm@epa.gov"
            },
            "distribution": [
                {
                    "title": "Ecological Modeling Figures and Tables data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/555/Ecological%20Modeling%20Figures%20and%20Tables%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://www.epa.gov/ceam/3mra",
                    "accessURL": "https://www.epa.gov/ceam/3mra"
                }
            ],
            "modified": "2017-04-11",
            "references": [
                "https://doi.org/10.1016/j.ecolmodel.2017.03.021"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/555/documents/ESP_Output.txt",
            "describedByType": "text/plain",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "On the implications of aerosol liquid water and phase separation for organic aerosol mass",
            "description": "This dataset contains data presented in the figures of the paper \"On the implications of aerosol liquid water and phase separation for organic aerosol mass\" published in Atmospheric Chemistry and Physics. It also links to the data archive of field observations. \n\nThis dataset is associated with the following publication:\nPye, H., B. Murphy, L. Xu, N. Ng, A. Carlton, H. Guo, R. Weber, P. Vasilakos, W. Appel, S. Budisulistiorini, J. Surratt, A. Nenes, W. Hu, J. Jimenez, G. saacman-VanWertz, P. Misztal, and A. Goldstein. On the implications of aerosol liquid water and phase separation for organic aerosol mass.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 17: 343-369, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-gf28-504",
            "keyword": [
                "air quality",
                "Secondary Organic Aerosol",
                "SOA",
                "SOAS",
                "Aerosol",
                "CMAQ",
                "WRF-CMAQ",
                "Southeastern USA",
                "organic aerosol"
            ],
            "contactPoint": {
                "fn": "Havala Pye",
                "hasEmail": "mailto:pye.havala@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.atmos-chem-phys.net/17/343/2017/acp-17-343-2017-assets.html",
                    "accessURL": "https://www.atmos-chem-phys.net/17/343/2017/acp-17-343-2017-assets.html"
                }
            ],
            "modified": "2017-01-06",
            "references": [
                "https://doi.org/10.5194/acp-17-343-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Measured exposure metrics",
            "description": "measured air pollution exposure metrics. \n\nThis dataset is associated with the following publication:\nBreen , M., T. Long , B. Schultz, R. Williams , J. Richmond-Bryant , M. Breen, J. Langstaff , R. Devlin , A. Schneider, J. Burke , S.A. Batterman, and Q.Y. Meng. Air Pollution Exposure Model for Individuals (EMI) in Health Studies: Evaluation for Ambient PM2.5 in Central North Carolina.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 49(24): 14184-14194, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-4f4v-187",
            "keyword": [
                "air pollution",
                "exposure",
                "human health"
            ],
            "contactPoint": {
                "fn": "Michael Breen",
                "hasEmail": "mailto:breen.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "rtp_tads.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/187/rtp_tads.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "rtp_pm_data.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/187/rtp_pm_data.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2015-06-05",
            "references": [
                "https://doi.org/10.1021/acs.est.5b02765"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/187/documents/rtp_pm_data_dictionary.doc",
            "describedByType": "application/msword",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "GMAP Phoenix 2013 data",
            "description": "mobile monitoring data from the 2013 Phoenix study. \n\nThis dataset is associated with the following publication:\nVenkatram, A., V. Isakov , P. Deshmukh, and R. Baldauf. Modeling the impact of solid noise barriers on near road air quality.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 141: 462-469, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-nck9-431",
            "keyword": [
                "dispersion modeling",
                "air quality",
                "near road",
                "noise barriers",
                "traffic"
            ],
            "contactPoint": {
                "fn": "Vladilen Isakov",
                "hasEmail": "mailto:isakov.vlad@epa.gov"
            },
            "distribution": [
                {
                    "title": "Phoenix2013data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/431/Phoenix2013data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2014-12-22",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2016.07.005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Chemical Transport Model Simulations of Organic Aerosol in Southern California: Model Evaluation and Gasoline and Diesel Source Contributions",
            "description": "Gasoline- and diesel-fueled engines are ubiquitous sources of air pollution in urban environments. They emit both primary particulate matter and precursor gases that react to form secondary particulate matter in the atmosphere. In this work, we use experimentally derived inputs and parameterizations to predict concentrations and properties of organic aerosol (OA) from mobile sources in southern California using a three-dimensional chemical transport model, the Community Multiscale Air Quality Model (CMAQ). The updated model includes secondary organic aerosol (SOA) formation from unspeciated intermediate volatility organic compounds (IVOC). Compared to the treatment of OA in the traditional version of CMAQ, which is commonly used for regulatory applications, the updated model did not significantly alter the predicted OA mass concentrations but it did substantially improve predictions of OA sources and composition (e.g., POA-SOA split), and ambient IVOC concentrations. The updated model, despite substantial differences in emissions and chemistry, performs similar to a recently released research version of CMAQ. Mobile sources are predicted to contribute about 30\u201340 % of the OA in southern California (half of which is SOA), making mobile sources the single largest source contributor to OA in southern California. The remainder of the OA is attributed to non-mobile anthropogenic sources (e.g., cooking, biomass burning) with biogenic sources contributing less than 5 % to the total OA. Gasoline sources are predicted to contribute about thirteen times more OA than diesel sources; this difference is driven by differences in SOA production. Model predictions highlight the need to better constrain multi-generational oxidation reactions in chemical transport models. \n\nThis dataset is associated with the following publication:\nJathar, S., M. Woody, H. Pye, K. Baker, and A. Robinson. Chemical transport model simulations of organic aerosol in southern California: model evaluation and gasoline and diesel source contributions.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 17: 4305-4318, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-tmq4-532",
            "keyword": [
                "Secondary Organic Aerosol",
                "CalNex",
                "Jathar",
                "California",
                "gasoline",
                "diesel",
                "vehicles",
                "SOA",
                "Aerosol"
            ],
            "contactPoint": {
                "fn": "Havala Pye",
                "hasEmail": "mailto:pye.havala@epa.gov"
            },
            "distribution": [
                {
                    "title": "calnex_ivoc.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/532/calnex_ivoc.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-01-01",
            "references": [
                "https://doi.org/10.5194/acp-17-4305-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CMAQv5.1 Base NEIv1 AQS hourly site compare files",
            "description": "CMAQv5.1 Base NEIv1 AQS hourly sitex files containing hourly paired model/ob data for the AQS network. \n\nThis dataset is associated with the following publication:\nAppel, W., S. Napelenok, K. Foley, H. Pye, C. Hogrefe, D. Luecken, J. Bash, S. Roselle, J. Pleim, H. Foroutan, B. Hutzell, G. Pouliot, G. Sarwar, K. Fahey, B. Gantt, D. Kang, R. Mathur, D. Schwede, T. Spero, D. Wong, J. Young, and N. Heath. Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1.   Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 10: 1703-1732, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1500016",
            "keyword": [
                "CMAQ",
                "WRF",
                "model evaluation",
                "Air Quality Model"
            ],
            "contactPoint": {
                "fn": "Keith Appel",
                "hasEmail": "mailto:appel.wyat@epa.gov"
            },
            "distribution": [
                {
                    "title": "CMAQv51_Base_NEIv1_AQS_Hourly_sitex.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500016/CMAQv51_Base_NEIv1_AQS_Hourly_sitex.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-05-03",
            "references": [
                "https://doi.org/10.5194/gmd-10-1703-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1500016/documents/WyatAppel_A-9zwc_Data_Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "ACONC Files",
            "description": "ACONC files containing simulated ozone and PM2.5 fields that were used to create the model difference plots shown in the journal article. \n\nThis dataset is associated with the following publication:\nAppel, W., S. Napelenok, K. Foley, H. Pye, C. Hogrefe, D. Luecken, J. Bash, S. Roselle, J. Pleim, H. Foroutan, B. Hutzell, G. Pouliot, G. Sarwar, K. Fahey, B. Gantt, D. Kang, R. Mathur, D. Schwede, T. Spero, D. Wong, J. Young, and N. Heath. Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1.   Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 10: 1703-1732, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1500013",
            "keyword": [
                "CMAQ",
                "WRF",
                "model evaluation",
                "Air Quality Model"
            ],
            "contactPoint": {
                "fn": "Keith Appel",
                "hasEmail": "mailto:appel.wyat@epa.gov"
            },
            "distribution": [
                {
                    "title": "CMAQv502_Base_aconc.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500013/CMAQv502_Base_aconc.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "CMAQv51_Base_NEIv1_aconc.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500013/CMAQv51_Base_NEIv1_aconc.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "CMAQv51_Base_NEIv2_aconc.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500013/CMAQv51_Base_NEIv2_aconc.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-05-03",
            "references": [
                "https://doi.org/10.5194/gmd-10-1703-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1500013/documents/WyatAppel_A-9zwc_Data_Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Site compare scripts and output",
            "description": "Monthly site compare scripts and output used to generate the model/ob plots and statistics in the manuscript. The AQS hourly site compare output files are not included as they were too large to store on ScienceHub. The files contain paired model/ob values for the various air quality networks. \n\nThis dataset is associated with the following publication:\nAppel, W., S. Napelenok, K. Foley, H. Pye, C. Hogrefe, D. Luecken, J. Bash, S. Roselle, J. Pleim, H. Foroutan, B. Hutzell, G. Pouliot, G. Sarwar, K. Fahey, B. Gantt, D. Kang, R. Mathur, D. Schwede, T. Spero, D. Wong, J. Young, and N. Heath. Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1.   Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 10: 1703-1732, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1500018",
            "keyword": [
                "CMAQ",
                "WRF",
                "model evaluation",
                "Air Quality Model"
            ],
            "contactPoint": {
                "fn": "Keith Appel",
                "hasEmail": "mailto:appel.wyat@epa.gov"
            },
            "distribution": [
                {
                    "title": "CMAQ_v502_Base_sitex.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500018/CMAQ_v502_Base_sitex.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "CMAQv5.1_Base_NEIv1_sitex.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500018/CMAQv5.1_Base_NEIv1_sitex.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "CMAQv5.1_Base_NEIv2_sitex.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500018/CMAQv5.1_Base_NEIv2_sitex.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-05-03",
            "references": [
                "https://doi.org/10.5194/gmd-10-1703-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1500018/documents/WyatAppel_A-9zwc_Data_Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CMAQv502 Base AQS Hourly site compare output",
            "description": "Monthly AQS hourly site compare output files for the CMAQv502 Base simulation. Monthly files contain hourly paired model/ob data for the AQS network. These data were used in some of model/ob plot provided in the manuscript. \n\nThis dataset is associated with the following publication:\nAppel, W., S. Napelenok, K. Foley, H. Pye, C. Hogrefe, D. Luecken, J. Bash, S. Roselle, J. Pleim, H. Foroutan, B. Hutzell, G. Pouliot, G. Sarwar, K. Fahey, B. Gantt, D. Kang, R. Mathur, D. Schwede, T. Spero, D. Wong, J. Young, and N. Heath. Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1.   Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 10: 1703-1732, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1500015",
            "keyword": [
                "CMAQ",
                "WRF",
                "model evaluation",
                "Air Quality Model"
            ],
            "contactPoint": {
                "fn": "Keith Appel",
                "hasEmail": "mailto:appel.wyat@epa.gov"
            },
            "distribution": [
                {
                    "title": "CMAQv5.0.2_Base_AQS_Hourly_sitex.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500015/CMAQv5.0.2_Base_AQS_Hourly_sitex.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-05-03",
            "references": [
                "https://doi.org/10.5194/gmd-10-1703-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1500015/documents/WyatAppel_A-9zwc_Data_Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CMAQv5.1 Base NEIv2 AQS Hourly site compare output",
            "description": "CMAQv5.1 Base NEIv2 AQS Hourly site compare output containing paired model/ob values that were used for some of the plots in the manuscript. \n\nThis dataset is associated with the following publication:\nAppel, W., S. Napelenok, K. Foley, H. Pye, C. Hogrefe, D. Luecken, J. Bash, S. Roselle, J. Pleim, H. Foroutan, B. Hutzell, G. Pouliot, G. Sarwar, K. Fahey, B. Gantt, D. Kang, R. Mathur, D. Schwede, T. Spero, D. Wong, J. Young, and N. Heath. Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1.   Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 10: 1703-1732, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1500014",
            "keyword": [
                "CMAQ",
                "WRF",
                "model evaluation",
                "Air Quality Model"
            ],
            "contactPoint": {
                "fn": "Keith Appel",
                "hasEmail": "mailto:appel.wyat@epa.gov"
            },
            "distribution": [
                {
                    "title": "CMAQv5.1_Base_NEIv2_AQS_Hourly_sitex.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500014/CMAQv5.1_Base_NEIv2_AQS_Hourly_sitex.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-05-03",
            "references": [
                "https://doi.org/10.5194/gmd-10-1703-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1500014/documents/WyatAppel_A-9zwc_Data_Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CMAQv5.1 TUCL and RetroPhot ACONC files",
            "description": "January and July monthly average ACONC files for the CMAQv5.1 TUCL and RetroPhot sensitivity runs that were performed and presented in the manuscript. \n\nThis dataset is associated with the following publication:\nAppel, W., S. Napelenok, K. Foley, H. Pye, C. Hogrefe, D. Luecken, J. Bash, S. Roselle, J. Pleim, H. Foroutan, B. Hutzell, G. Pouliot, G. Sarwar, K. Fahey, B. Gantt, D. Kang, R. Mathur, D. Schwede, T. Spero, D. Wong, J. Young, and N. Heath. Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1.   Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 10: 1703-1732, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1500017",
            "keyword": [
                "CMAQ",
                "WRF",
                "model evaluation",
                "Air Quality Model"
            ],
            "contactPoint": {
                "fn": "Keith Appel",
                "hasEmail": "mailto:appel.wyat@epa.gov"
            },
            "distribution": [
                {
                    "title": "CMAQv51_TUCL_RetroPhot_ACONC.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500017/CMAQv51_TUCL_RetroPhot_ACONC.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-05-04",
            "references": [
                "https://doi.org/10.5194/gmd-10-1703-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1500017/documents/WyatAppel_A-9zwc_Data_Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Complex conductivity results to silver nanoparticles in partically saturated laboratory columns",
            "description": "Laboratory complex conductivity data from partially saturated sand columns with silver nanoparticles. This dataset is not publicly accessible because: It involves two universities and the EPA.  The EPA collaborated in the research; but did not provide funding.  The data are the property of the universities. It can be accessed through the following means: The authors can be contacted individually for the data. Format: The data will be in xlsx format. \n\nThis dataset is associated with the following publication:\nAbdel Aal, G., E. Atekwana, and D. Werkema. Complex conductivity response to silver nanoparticles in partially saturated sand columns.   JOURNAL OF APPLIED GEOPHYSICS. Elsevier Science Ltd, New York, NY, USA, 137: 73-81, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-m0cz-580",
            "keyword": [
                "nanosilver",
                "complex conductivity",
                "Nanoparticles"
            ],
            "contactPoint": {
                "fn": "Douglas Werkema",
                "hasEmail": "mailto:werkema.d@epa.gov"
            },
            "distribution": [],
            "modified": "2016-11-14",
            "references": [
                "https://doi.org/10.1016/j.jappgeo.2016.12.013"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/580/documents/Abdel%20Aal%20et%20al%20nano%20vadose%20zone%20data%20dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Chemical Alterations of Pb using Flue Gas Desulfurization Gypsum (FGDG) in two contaminated soils",
            "description": "The data include chemical composition of Pb contaminated soils by adding FGDG as an amendment.  The data shows the changes in Pb speciation to sulfur based minerals. \n\nThis dataset is associated with the following publication:\nKoralegedara, N., S. Al-Abed, S. Rodrigo, R. Karna, K. Scheckel, and D. Dionysiou. Alterations of lead speciation by sulfate from addition of flue gas desulfurization gypsum (FGDG) in two contaminated soils.  D. Barcelo  SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 575: 1522-1529, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-t775-590",
            "keyword": [
                "Flue Gas Desulfurization Gypsum",
                "leaching test",
                "ferrihydrite bound Pb",
                "anglesite",
                "humic acid bound Pb",
                "leadhillite"
            ],
            "contactPoint": {
                "fn": "Souhail Al-Abed",
                "hasEmail": "mailto:al-abed.souhail@epa.gov"
            },
            "distribution": [
                {
                    "title": "Pb manuscript Metadata data tables with data dictionary 2016 - Copy.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/590/Pb%20manuscript%20Metadata%20data%20tables%20with%20data%20dictionary%202016%20-%20Copy.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-10-06",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.10.027"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/590/documents/data%20dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Experimental and fate and transport model simulation results of Se and B released from FGDG, soil and soil-FGDG mixture. ",
            "description": "The leachate concentrations of Se and B released from FGDG, soil and soil-FGDG mixture obtained from EPA-method 1314 is included in the data set. The non-equilibrium partitioning coefficients calculated based on the experimental data also included along with the predicted NPC values calculated using a regression model based on a power function. Long term environmental release of Se and B in agricultural field and a landfill calculated using fate and transport model simulation also included in the data set. \n\nThis dataset is associated with the following publication:\nKoralegedara, N., S. Al-Abed , M. Arambewela, and D. Dionysiou. Impact of Leaching Conditions on Constituents Release from Flue Gas Desulfurization Gypsum (FGDG) and FGDG-Soil Mixture.  Edith Rene, Robin Gerlach, Peter Galaz, Davide Zannoni and Piet Lens  JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 324: 83-93, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-g1kb-636",
            "keyword": [
                "Flue Gas Desulfurization Gypsum",
                "FGDG-soil mixture",
                "element leaching",
                "EPA-leaching methods",
                "Selenium",
                "Boron"
            ],
            "contactPoint": {
                "fn": "Souhail Al-Abed",
                "hasEmail": "mailto:al-abed.souhail@epa.gov"
            },
            "distribution": [
                {
                    "title": "FGDG manuscript Metadata data tables with data dictionary 2016 - Copy.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/636/FGDG%20manuscript%20Metadata%20data%20tables%20with%20data%20dictionary%202016%20-%20Copy.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-11-02",
            "references": [
                "https://doi.org/10.1016/j.jhazmat.2016.01.019"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/636/documents/Data%20dictionary-1.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset for Probabilistic estimation of residential air exchange rates for population-based exposure modeling",
            "description": "This dataset provides the city-specific air exchange rate measurements, modeled, literature-based as well as housing characteristics. \n\nThis dataset is associated with the following publication:\nBaxter, L., C. Stallings, L. Smith, and J. Burke. Probabilistic estimation of residential air exchange rates for population-based human exposure modeling.   Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London,  UK, 27: 227-234, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-n5tv-613",
            "keyword": [
                "air exchange rates",
                "air pollution",
                "exposure error",
                "Exposure modeling",
                "infiltration",
                "model evaluation"
            ],
            "contactPoint": {
                "fn": "Janet Burke-Norris",
                "hasEmail": "mailto:burke.janet@epa.gov"
            },
            "distribution": [
                {
                    "title": "Burke A-n5tv dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/613/Burke%20A-n5tv%20dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-11-25",
            "references": [
                "https://doi.org/10.1038/jes.2016.49"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Temperature profiles of three types CNTs (SWCNT, MWCNT and MWCNT-COOH) loaded environmental matrices generated from a microwave induced heating quantification method",
            "description": "Relationships of temperature and CNT mass (SWCNT, MWCNT, MWCNT-COOH) were developed for three environmental matrices (sand, soil and sludge) spiked with known amounts of different types of CNTs that were then irradiated in a microwave at low energies (70-149 W) for a short time (15-30 sec). Temperature rises data were recorded for CNT loaded environmental samples with excess of inorganic/organic carbon and other carbonaceous nanomaterials (C60, GAC and GO). \n\nThis dataset is associated with the following publication:\nHe, Y., S. Al-Abed, and D. Dionysiou. Quantification of Carbon Nanotubes in Different Environmental Matrices by a Microwave Induced Heating Method.  D. Barcelo, and Jay Gan  SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 580: 509-517, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-zpd1-639",
            "keyword": [
                "carbon nanotubes",
                "Quantitative analysis",
                "Microwave method",
                "Quartz sand",
                "soil",
                "Anaerobic sludge"
            ],
            "contactPoint": {
                "fn": "Souhail Al-Abed",
                "hasEmail": "mailto:al-abed.souhail@epa.gov"
            },
            "distribution": [
                {
                    "title": "Microwave_CNTs manuscript Metadata  data tables with data dictionary 2016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/639/Microwave_CNTs%20manuscript%20Metadata%20%20data%20tables%20with%20data%20dictionary%202016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-10-03",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.11.205"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/639/documents/Data%20Dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "RW1",
            "description": "Wind tunnel measurements of flow and dispersion from a simulated roadway with near-road solid barriers. \n\nThis dataset is associated with the following publication:\nAhangar, F., D. Heist, S. Perry, and A. Venkatram. Reduction of air pollution levels downwind of a road with an upwind noise barrier.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 155: 1-10, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-dv4c-515",
            "keyword": [
                "dispersion modeling",
                "near road",
                "noise barriers",
                "wind tunnel"
            ],
            "contactPoint": {
                "fn": "David Heist",
                "hasEmail": "mailto:heist.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "Heist A-dv4c-DataFiles_RW1-20170307.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/515/Heist%20A-dv4c-DataFiles_RW1-20170307.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-03-07",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2017.02.001"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/515/documents/Heist%20A-dv4c-DataDictionaryRW1-20170307.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The Acute Toxicity of Major Ion Salts to Ceriodaphnia dubia: I. Influence of background water chemistry.",
            "description": "This dataset provides concentration-response data and associated general chemistry conditions for 26 experiments consisting of 149 tests regarding the acute toxicity of major ions to Ceriodaphnia dubia in a variety of test waters; it also provides LC50 estimates and the estimated ion mixtures at the LC50 for each toxicity test. \n\nThis dataset is associated with the following publication:\nMount , D., R. Erickson , T. Highland , R. Hockett , D. Hoff , T. Norberg-King , K. Peterson, Z.  Polaske, and S. Wisniewski. The acute toxicity of major ion salts to Ceriodaphnia dubia: I. Influence of background water chemistry.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 35(12): 3039-3057, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-0gb6-45",
            "keyword": [
                "Ceriodaphnia dubia",
                "Acute Toxicity",
                "Test Water Chemistry Effects",
                "Major Ion Toxicity",
                "Freshwater"
            ],
            "contactPoint": {
                "fn": "Russell Erickson",
                "hasEmail": "mailto:erickson.russell@epa.gov"
            },
            "distribution": [
                {
                    "title": "MEDIonToxPaper1_Dataset.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/45/MEDIonToxPaper1_Dataset.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-05-05",
            "references": [
                "https://doi.org/10.1002/etc.3487"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/45/documents/MEDIonToxPaper1_DataDictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Box photosynthesis modeling results for WRF/CMAQ LSM",
            "description": "Box Photosynthesis model simulations for latent heat and ozone at 6 different FLUXNET sites. \n\nThis dataset is associated with the following publication:\nRan, L., J. Pleim, C. Song, L. Band, J. Walker, and F. Binkowski. A photosynthesis-based two-leaf canopy stomatal conductance model for meteorology and air quality modeling with WRF/CMAQ PX LSM.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 122(3): 1930-1952, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-w9h7-567",
            "keyword": [
                "photosynthesis",
                "PX LSM",
                "WRF/CMAQ",
                "ozone deposition",
                "air quality modeling"
            ],
            "contactPoint": {
                "fn": "Limei Ran",
                "hasEmail": "mailto:ran.limei@epa.gov"
            },
            "distribution": [
                {
                    "title": "EPA_science_hub_data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/567/EPA_science_hub_data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-04-27",
            "references": [
                "https://doi.org/10.1002/2016jd025583"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for manuscript titled \"Historical trends in PM2.5 related premature mortality during 1990-2010 across the northern hemisphere\"",
            "description": "This manuscript has 6 figures:\r\nFigure 1 shows the modeling domain and includes a map with the different analysis sub-regions. Shapefiles to be used with ArcGIS for re-creating this figure is included. \r\n\r\nThe file named \u201cEHP_data_summary\u201d is and Excel file and includes the data used in creation of Figures 2-6.  \r\n\r\nNote that these data files are a result of extensive data processing of many terra-bytes of model output from the hemispheric WRF-CMAQ model.  The manuscript includes details on how this analysis was conducted, and other data-sets incorporated. \n\nThis dataset is associated with the following publication:\nWang, J., J. Xing , R. Mathur , J. Pleim , S. Wang, C. Hogrefe , M. Gan , D. Wong , and J. Hao. Historical Trends in PM2.5-Related Premature Mortality during 1990-2010 across the Northern Hemisphere.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 125(3): 400\u2013408, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-t774-221",
            "keyword": [
                "Hemispheric CMAQ",
                "PM2.5 long-term exposure",
                "emission mitigation efficiency",
                "Air quality trends",
                "air pollution exposure"
            ],
            "contactPoint": {
                "fn": "Rohit Mathur",
                "hasEmail": "mailto:mathur.rohit@epa.gov"
            },
            "distribution": [
                {
                    "title": "EHP_data_Readme.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/221/EHP_data_Readme.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "EHP_data_summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/221/EHP_data_summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "EHP_figure1_shapefile_for_ArcGIS.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/221/EHP_figure1_shapefile_for_ArcGIS.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2015-10-01",
            "references": [
                "https://doi.org/10.1289/ehp298"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Arsenic Paper",
            "description": "Contains data related to Arsenate and Arsenite injections into chlorinated distribution system simulator. Contains data related to model to predict arsenate and arsenite aqueous and wall concentrations within a chlorinated water distribution system. \n\nThis dataset is associated with the following publication:\nBurkhardt, J., J. Szabo, S. Klosterman, J. Hall, and R. Murray. Modeling Fate and Transport of Arsenic in a Chlorinated Distribution System.   ENVIRONMENTAL MODELLING AND SOFTWARE. Elsevier Science Ltd, New York, NY, USA, 93(1): 322-331, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "A-n2zm-432",
            "keyword": [
                "drinking water",
                "water quality",
                "modeling",
                "homeland security",
                "water security",
                "water distribution",
                "adsorption"
            ],
            "contactPoint": {
                "fn": "Jonathan Burkhardt",
                "hasEmail": "mailto:burkhardt.jonathan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Burkhardt-Murray_SciHubData_ArsenicModelingPaper_2016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/432/Burkhardt-Murray_SciHubData_ArsenicModelingPaper_2016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-10-07",
            "references": [
                "https://doi.org/10.1016/j.envsoft.2017.03.016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Chemical Function Predictions for Tox21 Chemicals",
            "description": "Random forest chemical function predictions for Tox21 chemicals in personal care products uses and \"other\" uses. \n\nThis dataset is associated with the following publication:\nIsaacs , K., M. Goldsmith, P. Egeghy , K. Phillips, R. Brooks, T. Hong, and J. Wambaugh. Characterization and prediction of chemical functions and weight fractions in consumer products.   Toxicology Reports. Elsevier B.V., Amsterdam,  NETHERLANDS, 3: 723-732, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-mpgn-485",
            "keyword": [
                "chemical function",
                "Exposure modeling",
                "chemical prioritization",
                "consumer products",
                "cosmetics",
                "ExpoCast",
                "machine learning"
            ],
            "contactPoint": {
                "fn": "Kristin Isaacs",
                "hasEmail": "mailto:isaacs.kristin@epa.gov"
            },
            "distribution": [
                {
                    "title": "ALLPCPPREDS_080516.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/485/ALLPCPPREDS_080516.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "ALLOTHERPREDS_080516.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/485/ALLOTHERPREDS_080516.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-08-05",
            "references": [
                "https://doi.org/10.1016/j.toxrep.2016.08.011"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/485/documents/read_me_metadata_Tox21preds.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Chemical product and function dataset",
            "description": "Merged product weight fraction and chemical function data. \n\nThis dataset is associated with the following publication:\nIsaacs , K., M. Goldsmith, P. Egeghy , K. Phillips, R. Brooks, T. Hong, and J. Wambaugh. Characterization and prediction of chemical functions and weight fractions in consumer products.   Toxicology Reports. Elsevier B.V., Amsterdam,  NETHERLANDS, 3: 723-732, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-mpgn-483",
            "keyword": [
                "chemical function",
                "Exposure modeling",
                "chemical prioritization",
                "consumer products",
                "cosmetics",
                "ExpoCast",
                "machine learning"
            ],
            "contactPoint": {
                "fn": "Kristin Isaacs",
                "hasEmail": "mailto:isaacs.kristin@epa.gov"
            },
            "distribution": [
                {
                    "title": "MSDS_function_data.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/483/MSDS_function_data.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-08-05",
            "references": [
                "https://doi.org/10.1016/j.toxrep.2016.08.011"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/483/documents/read_me_metadata_MSDSFunction.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Chemicals and harmonized functions",
            "description": "Chemicals and harmonized functions -  dataset of chemicals mapped to a harmonized chemical function category. \n\nThis dataset is associated with the following publication:\nIsaacs , K., M. Goldsmith, P. Egeghy , K. Phillips, R. Brooks, T. Hong, and J. Wambaugh. Characterization and prediction of chemical functions and weight fractions in consumer products.   Toxicology Reports. Elsevier B.V., Amsterdam,  NETHERLANDS, 3: 723-732, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-mpgn-484",
            "keyword": [
                "chemical function",
                "Exposure modeling",
                "chemical prioritization",
                "consumer products",
                "cosmetics",
                "ExpoCast",
                "machine learning"
            ],
            "contactPoint": {
                "fn": "Kristin Isaacs",
                "hasEmail": "mailto:isaacs.kristin@epa.gov"
            },
            "distribution": [
                {
                    "title": "function_data.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/484/function_data.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-08-08",
            "references": [
                "https://doi.org/10.1016/j.toxrep.2016.08.011"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/484/documents/read_me_metadata_Function.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Importance of predictor variables for models of chemical function",
            "description": "Importance of random forest predictors for all classification models of chemical function. \n\nThis dataset is associated with the following publication:\nIsaacs , K., M. Goldsmith, P. Egeghy , K. Phillips, R. Brooks, T. Hong, and J. Wambaugh. Characterization and prediction of chemical functions and weight fractions in consumer products.   Toxicology Reports. Elsevier B.V., Amsterdam,  NETHERLANDS, 3: 723-732, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-mpgn-486",
            "keyword": [
                "chemical function",
                "Exposure modeling",
                "chemical prioritization",
                "consumer products",
                "cosmetics",
                "ExpoCast",
                "machine learning"
            ],
            "contactPoint": {
                "fn": "Kristin Isaacs",
                "hasEmail": "mailto:isaacs.kristin@epa.gov"
            },
            "distribution": [
                {
                    "title": "ranksfunctionimp.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/486/ranksfunctionimp.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-08-05",
            "references": [
                "https://doi.org/10.1016/j.toxrep.2016.08.011"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/486/documents/read_me_metadata.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Examining the impacts of increased corn production on groundwater quality using a coupled modeling system",
            "description": "This dataset was used to create graphics associated with manuscript:  Garcia et al., Examining the impacts of increased corn production on groundwater quality using a coupled modeling system, 2017, Science of the Total Environment. \n\nThis dataset is associated with the following publication:\nGarcia, V., E. Cooter, J. Crooks, B. Hinckley, M. Murphy, and X. Xing. Examining the impacts of increased corn production on groundwater quality using a coupled modeling system.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 586: 16-24, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-hdrn-492",
            "keyword": [
                "irrigated corn",
                "nitrogen",
                "groundwater",
                "EPIC",
                "nitrate in groundwater"
            ],
            "contactPoint": {
                "fn": "Valerie Cover",
                "hasEmail": "mailto:garcia.val@epa.gov"
            },
            "distribution": [
                {
                    "title": "FertilizerComparisonScenario2_SciHub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/492/FertilizerComparisonScenario2_SciHub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-02-07",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2017.02.009"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/492/documents/FertilizerScenarioComparison2_data_dic.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figs1,2,3a",
            "description": "all data is in the netCDF format and zipped. after downloading this data, you need to unzip it first to create original netCDF formatted data. \n\nThis dataset is associated with the following publication:\nHe, J., T. Glotfelty, K. Yahya, K. Alapaty, and S. Yu. Does temperature nudging overwhelm aerosol radiative effects in regional integrated climate models?.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 154: 42-52, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-2z37-499",
            "keyword": [
                "aerosol radiative forcing",
                "nudging",
                "aerosol effects",
                "climate"
            ],
            "contactPoint": {
                "fn": "Kirankumar Alapaty",
                "hasEmail": "mailto:alapaty.kiran@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/EPADataCommons/ORD/NudgingPRE_AtmosEnvPaperData/",
                    "accessURL": "https://gaftp.epa.gov/EPADataCommons/ORD/NudgingPRE_AtmosEnvPaperData/"
                }
            ],
            "modified": "2017-01-19",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2017.01.040"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Wind tunnel evaluation of Hi-Vol TSP effectiveness data",
            "description": "Wind tunnel evaluation of EPA's Hi-Vol TSP sampler for sampling effectiveness with regards to aerodynamic particle diameter (5 to 35 microns), wind speed (2, 8, 24 km/hr), orientation (0, 45, and 90 degrees relative to wind vector), and operational state (ON or OFF). A Coulter Counter analysis of the three Arizona Test Dust mixtures is presented. \n\nThis dataset is associated with the following publication:\nKrug, J., A. Dart, C. Witherspoon, J. Gilberry, Q. Malloy, S. Kaushik, and R. Vanderpool. Review of the of EPA's High-Volume Total Size Selective Performance  (Hi-Vol TSP) Sampler.   AEROSOL SCIENCE AND TECHNOLOGY. Taylor & Francis, Inc., Philadelphia, PA, USA, 0(0): 1-20, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-fxq2-572",
            "keyword": [
                "Hi-Vol TSP",
                "wind tunnel",
                "Size selective performance",
                "total suspended particulate"
            ],
            "contactPoint": {
                "fn": "Jonathan Krug",
                "hasEmail": "mailto:krug.jonathan@epa.gov"
            },
            "distribution": [
                {
                    "title": "HiVolData_ScienceHub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/572/HiVolData_ScienceHub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-26",
            "references": [
                "https://doi.org/10.1080/02786826.2017.1316358"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Development and Multi-laboratory Verification of U.S. EPA Method 543 for the Analysis of Drinking Water Contaminants by On-Line Solid Phase Extraction-LC/MS/MS",
            "description": "A drinking water method for seven pesticides and pesticide degradates was developed that addresses the occurrence monitoring needs of the U.S. Environmental Protection Agency (EPA) for a future Unregulated Contaminant Monitoring Regulation (UCMR).  The method employs on-line solid phase extraction-liquid chromatography/tandem mass spectrometry (SPE-LC/MS/MS).  On-line SPE-LC/MS/MS has the potential to offer cost-effective, faster, more sensitive, and more rugged methods than the traditional off-line SPE approach due to complete automation of the SPE process, as well as seamless integration with the LC/MS/MS system.  Multi-laboratory data are presented that demonstrate method ruggedness and transferability.  The final method meets all of the EPA\u2019s UCMR survey requirements for sample collection and storage, precision, accuracy, and sensitivity. \n\nThis dataset is associated with the following publication:\nShoemaker , J. Development and Multi-laboratory Verification of US EPA Method 543 for the Analysis of Drinking Water Contaminants by Online Solid Phase Extraction-LC\u2013MS-MS.   Journal of Chromatographic Science. Preston Publications Incorporated, Niles, IL, USA, 54(9): 1532-1539, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-f1vw-611",
            "keyword": [
                "pesticides",
                "drinking water",
                "on-line SPE",
                "LC/MS/MS",
                "Method 543",
                "contaminant candidate list"
            ],
            "contactPoint": {
                "fn": "Jody Shoemaker",
                "hasEmail": "mailto:shoemaker.jody@epa.gov"
            },
            "distribution": [
                {
                    "title": "ShoemakerJody_Method543_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/611/ShoemakerJody_Method543_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-05-11",
            "references": [
                "https://doi.org/10.1093/chromsci/bmw098"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/611/documents/Definitions_Method%20543%20data.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Predicted phototoxicities of carbon nano-material by quantum mechanical calculations",
            "description": "The data involves a prediction of phototoxicities of nano-materials.  The prediction is based on the calculated triplet excited states of fullerenols and single-walled carbon nanotubes.  The model used is one previously published using actual phototoxicities of polynuclear aromatic hydrocarbons and their calculated triplet excited states. \n\nThis dataset is associated with the following publication:\nBetowski, D. Predicted phototoxicities of carbon nano-material by quantum mechanical calculations.   Journal of Molecular Graphics and Modelling. Elsevier B.V., Amsterdam,  NETHERLANDS, 75: 102-105, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-m90n-180",
            "keyword": [
                "phototoxicity",
                "fullerenols",
                "single-walled carbon nanotubes",
                "ab initio calculations."
            ],
            "contactPoint": {
                "fn": "Leon Betowski",
                "hasEmail": "mailto:betowski.don@epa.gov"
            },
            "distribution": [
                {
                    "title": "Predicted phototoxicities of carbon nano material.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/180/Predicted%20phototoxicities%20of%20carbon%20nano%20material.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2016-08-09",
            "references": [
                "https://doi.org/10.1016/j.jmgm.2017.03.017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "EPA Contribution to Manuscript \"Evaluation and Error Apportionment of an Ensemble of Atmospheric Chemistry Transport Modelling Systems: Multi-variable Temporal and Spatial Breakdown\"",
            "description": "This dataset contains the data contributed by EPA/ORD/NERL/CED researchers to the manuscript \"Evaluation and Error Apportionment of an Ensemble of Atmospheric Chemistry Transport Modelling Systems: Multi-variable Temporal and Spatial Breakdown \" led by Dr. Efisio Solazzo of the European Commission's Joint Research Center. \n\nThis dataset is associated with the following publication:\nSolazzo, E., R. Bianconi, C. Hogrefe, G. Curci, P. Tuccella, U. Alyuz, A. Balzarini, R. Baro, R. Bellasio, J. Bieser, J. Brandt, J. Christensen, A. Colette, X. Francis, A. Fraser, M. Garcia Vivanco, P. Jim\u00e9nez-Guerrero, U. Im, A. Manders, U. Nopmongcol, N. Kitwiroon, G. Pirovano, L. Pozzoli, M. Prank, R. Sokhi, A. Unal, G. Yarwood, and S. Galmarini. Evaluation and error apportionment of an ensemble of atmospheric chemistry transport modeling systems: multivariable temporal and spatial breakdown.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 17: 3001-3054, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-z09b-493",
            "keyword": [
                "AQMEII",
                "model evaluation",
                "scale analysis",
                "model intercomparision",
                "ozone persistence"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "data_2010_0236_001_CO.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/493/data_2010_0236_001_CO.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data_2010_0236_001_NO2.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/493/data_2010_0236_001_NO2.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data_2010_0236_001_O3.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/493/data_2010_0236_001_O3.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data_2010_0236_001_SO2.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/493/data_2010_0236_001_SO2.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data_2010_0236_002_PM2_5.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/493/data_2010_0236_002_PM2_5.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data_2010_0236_002_PM10.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/493/data_2010_0236_002_PM10.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data_2010_0236_004_O3.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/493/data_2010_0236_004_O3.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data_2010_0236_004_TEMP.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/493/data_2010_0236_004_TEMP.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data_2010_0236_004_WS.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/493/data_2010_0236_004_WS.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data_2010_0236_005_TEMP.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/493/data_2010_0236_005_TEMP.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data_2010_0236_005_WS.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/493/data_2010_0236_005_WS.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2015-12-31",
            "references": [
                "https://doi.org/10.5194/acp-17-3001-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/493/documents/DataDictionary.zip",
            "describedByType": "application/zip",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Persistence of Initial Conditions in Continental Scale Air Quality Simulations",
            "description": "This dataset contains the data used in Figures 1 \u2013 6 and Table 2 of the technical note \"Persistence of Initial Conditions in Continental Scale Air Quality Simulations\". \n\nThis dataset is associated with the following publication:\nHogrefe, C., S. Roselle, and J. Bash. Persistence of initial conditions in continental scale air quality simulations.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 160: 36-45, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-4mwd-521",
            "keyword": [
                "Initial conditions",
                "spin-up period",
                "soil concentrations",
                "inert tracers"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "data_HogrefeChristian_A-4mwd.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/521/data_HogrefeChristian_A-4mwd.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-10-31",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2017.04.009"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/521/documents/DataDictionary_HogrefeEtAl_A-4mwd.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Simulated Pathogen Concentrations in Locally-Collected Greywater and Wastewater",
            "description": "This dataset contains simulated pathogen concentrations in locally-collected greywater and wastewater.  Each .zip file includes 21 .csv files, each containing 10,000 years of simulated daily pathogen concentrations in the water type designated by the title (Combined Greywater, Laundry Greywater, Shower Greywater, Sink Greywater, or Onsite Wastewater).  Each .csv file corresponds to one pathogen (Ad Adenovirus, Ca Campylobacter, Cr Cryptosporidium, Gi Giardia, No Norovirus, Ro Rotavirus, or Sa Salmonella) for one population size (5-, 100-, or 1000-person).  For example, ConcAdCombGW100.csv contains concentrations (Conc) of Adenovirus (Ad) in combined greywater (CombGW) for a 100-person population size (100).  Data is structured as 365 rows (days) by 10,000 columns (years), with the first row and column containing year and day indices, respectively.  Units are # pathogens/L water. \n\nThis dataset is associated with the following publication:\nJahne, M., M. Schoen, J. Garland, and N. Ashbolt. Simulation of enteric pathogen concentrations in locally-collected greywater and wastewater for microbial risk assessments.   Microbial Risk Analysis. Elsevier B.V., Amsterdam,  NETHERLANDS, 5: 44-52, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-f1vv-196",
            "keyword": [
                "greywater",
                "wastewater",
                "decentralized systems",
                "water reuse",
                "waterborne pathogens",
                "microbial risk assessment",
                "non-potable",
                "potable",
                "log reduction target",
                "QMRA",
                "pathogens"
            ],
            "contactPoint": {
                "fn": "Michael Jahne",
                "hasEmail": "mailto:jahne.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Simulated Pathogen Concentrations in Locally-Collected Greywater and Wastewater.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/196/Simulated%20Pathogen%20Concentrations%20in%20Locally-Collected%20Greywater%20and%20Wastewater.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-08-17",
            "references": [
                "https://doi.org/10.1016/j.mran.2016.11.001"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "None",
            "description": "This research effort is a publication summarizing the research needs identified at the Coordinating Research Council\u2019s 2016 Air Quality Research Needs Workshop. As such it contains no scientific data set. This dataset is not publicly accessible because: Since this publication is a discussion and presentation of the top research needs identified at a scientific workshop, it does not present any scientific data - thus there are no data sets associated and none to include in ScienceHub. It can be accessed through the following means: Contact author for any clarifications. Format: There are no data sets associated with this publication. \n\nThis dataset is associated with the following publication:\nCollet, S., R. Guensler, M. Beardsley, R. Mathur, and S. Gao. Highlights from the Coordinating Research Council\u2019s 2016 Air Quality Research Needs Workshop: Top 11 Research\r\nNeeds.   EM:  AIR AND WASTE MANAGEMENT ASSOCIATIONS MAGAZINE FOR ENVIRONMENTAL MANAGERS. Air & Waste Management Association, Pittsburgh, PA, USA,  1-6, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-1c5d-588",
            "keyword": [
                "air quality",
                "modeling",
                "research needs"
            ],
            "contactPoint": {
                "fn": "Rohit Mathur",
                "hasEmail": "mailto:mathur.rohit@epa.gov"
            },
            "distribution": [],
            "modified": "2016-07-05",
            "references": [
                "http://www.awma.org/publications/em-magazine/latest-issue"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Simulating Aqueous-Phase Isoprene-Epoxydiol (IEPOX) Secondary Organic Aerosol Production During the 2013 Southern Oxidant and Aerosol Study (SOAS)",
            "description": "Dataset contains information displayed in figures 1-4 and abstract/table of contents figure. \n\nThis dataset is associated with the following publication:\nBudisulistiorini, S., A. Nenes, A. Carlton, J. Surratt, V.F. McNeill, and H. Pye. Simulating Aqueous-Phase Isoprene-Epoxydiol (IEPOX) Secondary Organic Aerosol Production During the 2013 Southern Oxidant and Aerosol Study (SOAS).   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(9): 5026-5034, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-vmdj-576",
            "keyword": [
                "SOA",
                "SOAS",
                "Secondary Organic Aerosol",
                "isoprene",
                "Fine Particulate Matter",
                "particulate matter (PM)",
                "acidity",
                "sulfate",
                "organosulfate"
            ],
            "contactPoint": {
                "fn": "Havala Pye",
                "hasEmail": "mailto:pye.havala@epa.gov"
            },
            "distribution": [
                {
                    "title": "IEPOXSOAmodel_paper_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/576/IEPOXSOAmodel_paper_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://esrl.noaa.gov/csd/groups/csd7/measurements/2013senex/",
                    "accessURL": "https://esrl.noaa.gov/csd/groups/csd7/measurements/2013senex/"
                }
            ],
            "modified": "2017-05-01",
            "references": [
                "https://doi.org/10.1021/acs.est.6b05750"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CMAQ predicted concentration files",
            "description": "CMAQ predicted ozone. \n\nThis dataset is associated with the following publication:\nGantt, B., G. Sarwar, J. Xing, H. Simon, D. Schwede, B. Hutzell, R. Mathur, and A. Saiz-Lopez. The Impact of Iodide-Mediated Ozone Deposition and Halogen Chemistry on Surface Ozone Concentrations Across the Continental United States.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(3): 1458-1466, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-5x6j-655",
            "keyword": [
                "Halogen chemistry",
                "ozone concentrations",
                "CMAQ",
                "iodide",
                "ozone deposition",
                "marine boundary layer"
            ],
            "contactPoint": {
                "fn": "Golam Sarwar",
                "hasEmail": "mailto:sarwar.golam@epa.gov"
            },
            "distribution": [
                {
                    "title": "CMAQ_BASELINE_O3_SURFACE_08_8HRMAX_AVG.nc.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/655/CMAQ_BASELINE_O3_SURFACE_08_8HRMAX_AVG.nc.tar",
                    "mediaType": "application/x-tar"
                },
                {
                    "title": "CMAQ_CASE_B_O3_SURFACE_08_8HRMAX_AVG.nc.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/655/CMAQ_CASE_B_O3_SURFACE_08_8HRMAX_AVG.nc.tar",
                    "mediaType": "application/x-tar"
                },
                {
                    "title": "CMAQ_CASE_C_O3_SURFACE_08_8HRMAX_AVG.nc.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/655/CMAQ_CASE_C_O3_SURFACE_08_8HRMAX_AVG.nc.tar",
                    "mediaType": "application/x-tar"
                },
                {
                    "title": "CMAQ_CASE_D_O3_SURFACE_08_8HRMAX_AVG.nc.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/655/CMAQ_CASE_D_O3_SURFACE_08_8HRMAX_AVG.nc.tar",
                    "mediaType": "application/x-tar"
                },
                {
                    "title": "CMAQ_CASE_E_O3_SURFACE_08_8HRMAX_AVG.nc.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/655/CMAQ_CASE_E_O3_SURFACE_08_8HRMAX_AVG.nc.tar",
                    "mediaType": "application/x-tar"
                },
                {
                    "title": "CMAQ_REVISED_O3_SURFACE_08_8HRMAX_AVG.nc.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/655/CMAQ_REVISED_O3_SURFACE_08_8HRMAX_AVG.nc.tar",
                    "mediaType": "application/x-tar"
                }
            ],
            "modified": "2016-08-01",
            "references": [
                "https://doi.org/10.1021/acs.est.6b03556"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/655/documents/SrawarGolaml_A-5x6j_Data_Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Experimental data of Se and B released from FGDG, soil and soil-FGDG mixture in EPA-Method 1314 and optimization of fate and transport model simulation results of Se and B leaching from FGDG in an agricultural field and a landfill.  ",
            "description": "The leachate concentrations of Se and B released from FGDG, soil and soil-FGDG mixture obtained from EPA-method 1314 is included in the data set. The non-equilibrium partitioning coefficients (NPC) calculated based on the experimental data also included along with the predicted NPC values calculated using a regression model based on a power function. Long term environmental release of Se and B in agricultural field and a landfill calculated using fate and transport model simulation also included in the data set. \n\nThis dataset is associated with the following publication:\nLittle, K., N. Koralegedara, C. Northeim, and S. Al-Abed. Decision Support for Environmental Management of Industrial Non-Hazardous Secondary Materials:  New Analytical Methods Combined with Simulation and Optimization Modeling.  R. Dewil; J.M. Evans; B. Tansel  JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 196: 137-147, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-8673-644",
            "keyword": [
                "Industrial non-hazardous secondary materials",
                "fate and transport model",
                "Beneficial uses",
                "Beneficial use decision support system"
            ],
            "contactPoint": {
                "fn": "Souhail Al-Abed",
                "hasEmail": "mailto:al-abed.souhail@epa.gov"
            },
            "distribution": [
                {
                    "title": "meta deta set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/644/meta%20deta%20set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-01",
            "references": [
                "https://doi.org/10.1016/j.jenvman.2017.02.075"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/644/documents/data%20dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "X-ray spectroscopy results for the pristine nanosilver solution and solution after undergoing the specific usage scenario ",
            "description": "The results demonstrate the Ag 3d5/2-3/2 spectrum of the pristine AgNPs. Furthermore, the XAS spectra from the analysis of the nanosilver solution (ASAP-AGX-32) after the disinfection process is demonstrated followed by the LCF results indicating the dominant species formed after the disinfection process. \n\nThis dataset is associated with the following publication:\nGitipour, A., S. Al-Abed, S. Thiel, K. Scheckel, and T. Tolaymat. Nanosilver as a disinfectant in dental unit waterlines: Assessment of the physiochemical transformations of the AgNPs.  Jacob de Boer and Shane Snyder  CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 173: 245-252, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-5mks-661",
            "keyword": [
                "X-ray Absorption Spectroscopy",
                "X-ray Photoelectron Spectroscopy",
                "Dental Unit Waterline",
                "Phase transformations"
            ],
            "contactPoint": {
                "fn": "Souhail Al-Abed",
                "hasEmail": "mailto:al-abed.souhail@epa.gov"
            },
            "distribution": [
                {
                    "title": "Dental Unit manuscript Metadata data tables with data dictionary .xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/661/Dental%20Unit%20manuscript%20Metadata%20data%20tables%20with%20data%20dictionary%20.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-05",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2017.01.050"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/661/documents/data%20dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data used in the analysis presented in the manuscript \"Dynamic Evaluation of Two Decades of WRF-CMAQ Ozone Simulations over the Contiguous United States\"",
            "description": "Files containing daily maximum 8-hr ozone mixing ratio observations and WRF/CMAQ simulations used in the analysis presented in the manuscript \u201cDynamic Evaluation of Two Decades of WRF-CMAQ Ozone Simulations over the Contiguous United States\u201d. \n\nThis dataset is associated with the following publication:\nAstitha, M., H. Luo, S.T. Rao, C. Hogrefe, R. Mathur, and N. Kumar. Dynamic evaluation of two decades of WRF-CMAQ ozone simulations over the contiguous United States.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 164: 102-116, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-m90p-540",
            "keyword": [
                "model evaluation",
                "WRF-CMAQ",
                "spectral decomposition",
                "ozone trends",
                "ozone design value",
                "decadal simulations"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "sitecompare_daily_o3_doe_conus36_sf_1990_2010.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/540/sitecompare_daily_o3_doe_conus36_sf_1990_2010.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2015-06-30",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2017.05.020"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/540/documents/HogrefeChristian_A-m90p_Data_Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Breeding bird survey data",
            "description": "The data are maintained by the USGS (https://www.pwrc.usgs.gov/bbs/RawData/)  and provides information on the trends and status of North American bird populations reported as a population abundance index. This dataset is not publicly accessible because: It is secondary data maintained by USGS. It can be accessed through the following means: https://www.pwrc.usgs.gov/bbs/RawData/). Format: Electronic text files. \n\nThis dataset is associated with the following publication:\nSundstrom, S., T. Eason, J. Nelson, D. Angeler, C. Barichievy, A. Garmestani, N. Graham, D. Granholm, L. Gunderson, M. Knutson, K. Nash, M. Nystrom, T. Spanbauer, C. Stow, and C. Allen. Detecting spatial regimes in ecosystems.   ECOLOGY LETTERS. Blackwell Publishing, Malden, MA, USA, 20(1): 19-32, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-wh7r-665",
            "keyword": [
                "breeding bird survey",
                "north america",
                "community structure",
                "USGS",
                "resilience",
                "leading indicators",
                "governance",
                "environmental change",
                "complex systems",
                "law and policy"
            ],
            "contactPoint": {
                "fn": "Tarsha Eason",
                "hasEmail": "mailto:eason.tarsha@epa.gov"
            },
            "distribution": [],
            "modified": "2017-04-25",
            "references": [
                "https://doi.org/10.1111/ele.12709"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Global annual surface air temperature change",
            "description": "The data are maintained by NASA (https://data.giss.nasa.gov/gistemp/)  and provides an estimate of global annual surface air temperature change expressed as temperature anomaly in degrees Celsius. This dataset is not publicly accessible because: It is secondary data. It can be accessed through the following means: The data are maintained by NASA (https://data.giss.nasa.gov/gistemp/). Format: The dataset is secondary data gathered from the NASA site (https://data.giss.nasa.gov/gistemp/) and can be downloaded in a variety of formats including *.txt and *.csv. \n\nThis dataset is associated with the following publication:\nAhmad, N., S. Derrible, T. Eason, and H. Cabezas. Using Fisher information to track stability in multivariate systems.   Royal Society Open Science. Royal Society Publishing, London,  UK,  01-08, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-wh7r-664",
            "keyword": [
                "global surface temperature change",
                "NASA",
                "resilience",
                "leading indicators",
                "governance",
                "environmental change",
                "complex systems",
                "law and policy"
            ],
            "contactPoint": {
                "fn": "Tarsha Eason",
                "hasEmail": "mailto:eason.tarsha@epa.gov"
            },
            "distribution": [],
            "modified": "2016-08-08",
            "references": [
                "https://doi.org/10.1098/rsos.160582"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Modeled population exposures to ozone",
            "description": "Population exposures to ozone from APEX modeling for combinations of potential future air quality and demographic change scenarios. This dataset is not publicly accessible because: Total file size is too large (73 GB) to be included in ScienceHub. It can be accessed through the following means: data files are stored at L:\\PRIV\\DIONISIO\\ACE118\\APEXFiles\\RCode\\Rfiles. Format: 73 GB, 2,300 files (saved as .rsav R data files). \n\nThis dataset is associated with the following publication:\nDionisio, K., C. Nolte, T. Spero, S. Graham, N. Caraway, K. Foley, and K. Isaacs. Characterizing the impact of projected changes in climate and air quality on human exposures to ozone.   Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London,  UK, 27(3): 260-270, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-1zcv-534",
            "keyword": [
                "criteria pollutants",
                "Exposure modeling",
                "personal exposure",
                "population-based studies",
                "exposure",
                "Ozone",
                "climate",
                "climate change"
            ],
            "contactPoint": {
                "fn": "Kathie Dionisio",
                "hasEmail": "mailto:dionisio.kathie@epa.gov"
            },
            "distribution": [],
            "modified": "2016-08-17",
            "references": [
                "https://doi.org/10.1038/jes.2016.81"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/534/documents/READ%20ME_Dionisioetal_Dataset.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Combined Fish Data",
            "description": "The data set is abundance or presence/absence data collected by species from wadeable stream sites along with water chemistry, including specifically specific conductivity and some other variables that were not used in the analysis. \n\nThis dataset is associated with the following publication:\nGriffith, M., L. Zheng, and S. Cormier. Using extirpation to evaluate ionic tolerance of freshwater fish.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(3): 871-883, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1376690",
            "keyword": [
                "fish",
                "Specific Conductivity",
                "salinity",
                "sensitivity distribution",
                "freshwater."
            ],
            "contactPoint": {
                "fn": "Michael Griffith",
                "hasEmail": "mailto:griffith.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Combined_Less.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376690/Combined_Less.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Fish Conductivity Column Metadata.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376690/Fish%20Conductivity%20Column%20Metadata.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-01-18",
            "references": [
                "https://doi.org/10.1002/etc.4022"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1376690/documents/Fish%20Conductivity%20Column%20Metadata.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Evaluation of the immunomodulatory effects of 2,3,3,3-tetrafluoro-2-(heptafluoropropoxy)-propanoate (\u201cGenX\u201d) in C57BL/6 mice",
            "description": "Raw data file outputs of serum and urine measurements of GenX in dosed rodents. \n\nThis dataset is associated with the following publication:\nRushing, B., Q. Hu, J. Franklin, R. McMahen, S. Dagnino, C. Higgins, M. Strynar, and J. DeWitt. Evaluation of the Immunomodulatory Effects of 2,3,3,3-tetrafluoro-2-(heptafluoropropoxy)-propanoate (\u201cGenX\u201d) in C57BL/6 Mice.   ENVIRONMENTAL TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 156(1): 179-189, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-9gj6-433",
            "keyword": [
                "GenX",
                "serum",
                "urine",
                "immunotoxicity",
                "per and polyfluorinated"
            ],
            "contactPoint": {
                "fn": "Mark Strynar",
                "hasEmail": "mailto:strynar.mark@epa.gov"
            },
            "distribution": [
                {
                    "title": "9-6-13 Dweitt U2M3O hex 0 and 1 mg kg dosed.xml",
                    "downloadURL": "https://pasteur.epa.gov/uploads/433/9-6-13%20Dweitt%20U2M3O%20hex%200%20and%201%20mg%20kg%20dosed.xml",
                    "mediaType": "text/xml"
                },
                {
                    "title": "9-6-13 Dweitt U2M3O hex 10 and 100 mg kg no IS dosed.xml",
                    "downloadURL": "https://pasteur.epa.gov/uploads/433/9-6-13%20Dweitt%20U2M3O%20hex%2010%20and%20100%20mg%20kg%20no%20IS%20dosed.xml",
                    "mediaType": "text/xml"
                },
                {
                    "title": "9-6-13 Dweitt U2M3O hex 10 repeat  mg kg no IS dosed.xml",
                    "downloadURL": "https://pasteur.epa.gov/uploads/433/9-6-13%20Dweitt%20U2M3O%20hex%2010%20repeat%20%20mg%20kg%20no%20IS%20dosed.xml",
                    "mediaType": "text/xml"
                },
                {
                    "title": "1-15-14 Dewitt U2M3O-hexane dosed rodent urine.xml",
                    "downloadURL": "https://pasteur.epa.gov/uploads/433/1-15-14%20Dewitt%20U2M3O-hexane%20dosed%20rodent%20urine.xml",
                    "mediaType": "text/xml"
                },
                {
                    "title": "1-21-14 Dewitt high redo U2M3O-hexane dosed rodent urine.xml",
                    "downloadURL": "https://pasteur.epa.gov/uploads/433/1-21-14%20Dewitt%20high%20redo%20U2M3O-hexane%20dosed%20rodent%20urine.xml",
                    "mediaType": "text/xml"
                },
                {
                    "title": "4-24-13 Dewitt dosed U2M3O-hexane male mice.xml",
                    "downloadURL": "https://pasteur.epa.gov/uploads/433/4-24-13%20Dewitt%20dosed%20U2M3O-hexane%20male%20mice.xml",
                    "mediaType": "text/xml"
                },
                {
                    "title": "4-29-13 redo Dewitt U2MO3-hex high dosed male mice.xml",
                    "downloadURL": "https://pasteur.epa.gov/uploads/433/4-29-13%20redo%20Dewitt%20U2MO3-hex%20high%20dosed%20male%20mice.xml",
                    "mediaType": "text/xml"
                },
                {
                    "title": "5-29-13 redo Dewitt male mouse U2M3O-hexane 0 and 1 mg_kg.xml",
                    "downloadURL": "https://pasteur.epa.gov/uploads/433/5-29-13%20redo%20Dewitt%20male%20mouse%20U2M3O-hexane%200%20and%201%20mg_kg.xml",
                    "mediaType": "text/xml"
                },
                {
                    "title": "5-30-13 Dewitt U2M30-hex dosed male mouse serum 10 and 100 mg_kg and high repeats.xml",
                    "downloadURL": "https://pasteur.epa.gov/uploads/433/5-30-13%20Dewitt%20U2M30-hex%20dosed%20male%20mouse%20serum%2010%20and%20100%20mg_kg%20and%20high%20repeats.xml",
                    "mediaType": "text/xml"
                },
                {
                    "title": "5-31-13 Dewitt dosed male mice U2M3O-hexane high rerun samples.xml",
                    "downloadURL": "https://pasteur.epa.gov/uploads/433/5-31-13%20Dewitt%20dosed%20male%20mice%20U2M3O-hexane%20high%20rerun%20samples.xml",
                    "mediaType": "text/xml"
                },
                {
                    "title": "Rushing et al_Raw Data.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/433/Rushing%20et%20al_Raw%20Data.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-10-13",
            "references": [
                "https://doi.org/10.1093/toxsci/kfw251"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Advancing the Adverse Outcome Pathway Concept \u2013 An International \u2018Horizon Scanning\u2019 Approach ",
            "description": "Our ability to conduct whole organism toxicity tests to understand chemical safety has been outpaced by our ability to synthesize new chemicals for a wide variety of commercial applications.  Therefore, to increase efficiencies in chemical risk assessment, scientists and risk assessors are turning to mechanistic-based studies, making greater use of in vitro and in silico methods, to evaluate potential environmental and human health hazards.  A framework that has gained traction for capturing available knowledge describing the linkage between mechanistic data and the apical toxicity endpoints, required for regulatory assessments, is the adverse outcome pathway (AOP).  A number of international activities have focused on AOP development and plausible applications to regulatory decision-making.  These interactions have prompted dialog between research scientists and regulatory communities to consider how best to use the AOP framework in risk assessment.  While expert-facilitated discussions have been instrumental in moving the science of AOPs forward, it was recognized that a survey of the broader scientific community would aid in identifying current limitations while guiding future initiatives for the AOP framework.  To that end, a global \u2018Horizon Scanning\u2019 exercise was conducted to solicit questions concerning the challenges or limitations that must be addressed to realize the full potential of the AOP framework in research and regulatory decision making.  The majority of questions received fell into several broad topical areas including the concepts of AOP networks and quantitative AOPs, collaboration on and communication of AOP knowledge, AOP discovery and development, chemical and cross-species extrapolation, exposure considerations, and AOP applications.  An expert ranking exercise was then conducted to identify the most important questions for each category.  These questions were used to develop four broad themes to inform and guide future AOP research and regulatory initiatives.  In addition, frequently asked questions (FAQs) were identified and addressed by experts in the field.  Answers to FAQs will aid in framing further discussions about common misperceptions about AOPs and allow for clarification of AOP topics.  The need for clarification occurred with surprising frequency, indicating that improvements are needed in communicating the AOP framework among the scientific and regulatory communities.  Overall, the \u2018Horizon Scanning\u2019 effort brought together the global scientific community to guide the direction of future initiatives and identify key questions surrounding the AOP framework.  The views expressed in this manuscript are those of the authors and may not reflect U.S. EPA policy. This dataset is not publicly accessible because: It is available online and was collected through the Society of Environmental Toxicology and Chemistry in support of a Pellston Workshop. It can be accessed through the following means: All materials associated with this paper are found at the provided URL as the main document or as the supplemental files. Format: http://onlinelibrary.wiley.com/doi/10.1002/etc.3805/full. \n\nThis dataset is associated with the following publication:\nLaLone, C., G. Ankley, S. Belanger, M. Embry, G. Hodges, D. Knapen, S. Munn, E. Perkins, M. Rudd, D. Villeneuve, M. Whelan, C. Willett, X.  Zhang, and M. Hecker. Advancing the adverse outcome pathway framework - An international horizon scanning approach.   SOCIETY OF ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY JOURNAL. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 36(6): 1411-1421, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-g4fj-514",
            "keyword": [
                "Horizon Scanning",
                "expert ranking",
                "global survey",
                "quantitiative",
                "network",
                "regulatory application",
                "communication and outreach",
                "adverse outcome pathway framework",
                "adverse outcome pathway",
                "ecotoxicology",
                "honey bee",
                "cross-species extrapolation",
                "screening and prioritization",
                "networks"
            ],
            "contactPoint": {
                "fn": "Carlie Lalone",
                "hasEmail": "mailto:lalone.carlie@epa.gov"
            },
            "distribution": [],
            "modified": "2016-08-30",
            "references": [
                "https://doi.org/10.1002/etc.3805"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://onlinelibrary.wiley.com/doi/10.1002/etc.3805/full",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Rainwater harvesting human health and environmental impact assessment and sustainability analysis",
            "description": "LCA/LCCA/LCIA data used to create figures and tables in the papers. \n\nThis dataset is associated with the following publications:\nGhimire, S., and J. Johnston. Holistic impact assessment and cost savings of rainwater harvesting at the watershed scale.   Elementa: Science of the Anthropocene. University of California Press (UC Press), Oakland, CA, USA, 5(9): 1-17, (2017).\nGhimire, S., and J. Johnston. A modified eco-efficiency framework and methodology for advancing the state of practice of sustainability analysis as applied to green infrastructure.   Integrated Environmental Assessment and Management. Allen Press, Inc., Lawrence, KS, USA, 13(5): 821-831, (2017).\nGhimire, S., J. Johnston, W. Ingwersen, and S. Sojka. Life cycle assessment of a commercial rainwater harvesting system compared with a municipal water supply system.   JOURNAL OF CLEANER PRODUCTION. Elsevier Science Ltd, New York, NY, USA, 151: 74\u201386, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-fttt-543",
            "keyword": [
                "agricultural and domestic rainwater harvesting systems",
                "sustainability analysis",
                "data envelopment analysis",
                "eco-efficiency analysis",
                "Commercial rainwater harvesting",
                "Municipal water supply",
                "life cycle assessment",
                "life cycle impact assessment method",
                "life cycle costing",
                "holistic analysis",
                "watershed scale",
                "Energy intensity"
            ],
            "contactPoint": {
                "fn": "John Johnston",
                "hasEmail": "mailto:johnston.johnm@epa.gov"
            },
            "distribution": [
                {
                    "title": "RWH PAPERS DATA.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/543/RWH%20PAPERS%20DATA.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-02-27",
            "references": [
                "https://doi.org/10.1525/elementa.135",
                "https://doi.org/10.1002/ieam.1928",
                "https://doi.org/10.1016/j.jclepro.2017.02.025"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/543/documents/SOP%20LCA%20Projects%20Involving%20Data%20Collection%2020Jan2015.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Results of chemical analysis from the 2008-2009 National Rivers and Streams Assessment Survey, including persistent organic pollutants and pharmaceuticals",
            "description": "In 2008-2009, fish are were collected from approximately 560 national streams, which included a representative subset of 154 urban river sites, which were in close proximity to urban areas. Site selection included a mix of statistically-selected and targeted sites. ORD/NERL analyzed fish fillets from the 560 stream sampling sites for 22 pesticides, 21 congeners of PCBs, and 8 congeners of PBDEs. Surface water was collected at the 154 urban river sites, and was analyzed for concentrations of almost 50 human prescription pharmaceuticals. Two data files are included, and report the full findings of the chemical analysis in each individual fish or water sample site for each chemical. \n\nThis dataset is associated with the following publications:\nBatt , A., T. Kincaid , M. Kostich , J. Lazorchak , and T. Olsen. Evaluating the extent of pharmaceuticals in surface waters of the United States using a national scale rivers and streams assessment survey.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 35(4): 874-881, (2016).\nBatt, A., J. Wathen, J. Lazorchak, T. Olsen, and T. Kincaid. Statistical Survey of Persistent Organic Pollutants: Risk Estimations to Humans and Wildlife through Consumption of Fish from U.S. Rivers.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(5): 3021-3031, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-q57n-156",
            "keyword": [
                "fish",
                "brominated flame retardant",
                "water quality",
                "pestcides",
                "PCBs",
                "pharmaceuticals",
                "fish tissue"
            ],
            "contactPoint": {
                "fn": "Angela Batt",
                "hasEmail": "mailto:batt.angela@epa.gov"
            },
            "distribution": [
                {
                    "title": "NRSA0809-POPs-fishtissue.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/156/NRSA0809-POPs-fishtissue.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "NRSA0809-Pharmaceuticals-surfacewater.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/156/NRSA0809-Pharmaceuticals-surfacewater.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-03",
            "references": [
                "https://doi.org/10.1002/etc.3161",
                "https://doi.org/10.1021/acs.est.6b05162"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Spatiotemporal modeling of WNV in mosquitoes in Suffolk County",
            "description": "R code and dataset to produce spatial models. \n\nThis dataset is associated with the following publication:\nMeyer, M., S. Campbell, and J. Johnston. Spatiotemporal modeling of ecological and sociological predictors of West Nile virus in Suffolk County, NY, mosquitoes.   Ecosphere. ESA Journals,    8(6): e01854, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-0001-600",
            "keyword": [
                "Bayesian",
                "West Nile",
                "INLA",
                "SPDE",
                "Culex pipiens",
                "spatial modeling",
                "disease ecology",
                "Long Island",
                "septic systems"
            ],
            "contactPoint": {
                "fn": "John Johnston",
                "hasEmail": "mailto:johnston.johnm@epa.gov"
            },
            "distribution": [
                {
                    "title": "Ecosphere data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/600/Ecosphere%20data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-05-09",
            "references": [
                "https://doi.org/10.1002/ecs2.1854"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/600/documents/DataDictionary_WNVPaper.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The average concentrations of As, Cd, Cr, Hg, Ni and Pb in residential soil and drinking water obtained from springs and wells in Rosia Montana area. ",
            "description": "The average concentrations of As, Cd, Cr, Hg, Ni and Pb in n=84 residential soil samples, in Rosia Montana area, analyzed by X-ray fluorescence spectrometry are given along with the standard deviations. The metal concentrations of mine pit soil (n=7) provided by Rosia Montana Gold Corporation are also given. The data are compared with the Romanian regulatory exposure levels (Alert threshold (AT) and Intervention threshold (IT)) for residential soil.\r\nThe average concentrations of As, Cd, Cr, Hg, Ni and Pb in n=10 drinking water samples collected from springs and wells in Rosia Montana area, analyzed by atomic absorption spectrometry with hydride generation (for As), graphite furnace (for Pb, Cd, Cr, Ni), cold vapors hydride generation (for Hg) are given along with the standard deviations. The secondary data of metal concentrations of the stream waters in Rosia Montana area from 2005-2008, obtained from Rosia Montana Gold Corporation (RMGC) Environmental Impact Assessment Study - water Baseline report, 2007 and  Rosia Montana Gold Corporation (RMGC) Environmental Impact Assessment Study - Surface water quality, 2007 are also available. The Romanian regulatory exposure levels for metals in drinking water are given for comparison purposes. \r\nThe distribution of metal concentrations in residential soils around the Rosia Montana area are given along with the distances from the mine pit. \n\nThis dataset is associated with the following publication:\nNeamtiu, I., S. Al-Abed, J. McKernan, C. Baciu, E. Gurzau, A. Pogacean, and S. Bessler. Metals contamination in environmental media in residential areas around Romanian mining sites.  David O. Carpenter, and Peter Sly  REVIEWS ON ENVIRONMENTAL HEALTH. Freund Publishing House Limited, Tel Aviv,  ISRAEL, 31(4): 1-6, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-wsvg-681",
            "keyword": [
                "metal contamination",
                "mining",
                "contaminated water",
                "contaminated soil"
            ],
            "contactPoint": {
                "fn": "John McKernan",
                "hasEmail": "mailto:mckernan.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "Meta data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/681/Meta%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-07",
            "references": [
                "https://doi.org/10.1515/reveh-2016-0033"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/681/documents/data%20dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Rainbow trout estrogen receptor (ER) competitive bindng and vitellogenin induction agonism/antagonism data for 94 chemicals",
            "description": "This dataset is from screening 94 diverse chemicals for estrogen receptor (ER) activation in a competitive rainbow trout ER binding assay and a trout liver slice vitellogenin mRNA expression assay. \n\nThis dataset is associated with the following publication:\nHornung, M., M. Tapper, J. Denny, B. Sheedy, R. Erickson, T. Sulerud, R. Kolanczyk, and P. Schmieder. Avoiding false positives and optimizing identification of true negatives in estrogen receptor binding and agonist/antagonist assays.   Applied In vitro Toxicology. Mary Ann Liebert, Inc., Larchmont, NY, USA, 3(2): 163-181, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-8czj-472",
            "keyword": [
                "rainbow trout",
                "antagonist",
                "estrogen receptor",
                "in vitro",
                "competitive binding",
                "vitellogenin"
            ],
            "contactPoint": {
                "fn": "Michael Hornung",
                "hasEmail": "mailto:hornung.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Trout_ER_Antagonism_Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/472/Trout_ER_Antagonism_Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-01-11",
            "references": [
                "https://doi.org/10.1089/aivt.2016.0021"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data sets used in the analysis presented in the manuscript \u201cRegional and Hemispheric Influences on Temporal Variability in Baseline Carbon Monoxide and Ozone over the Northeast US\u201d",
            "description": "This dataset documents that all of the data analyzed in the manuscript \"Regional and Hemispheric Influences on Temporal Variability in Baseline Carbon Monoxide and Ozone over the Northeast US \" led by doctoral candidate Ms. Ying Zhou of the College of Environmental Science and Forestry at the State University of New York at Syracuse were contributed by non-EPA research groups and entities. \n\nThis dataset is associated with the following publication:\nZhou, Y., H. Mao, K. Demerjian , C. Hogrefe , and J.L. Liu. Regional and hemispheric influences on temporal variability in baseline carbon monoxide and ozone over the Northeast US.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 164: 309-324, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1364176",
            "keyword": [
                "Baseline CO",
                "baseline O3",
                "Temporal Variability",
                "Northeast U.S.",
                "emission",
                "Meteorology"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "ZhouEtAl_DataStatement.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1364176/ZhouEtAl_DataStatement.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-04-15",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2017.06.017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Decontamination of B. globigii spores from drinking water infrastructure using disinfectants",
            "description": "Decontamination of Bacillus spores adhered to common drinking water infrastructure surfaces was evaluated using a variety of disinfectants.  Corroded iron and cement-mortar lined iron represented the infrastructure surfaces, and were conditioned in a 23 m long, 15 cm diameter (75 ft long, 6 in diameter) pilot-scale drinking water distribution pipe system.  Decontamination was evaluated using increased water velocity (flushing) alone at 0.5 m sec-1 (1.7 ft sec-1), as well as free chlorine (5 and 25 mg L-1), monochloramine (25 mg L-1), chlorine dioxide (5 and 25 mg L-1), ozone (2.0 mg L-1), peracetic acid 25 mg L-1) and acidified nitrite (0.1 mol L-1 at pH 2 and 3), all followed by flushing at 0.3 m sec-1 (1 ft sec-1).  Flushing alone reduced the adhered spores by 0.5 and 2.0 log10 from iron and cement-mortar, respectively.   Log10 reduction on corroded iron pipe wall coupons ranged from 1.0 to 2.9 at respective chlorine dioxide concentrations of 5 and 25 mg L-1, although spores were undetectable on the iron surface during disinfection at 25 mg L-1.  Acidified nitrite (pH 2, 0.1 mol L-1) yielded no detectable spores on the iron surface during the flushing phase after disinfection. Chlorine dioxide was the best performing disinfectant with >3.0 log10 removal from cement-mortar at 5 and 25 mg L-1.The data show that free chlorine, monochloramine, ozone and chlorine dioxide followed by flushing can reduce adhered spores by >3.0 log10 on cement-mortar. \n\nThis dataset is associated with the following publication:\nSzabo , J., G. Meiners, L. Heckman, G. Rice , and J. Hall. Decontamination of Bacillus spores adhered to iron and cement-mortar drinking water infrastructure in a model system using disinfectants.   JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 187: 1-7, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "A-g79s-453",
            "keyword": [
                "bacillus atrophaeus",
                "Bacillus anthracis",
                "Decontamination",
                "drinking water",
                "infrastructure",
                "free chlorine",
                "monochloramine",
                "chlorine dioixde",
                "Ozone",
                "acidified nitrite",
                "peracetic acid",
                "flushing",
                "iron",
                "cement-mortar",
                "water pipes",
                "bacterial spores"
            ],
            "contactPoint": {
                "fn": "Jeffrey Szabo",
                "hasEmail": "mailto:szabo.jeff@epa.gov"
            },
            "distribution": [
                {
                    "title": "Disinfection Loop Data Analysis 11252016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/453/Disinfection%20Loop%20Data%20Analysis%2011252016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-11-25",
            "references": [
                "https://doi.org/10.1016/j.jenvman.2016.11.024"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataforfigures_NEWSMRB-DIN",
            "description": "These are the values plotted in the manuscript and supplemental information sections. \n\nThis dataset is associated with the following publication:\nMcCrackin, M., E. Cooter, R. Dennis, J. Harrison, and J. Compton. Alternative futures of dissolved inorganic nitrogen export from the Mississippi River Basin: influence of crop management, atmospheric deposition, and population growth.   BIOGEOCHEMISTRY. Springer, New York, NY, USA, 133(3): 263-377, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1364132",
            "keyword": [
                "dissolved inorganic nitrogen",
                "Mississippi River Basin",
                "tile drain",
                "atmospheric deposition",
                "sewage",
                "fertilizer",
                "model coastal zone"
            ],
            "contactPoint": {
                "fn": "Ellen Cooter",
                "hasEmail": "mailto:cooter.ellen@epa.gov"
            },
            "distribution": [
                {
                    "title": "Dataforfigures_NEWSMRB-DIN.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1364132/Dataforfigures_NEWSMRB-DIN.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-19",
            "references": [
                "https://doi.org/10.1007/s10533-017-0331-z"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "FigS7.txt",
            "description": "This is an ascii file with georeferencing information containing the data plotted in Figure S7 of the supplemental information manuscript section. \n\nThis dataset is associated with the following publication:\nMcCrackin, M., E. Cooter, R. Dennis, J. Harrison, and J. Compton. Alternative futures of dissolved inorganic nitrogen export from the Mississippi River Basin: influence of crop management, atmospheric deposition, and population growth.   BIOGEOCHEMISTRY. Springer, New York, NY, USA, 133(3): 263-377, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1364743",
            "keyword": [
                "agricultural land cover",
                "dissolved inorganic nitrogen",
                "Mississippi River Basin",
                "tile drain",
                "atmospheric deposition",
                "sewage",
                "fertilizer",
                "model coastal zone"
            ],
            "contactPoint": {
                "fn": "Ellen Cooter",
                "hasEmail": "mailto:cooter.ellen@epa.gov"
            },
            "distribution": [
                {
                    "title": "FigS7.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1364743/FigS7.txt",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2017-06-22",
            "references": [
                "https://doi.org/10.1007/s10533-017-0331-z"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "FigS8.txt",
            "description": "This is an ASCII file with georeferencing information containing data plotted in Figure S8 of the supplemental information section of the manuscript. \n\nThis dataset is associated with the following publication:\nMcCrackin, M., E. Cooter, R. Dennis, J. Harrison, and J. Compton. Alternative futures of dissolved inorganic nitrogen export from the Mississippi River Basin: influence of crop management, atmospheric deposition, and population growth.   BIOGEOCHEMISTRY. Springer, New York, NY, USA, 133(3): 263-377, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1364744",
            "keyword": [
                "tile drainage area",
                "dissolved inorganic nitrogen",
                "Mississippi River Basin",
                "tile drain",
                "atmospheric deposition",
                "sewage",
                "fertilizer",
                "model coastal zone"
            ],
            "contactPoint": {
                "fn": "Ellen Cooter",
                "hasEmail": "mailto:cooter.ellen@epa.gov"
            },
            "distribution": [
                {
                    "title": "FigS8.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1364744/FigS8.txt",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2017-06-22",
            "references": [
                "https://doi.org/10.1007/s10533-017-0331-z"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Mutagenicity of Oil Burn Emissions",
            "description": "Description included in the dataset. \n\nThis dataset is associated with the following publication:\nDeMarini, D., S. Warren, K. Lavrich, A. Flen, J. Aurell, B. Mitchell, D. Greenwell, B. Preston, J. Schmid, B. Linak, M. Hays, J. Samet, and B. Gullett. Mutagenicity and Oxidative Damage Induced by an Organic Extract of the Particulate Emissions from a Simulation of the Deepwater Horizon Surface Oil Burns.   ENVIRONMENTAL AND MOLECULAR MUTAGENESIS. John Wiley & Sons, Inc, Hoboken, NJ, USA, 58(3): 162-171, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-v429-444",
            "keyword": [
                "oil burn emissions",
                "Mutagenicity",
                "Salmonella",
                "oil burn",
                "polycyclic aromatic hydrocarbons",
                "oxidative damage",
                "emission factor"
            ],
            "contactPoint": {
                "fn": "David Demarini",
                "hasEmail": "mailto:demarini.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science Hub Data Set for BP Oil Burn.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/444/Science%20Hub%20Data%20Set%20for%20BP%20Oil%20Burn.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-06-01",
            "references": [
                "https://doi.org/10.1002/em.22085"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The Application of a Highly Purified Rat Leydig Cell Assay as a Complement to the H295R Steroidogenesis Assay for the Evaluation of Toxicant Induced Alterations in Testosterone Production",
            "description": "The greater dynamic range of testosterone production in a highly purified rat Leydig cell assay permitted the detection of chemical induced inhibition that was not detected by the high throughput screening format of the H295R steroidogenesis assay. This dataset is associated with the following publication:\nKlinefelter , G., J. Laskey, and R. Amann. Statin Drugs Markedly Inhibit Testosterone Production by Rat Leydig Cells In Vitro: Implications for Men.   REPRODUCTIVE TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 45: 52-58, (2014). NOTE: This dataset has been removed from public access due to revocation. Please refer inquiries regarding this dataset to the listed contact person.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1367522",
            "keyword": [
                "Leydig cells",
                "testosterone",
                "testis",
                "cell culture",
                "Endocrine Disruptors",
                "gonadal steroids",
                "male infertility",
                "steroidogenesis",
                "Leydig cell assay",
                "2nd Tier screen"
            ],
            "contactPoint": {
                "fn": "Gary Klinefelter",
                "hasEmail": "mailto:klinefelter.gary@epa.gov"
            },
            "distribution": [],
            "modified": "2017-06-16",
            "references": null,
            "publisher": {
                "name": "U.S. Environmental Protection Agency",
                "subOrganizationOf": {
                    "name": "U.S. Government"
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Annual variations and effects of temperature on Legionella spp. and other potential opportunistic pathogens in tap and shower water",
            "description": "The data contained in this worksheet provides the quantitative detection of potential pathogens for the bathroom water samples used in this study. \n\nThis dataset is associated with the following publication:\nLu, J., H. Buse, I. Struewing, A. Zhao, D. Lytle, and N. Ashbolt. Annual variations and effects of temperature on Legionella spp. and other potential opportunistic pathogens in tap and shower water.   JOURNAL OF APPLIED MICROBIOLOGY. Blackwell Publishing, Malden, MA, USA, 24(0): 2326-2336, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1366969",
            "keyword": [
                "bath tap water",
                "opportunistic pathogen",
                "legionella",
                "qPCR",
                "shower water",
                "tapwater"
            ],
            "contactPoint": {
                "fn": "Jingrang Lu",
                "hasEmail": "mailto:lu.jingrang@epa.gov"
            },
            "distribution": [
                {
                    "title": "DataSet_LegionellaBathroom ESPR.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1366969/DataSet_LegionellaBathroom%20ESPR.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-19",
            "references": [
                "https://doi.org/10.1007/s11356-016-7921-5"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Monochloramine Cometabolism by Mixed-Culture Nitrifiers under Drinking Water Conditions",
            "description": "Data for Figures in manuscript. \n\nThis dataset is associated with the following publication:\nMaestre, J., D. Wahman , and G. Speitel. Monochloramine Cometabolism by Mixed-Culture Nitrifiers under Drinking Water Conditions.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(12): 6240-6248, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1365718",
            "keyword": [
                "nitrification",
                "chloramine"
            ],
            "contactPoint": {
                "fn": "David Wahman",
                "hasEmail": "mailto:wahman.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "Monochloramine Cometabolism by Mixed-Culture Nitrifiers under Drinking Water Conditions.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1365718/Monochloramine%20Cometabolism%20by%20Mixed-Culture%20Nitrifiers%20under%20Drinking%20Water%20Conditions.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-03-10",
            "references": [
                "https://doi.org/10.1021/acs.est.5b05641"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Monochloramine Cometabolism by Nitrifying Biofilm Relevant to Drinking Water",
            "description": "Data for Figures in manuscript. \n\nThis dataset is associated with the following publication:\nWahman , D., J. Maestre, and G. Speitel Jr.. Monochloramine Cometabolism by Nitrifying Biofilm Relevant to Drinking Water.   JOURNAL OF AMERICAN WATER WORKS ASSOCIATION. American Water Resources Association, Middleburg, VA, USA, 108(7): 362-373, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1365719",
            "keyword": [
                "nitrification",
                "chloramine"
            ],
            "contactPoint": {
                "fn": "David Wahman",
                "hasEmail": "mailto:wahman.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "Monochloramine Cometabolism by Nitrifying Biofilm Relevant to Drinking Water.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1365719/Monochloramine%20Cometabolism%20by%20Nitrifying%20Biofilm%20Relevant%20to%20Drinking%20Water.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-03-09",
            "references": [
                "http://www.awwa.org/publications/journal-awwa/abstract/articleid/58233023.aspx"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Adverse outcome pathway (AOP) development and weight of evidence evaluation as illustrated by ecological case studies using online tools such as ECOTOX and SeqAPASS",
            "description": "The majority of this dataset includes the query output from online databases ECOTOX and SeqAPASS used to support the ecological AOP case studies described within the manuscript.  The final worksheet includes the raw data used to generate concentration vs response curves for four putative chemical initiators (Supplemental Figure S4). \n\nThis dataset is associated with the following publication:\nFay, K., D. Villeneuve, C. LaLone, Y. Song, K.E. Tollefsen, and G. Ankley. Practical approaches to adverse outcome pathway (AOP) development as illustrated by ecological case studies.   SOCIETY OF ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY JOURNAL. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 36(6): 1429\u20131449, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-ghxh-429",
            "keyword": [
                "adverse outcome pathway",
                "weight of evidence",
                "ecotoxicology",
                "case studies",
                "Risk Assessment"
            ],
            "contactPoint": {
                "fn": "Kellie Fay",
                "hasEmail": "mailto:fay.kellie@epa.gov"
            },
            "distribution": [
                {
                    "title": "AOP development_Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/429/AOP%20development_Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-10-03",
            "references": [
                "https://doi.org/10.1002/etc.3770"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Weight of evidence evaluation of a network of adverse outcome pathways linking activaiton of the nicotinic acetylcholine receptor in honey bees to colony death",
            "description": "Ongoing honey bee colony losses are of significant international concern because of the essential role these insects play in pollinating many high nutrient crops, such as fruits, vegetables, and nuts.  Both chemical and non-chemical stressors have been implicated as possible contributors to colony failure; however, the potential role(s) of commonly-used neonicotinoid insecticides has emerged as particularly concerning. Neonicotinoids act on the nicotinic acetylcholine receptors (nAChRs) in the central nervous system to eliminate target pest insects. However, mounting evidence indicates that these neonicotinoids also may adversely affect beneficial pollinators, such as the honey bee (Apis mellifera), via impairments on learning and memory, and ultimately foraging success. The specific mechanisms linking activation of the nAChR to adverse effects on learning and memory are uncertain. Additionally, clear connections between observed impacts on individual bees and colony level effects are lacking. The objective of this review was to develop adverse outcome pathways (AOPs) as a means to evaluate the biological plausibility and empirical evidence supporting (or refuting) the linkage between activation of the physiological target site, the nAChR, and colony level consequences. Development of AOPs has led to the identification of research gaps which, for example, may be of high priority in understanding how perturbation of pathways involved in neurotransmission can adversely affect normal colony functions, causing colony instability and subsequent bee population failure. A putative AOP network was developed, laying the foundation for further insights as to the role of combined chemical and non-chemical stressors in impacting bee populations. Insights gained from the putative AOP network assembly, which more realistically represents multi-stressor impacts on honey bee colonies, are promising toward understanding common sensitive nodes in key biological pathways and identifying where mitigation strategies may be focused to reduce colony losses. This dataset is not publicly accessible because: No data, literature review only. It can be accessed through the following means: N/A. Format: N/A. \n\nThis dataset is associated with the following publication:\nLaLone, C., D. Villeneuve, J. Wu-Smart, R. Milsk, K. Sappington, K. Garber, J. Housenger, and G. Ankley. Weight of evidence evaluation of a network of adverse outcome pathways linking activation of the nicotinic acetylcholine receptor in honey bees to colony death.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 584: 751\u2013775, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-g4fj-513",
            "keyword": [
                "Adverse outcome pathway network",
                "neonicotinoids",
                "bees",
                "; multiple stressors",
                "weight of evidence",
                "adverse outcome pathway",
                "ecotoxicology",
                "honey bee",
                "cross-species extrapolation",
                "screening and prioritization",
                "networks"
            ],
            "contactPoint": {
                "fn": "Carlie Lalone",
                "hasEmail": "mailto:lalone.carlie@epa.gov"
            },
            "distribution": [],
            "modified": "2017-02-07",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2017.01.113"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "NWCA 2011 Soil Chemistry - Data",
            "description": "NWCA 2011 Soil Chemistry Data. \n\nThis dataset is associated with the following publication:\nNahlik, A., and M.S. Fennessy. Carbon storage in US wetlands.   Nature Communications. Nature Publishing Group, London,  UK, 7: 1-9, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1367565",
            "keyword": [
                "soil data",
                "carbon",
                "wetlands",
                "National Wetland Condition Assessment",
                "National Aquatic Resource Surveys",
                "climate change"
            ],
            "contactPoint": {
                "fn": "Amanda Nahlik",
                "hasEmail": "mailto:nahlik.amanda@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys"
                }
            ],
            "modified": "2016-10-01",
            "references": [
                "https://doi.org/10.1038/ncomms13835"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Chemical concentrations, exposures, health risks by census tract from National Scale Air Toxics Assessment (NATA)",
            "description": "Chemical concentrations, exposures, health risks by census tract for the United States from National Scale Air Toxics Assessment (NATA). \n\nThis dataset is associated with the following publication:\nHuang, H., and T. Barzyk. Connecting the Dots: Linking Environmental Justice Indicators to Daily Dose Model Estimates.   International Journal of Environmental Research and Public Health. Molecular Diversity Preservation International, Basel,  SWITZERLAND, 14(1): 1-15, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-dz0p-627",
            "keyword": [
                "average daily dose",
                "cumulative risk assessment",
                "Susceptibility",
                "Vulnerability"
            ],
            "contactPoint": {
                "fn": "Timothy Barzyk",
                "hasEmail": "mailto:barzyk.timothy@epa.gov"
            },
            "distribution": [
                {
                    "title": "ADD Dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/627/ADD%20Dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-11-16",
            "references": [
                "https://doi.org/10.3390/ijerph14010024"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/627/documents/Data%20dictionary%20for%20ADD%20dataset.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Field-based methods for evaluating the annual maximum specific conductivity tolerated by freshwater invertebrates",
            "description": "Data includes chemical and biological samples from Ecoregion 69 in West Virginia. eco69_dupchem.csv:  1. Station-year with at least 6 conductivity samples, one in the spring and one in the summer. bio.sample69.csv: Final Criteria dataset for ecoregion 69 by excluding: 1. Non-biology samples, 2. Removed no-conductivity record; 4. removed pH <=6 samples; 5. removed high Cl sites (SO4+HCO3 < CL).  ss.csv: Source:WVDEP Crosstabed genus X sample matrix for Ecoregion 69 and 70. 1. Remove ambiguous taxa; 2. Remove non-reference taxa in these two ecoregions in WV data set. \n\nThis dataset is associated with the following publication:\nCormier, S., C. Flaherty, and L. Zheng. Field-based method for evaluating the annual maximum specific conductivity tolerated by freshwater invertebrates.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 633: 1637-1646, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1371704",
            "keyword": [
                "benthic macroinvertebrate",
                "conductivity",
                "criterion maximum"
            ],
            "contactPoint": {
                "fn": "Susan Cormier",
                "hasEmail": "mailto:cormier.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "CMEC Data sets.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371704/CMEC%20Data%20sets.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-01-10",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.01.136",
                "https://pasteur.epa.gov/uploads/10.23719/1371704/documents/Cond_DataFileColumnMetadata_20161221.xlsx"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1371704/documents/Cond_DataFileColumnMetadata_20161221.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data Set for: Step-by-Step Calculation and Spreadsheet Tools for Predicting Stressor Levels that Extirpate Genera and Species",
            "description": "The data includes measured data from Ecoregions 69 and 70 in West Virginia.  Paired biological and chemical grab samples are included.  These data were used to estimate SC extirpation concentration  (XC95) for benthic invertebrate genera.  Also included are cumulative frequency distribution plots, scatter plots fitted with generalized additive models, and biogeographical maps of observations of each genus.\nThe metadata and full data set is available in Supplemental Appendices S4 and S5, respectively. The output of 176 XC95 values from Ecoregions 69 and 70 are provided in Supplemental Appendix S6. Supplemental Appendix S7 depicts the probability of observing a genus for discrete ranges of SC. Supplemental Appendix S8 depicts the proportion of occurrence of a genus for discrete ranges of SC. Supplemental Appendix S9 shows the biogeographic distributions of the genera included in the data set. We also discuss limitations of this method to help avoid misinterpretations and inferential errors.  A data dictionary is provided in Cond_DataFileColumnMetada-20161221. \n\nThis dataset is associated with the following publication:\nCormier, S., L. Zheng, E. Leppo, and A. Hamilton. Step-by-Step Calculation and Spreadsheet Tools for Predicting Stressor Levels that Extirpate Genera and Species.   Integrated Environmental Assessment and Management. Allen Press, Inc., Lawrence, KS, USA, 14(2): 174-180, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1371705",
            "keyword": [
                "dissolved minerals",
                "conductivity",
                "Extirpation",
                "Excel tool"
            ],
            "contactPoint": {
                "fn": "Susan Cormier",
                "hasEmail": "mailto:cormier.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Appendix_S4-BEAT Metadata_69-70 20170112.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371705/Appendix_S4-BEAT%20Metadata_69-70%2020170112.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Cond_DataFileColumnMetadata_20161221.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371705/Cond_DataFileColumnMetadata_20161221.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Appendix_S5-BEAT Data_69-70 20170112.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371705/Appendix_S5-BEAT%20Data_69-70%2020170112.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "https://www.epa.gov/sites/production/files/2016-12/field-based-conductivity-field-data-sets.zip",
                    "accessURL": "https://www.epa.gov/sites/production/files/2016-12/field-based-conductivity-field-data-sets.zip"
                },
                {
                    "title": "Appendix_S6-BEAT XC95values_69-70 20170112.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371705/Appendix_S6-BEAT%20XC95values_69-70%2020170112.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Appendix_S7-BEAT GAMplots_69-70 20170112.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371705/Appendix_S7-BEAT%20GAMplots_69-70%2020170112.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Appendix_S8-BEAT CFDplots_69-70 20170112.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371705/Appendix_S8-BEAT%20CFDplots_69-70%2020170112.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Appendix_S9-BEAT Biogeographic_maps_69-70 20170112.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371705/Appendix_S9-BEAT%20Biogeographic_maps_69-70%2020170112.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-01-12",
            "references": [
                "https://doi.org/10.1002/ieam.1993"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1371705/documents/Cond_DataFileColumnMetadata_20161221.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Phthalate Intakes",
            "description": "Compilation of literature-reported intake values of phthalates; specifically dibutyl phthalate (DBP), bis(2-ethylhexyl) phthalate, and diisononyl phthalate (DiNP). \n\nThis dataset is associated with the following publication:\nMoreau, M., J. Leonard, K. Phillips, J. Campbell, S. Pendse, C. Nicolas, M. Phillips, M. Yoon, C. Tan, S. Smith, H. Pudukodu, K. Isaacs, and H. Clewell. Using exposure prediction tools to link exposure and dosimetry for risk-based decisions: A case study with phthalates.   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 184: 1194-1201, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1365652",
            "keyword": [
                "phthalate intakes",
                "Phthalates",
                "PBPK-reverse dosimetry"
            ],
            "contactPoint": {
                "fn": "Yu-Mei Tan",
                "hasEmail": "mailto:tan.cecilia@epa.gov"
            },
            "distribution": [
                {
                    "title": "phthalate_intakes.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1365652/phthalate_intakes.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-09",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2017.06.098"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Phthalate SHEDS-HT runs",
            "description": "Inputs and outputs for SHEDS-HT runs of DiNP, DEHP, DBP. \n\nThis dataset is associated with the following publication:\nMoreau, M., J. Leonard, K. Phillips, J. Campbell, S. Pendse, C. Nicolas, M. Phillips, M. Yoon, C. Tan, S. Smith, H. Pudukodu, K. Isaacs, and H. Clewell. Using exposure prediction tools to link exposure and dosimetry for risk-based decisions: A case study with phthalates.   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 184: 1194-1201, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1365653",
            "keyword": [
                "SHEDS-HT",
                "Phthalates",
                "PBPK-reverse dosimetry"
            ],
            "contactPoint": {
                "fn": "Yu-Mei Tan",
                "hasEmail": "mailto:tan.cecilia@epa.gov"
            },
            "distribution": [
                {
                    "title": "shedsht_phthalate_runs.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1365653/shedsht_phthalate_runs.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-11-08",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2017.06.098"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1365653/documents/SHEDSHT_TechManual_100116_input_and_output_files.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Soil processing method journal article supporting data",
            "description": "This study aimed to optimize a previously used indirect processing protocol, which included a series of washing and centrifugation steps. Optimization of the protocol included: identifying an ideal extraction diluent and evaluating variation in the number of wash steps, variation in the initial centrifugation speed, sonication and shaking mechanisms. The optimized protocol was demonstrated at two laboratories in order to evaluate the recovery of spores from loamy and sandy soils. Data supplied are statistical data and were used to help support conclusions and tables in the journal article. \n\nThis dataset is associated with the following publication:\nSilvestri, E., D. Feldhake, D. Griffin, J. Lisle, T. Nichols, S. Shah, A. Pemberton, and F. Schaefer. Optimization of a Sample Processing Protocol for Recovery of Bacillus anthracis Spores from Soil  [HS7.52.02 - 514].   JOURNAL OF MICROBIOLOGICAL METHODS. Elsevier Science Ltd, New York, NY, USA, 130: 6-13, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-08kq-184",
            "keyword": [
                "Bacillus anthracis",
                "spores",
                "sand",
                "loam",
                "soil",
                "indirect processing"
            ],
            "contactPoint": {
                "fn": "Erin Silvestri",
                "hasEmail": "mailto:silvestri.erin@epa.gov"
            },
            "distribution": [
                {
                    "title": "Table 1_Bacillus anthracis Sterne Spore Recoveries_metadata.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/184/Table%201_Bacillus%20anthracis%20Sterne%20Spore%20Recoveries_metadata.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Table 2_Average Spore Recovery for Mechanical Shaking versus Manual_metadata.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/184/Table%202_Average%20Spore%20Recovery%20for%20Mechanical%20Shaking%20versus%20Manual_metadata.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "ANNOVA comparison tables sandy and loamy soils.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/184/ANNOVA%20comparison%20tables%20sandy%20and%20loamy%20soils.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Laboratory Comparison Data 121815.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/184/Laboratory%20Comparison%20Data%20121815.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Percent Recovery Efficiency data with data dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/184/Percent%20Recovery%20Efficiency%20data%20with%20data%20dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Descriptive Statistics for raw and log10 data with data dictionary 121815.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/184/Descriptive%20Statistics%20for%20raw%20and%20log10%20data%20with%20data%20dictionary%20121815.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Data Back Log10 Transformed  and geometic means Summary Stats LV  SV.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/184/Data%20Back%20Log10%20Transformed%20%20and%20geometic%20means%20Summary%20Stats%20LV%20%20SV.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-15",
            "references": [
                "https://doi.org/10.1016/j.mimet.2016.08.013"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Strontium removal jar test dataset for all figures and tables.",
            "description": "The datasets where used to generate data to demonstrate strontium removal under various water quality and treatment conditions. \n\nThis dataset is associated with the following publication:\nO'Donnell, A.J., D. Lytle , S. Harmon , K. Vu, H. Chait, and D.D. Dionysiou. Removal of Strontium from Drinking Water by Conventional Treatment and Lime Softening.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 103: 319-333, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1371540",
            "keyword": [
                "Strontium",
                "drinking water",
                "coagulation",
                "Lime softening",
                "Jar Test"
            ],
            "contactPoint": {
                "fn": "Darren Lytle",
                "hasEmail": "mailto:lytle.darren@epa.gov"
            },
            "distribution": [
                {
                    "title": "Sr pilot paper.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371540/Sr%20pilot%20paper.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-20",
            "references": [
                "https://doi.org/10.1016/j.watres.2016.06.036"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Soot, organics, and ultrafine ash from air- and oxy-fired coal combustion",
            "description": "Pulverized bituminous coal was burned in a 10W externally heated entrained flow furnace under air-combustion and three oxy-combustion inlet oxygen conditions (28, 32, and 36%).  Experiments were designed to produce flames with practically relevant stoichiometric ratios (SR=1.2-1.4) and constant residence times (2.3s).  Size-classified fly ash samples were collected, and measurements focused on the soot, elemental carbon (EC), and organic carbon (OC) composition of the total and ultrafine (<0.6\u00b5m) fly ash.  Results indicate that although the total fly ash carbon, as measured by loss on ignition, was always acceptably low (<2%) with all three oxy-combustion conditions lower than air-combustion, the ultrafine fly ash for both air-fired and oxy-fired combustion conditions consists primarily of carbonaceous material (50-95%).  Carbonaceous components on particles <0.6\u00b5m measured by a thermal optical method showed that large fractions (52-93%) consisted of OC rather than EC, as expected.  This observation was supported by thermogravimetric analysis indicating that for the air, 28% oxy, and 32% oxy conditions, 14-71% of this material may be OC volatilizing between 100 and 550\u00b0C with the remaining 29-86% being EC/soot.  However, for the 36% oxy condition, OC may comprise over 90% of the ultrafine carbon with a much smaller EC/soot contribution.  These data were interpreted by considering the effects of oxy-combustion on flame attachment, ignition delay, and soot oxidation of a bituminous coal, and the effects of these processes on OC and EC emissions.  Flame aerodynamics and inlet oxidant composition may influence emissions of organic hazardous air pollutants (HAPs) from a bituminous coal.   During oxy-coal combustion, judicious control of inlet oxygen concentration and placement may be used to minimize organic HAP and soot emissions. \n\nThis dataset is associated with the following publication:\nAndersen, M., N. Modak, C. Winterrowd, C.W. Lee , W. Roberts, J. Wendt, and B. Linak. Soot, organics and ultrafine ash from air- and oxy-fired coal combustion.   Proceedings of the Combustion Institute. Elsevier B.V., Amsterdam,  NETHERLANDS, 36(3): 4029-4037, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1372478",
            "keyword": [
                "oxy-coal combustion",
                "ultrafine fly ash",
                "loss on ignition",
                "elemental carbon",
                "organic carbon"
            ],
            "contactPoint": {
                "fn": "William Linak",
                "hasEmail": "mailto:linak.bill@epa.gov"
            },
            "distribution": [
                {
                    "title": "Table 1 of 4.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372478/Table%201%20of%204.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Table 2 of 4.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372478/Table%202%20of%204.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Table 3 of 4.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372478/Table%203%20of%204.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Table 4 of 4.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372478/Table%204%20of%204.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Fig 1 of 3.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372478/Fig%201%20of%203.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Fig 2rev.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372478/Fig%202rev.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Fig 3_20160509_Possible_Edits.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372478/Fig%203_20160509_Possible_Edits.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-25",
            "references": [
                "https://doi.org/10.1016/j.proci.2016.08.073"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1372478/documents/Data%20Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Polycyclic aromatic hydrocarbon in fine particulate matter emitted from burning kerosene, liquid petroleum gas, and wood fuels in household cookstoves",
            "description": "This dataset includes all data in figures in the manuscript and supporting information for the publication entitled \"Particulate polycyclic aromatic hydrocarbon emissions from burning kerosene, liquid petroleum gas, and wood fuels in household cookstoves.\". \n\nThis dataset is associated with the following publication:\nShen, G., W. Preston, S. Ebersviller, C. Williams, J. Faircloth, J. Jetter, and M. Hays. Particulate polycyclic aromatic hydrocarbon emissions from burning kerosene, liquid petroleum gas, and wood fuels in household cookstoves.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 31(3): 3081-3090, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1372312",
            "keyword": [
                "particulate matter",
                "cookstove",
                "PAH",
                "emissions",
                "stove",
                "emission",
                "efficiency"
            ],
            "contactPoint": {
                "fn": "James Jetter",
                "hasEmail": "mailto:jetter.jim@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data in PAH cookstoves paper-10032016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372312/Data%20in%20PAH%20cookstoves%20paper-10032016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-04",
            "references": [
                "https://doi.org/10.1021/acs.energyfuels.6b02641"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Conversion of environmental estrone to estradiol by male fathead minnows",
            "description": "This data set describes experiments that were conducted to investigate whether exposure of male fathead minnows to environmentally-relevant estrone concentrations would result in elevated plasma 17\u03b2-estradiol concentrations in the fish. Secondly, we sought to establish whether observed elevations in plasma 17\u03b2-estradiol occurred as a result of the conversion of external estrone by the fish using an approach involving exposure of the fish to 13C-labeled estrone. Endpoints reported in the dataset include plasma 17\u03b2-estradiol and estrone concentrations, plasma vitellogenin concentrations, hepatic vitellogenin mRNA, 13C-labeled plasma 17\u03b2-estradiol and estrone concentrations, and testicular and/or hepatic expression of aromatase and several hydroxysteroid dehydrogenases involved in estrone metabolism. \n\nThis dataset is associated with the following publication:\nAnkley, G., D. Feifarek, B. Blackwell, J. Cavallin, K. Jensen, M. Kahl, S. Poole, E. Randolph, T. Saari, and D. Villeneuve. Reevaluating the significance of estrone as an environmental estrogen (article).   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51: 4705-4713, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1369435",
            "keyword": [
                "environmental estrogens",
                "estrone",
                "estradiol",
                "adverse outcome pathway",
                "endocrine disruption",
                "ecotoxicology",
                "aquatic ecosystems",
                "screening and prioritization"
            ],
            "contactPoint": {
                "fn": "Gerald Ankley",
                "hasEmail": "mailto:ankley.gerald@epa.gov"
            },
            "distribution": [
                {
                    "title": "AnkleyGerald_A-cjt8_Dataset Estrone.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1369435/AnkleyGerald_A-cjt8_Dataset%20Estrone.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-13",
            "references": [
                "https://doi.org/10.1021/acs.est.7b00606"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "First Generation Annotations for the Fathead Minnow (Pimephales promelas) Genome",
            "description": "The fathead minnow (Pimephales promelas) is a laboratory model organism widely used in regulatory toxicity testing and ecotoxicology research. Despite, the wealth of toxicological data for this organism, until recently genome scale information was lacking for the species, which limited the utility of the species for pathway-based toxicity testing and research. As part of a EPA Pathfinder Innovation Project, next generation sequencing was applied to generate a draft genome assembly, which was published in 2016. However, application of those genome-scale sequencing resources was still limited by the lack of available gene annotations for fathead minnow. Here we report on development of a first generation genome annotation for fathead minnow and the dissemination of that information through a web-based browser that makes it easy to search for genes of interest, extract the corresponding sequence, identify intron and exon boundaries and regulatory regions, and align the computationally predicted genes with other supporting evidence. This work greatly enhances the utility of the genome assemblies that were developed and makes it accessible to the ecotoxicology community world-wide, opening up a wide array of new research opportunities with the species. The URL associated with this data set provides access to the genome browser that was developed as well as the current gene models and evidence tracks. \n\nThis dataset is associated with the following publication:\nSaari, T., A. Schroeder, G. Ankley, and D. Villeneuve. First generation annotations for the fathead minnow (Pimephales promelas) genome.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 36(12): 3436-3442, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1369565",
            "keyword": [
                "genome",
                "pimephales promelas",
                "fish",
                "bioinformatics",
                "adverse outcome pathway",
                "ecotoxicology",
                "endocrine disruption",
                "screening and prioritization",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.setac.org/fhm-genome",
                    "accessURL": "https://www.setac.org/fhm-genome"
                }
            ],
            "modified": "2017-07-13",
            "references": [
                "https://doi.org/10.1002/etc.3929"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Temporary Vs. Permanent Sub-Slab Ports: A Comparative Performance Study ",
            "description": "Data Tables from Published Article. \n\nThis dataset is associated with the following publication:\nZimmerman, J., C. Lutes, B. Cosky, B. Schumacher, D. Salkie, and R. Truesdale. Temporary vs. Permanent Sub-slab Ports: A Comparative Performance Study.   SOIL AND SEDIMENT CONTAMINATION: AN INTERNATIONAL JOURNAL. CRC Press LLC, Boca Raton, FL, USA, 26(3): 294-307, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-w9h6-366",
            "keyword": [
                "sub-slab port",
                "vapor intrusion",
                "PCE",
                "TCE",
                "volatile organic compounds"
            ],
            "contactPoint": {
                "fn": "John Zimmerman",
                "hasEmail": "mailto:zimmerman.johnh@epa.gov"
            },
            "distribution": [
                {
                    "title": "Zimmerman_A_w9h6_Dataset_20160921.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/366/Zimmerman_A_w9h6_Dataset_20160921.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-21",
            "references": [
                "https://doi.org/10.1080/15320383.2017.1298565"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Respiratory Effects and Systemic Stress Response Following Acute Acrolein Inhalation in Rats",
            "description": "This data set is an Excel file pertaining to the study that examined nasal, pulmonary, and systemic effects of acrolein in rats acutely exposed to a range of concentrations.  The different tabs of the spreadsheet pertain to each figure found in the manuscript. \n\nThis dataset is associated with the following publication:\nSnow, S., M. McGee, A. Henriquez, J. Richards, M. Schladweiler, A. Ledbetter, and U. Kodavanti. Respiratory Effects and Systemic Stress Response Following Acute Acrolein Inhalation in Rats#.   TOXICOLOGICAL SCIENCES. Society of Toxicology,    158(2): 454-464, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1369397",
            "keyword": [
                "acrolein",
                "Stress Response",
                "neuroendocrine",
                "nasal injury",
                "pulmonary injury"
            ],
            "contactPoint": {
                "fn": "Samantha Snow",
                "hasEmail": "mailto:snow.samantha@epa.gov"
            },
            "distribution": [
                {
                    "title": "GKAcrolein Manuscript - Data for ScienceHub - SnowKodavanti.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1369397/GKAcrolein%20Manuscript%20-%20Data%20for%20ScienceHub%20-%20SnowKodavanti.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-05-24",
            "references": [
                "https://doi.org/10.1093/toxsci/kfx108"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Evidence of sulfate-dependent anaerobic methane oxidation... Wolfe & Wilkin data table vers 1",
            "description": "Data file (.csv) including data plotted in manuscript figures: methane and sulfate concentrations, and stable isotope data for carbon, hydrogen, sulfur, and oxygen. \n\nThis dataset is associated with the following publication:\nWolfe, A., and R. Wilkin. Evidence of sulfate-dependent anaerobic methane oxidation within an area impacted by coalbed methane-related gas migration.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51: 1901-1909, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1373358",
            "keyword": [
                "Methane",
                "groundwater",
                "anaerobic methane oxidation",
                "coalbed methane",
                "gas migration",
                "hydraulic fracturing",
                "Raton Basin"
            ],
            "contactPoint": {
                "fn": "Richard Wilkin",
                "hasEmail": "mailto:wilkin.rick@epa.gov"
            },
            "distribution": [
                {
                    "title": "Evidence of sulfate-dependent anaerobic methane oxidation within an area impacted by coalbed methane... - Wolfe & Wilkin ES&T 2017 v51 p1901.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1373358/Evidence%20of%20sulfate-dependent%20anaerobic%20methane%20oxidation%20within%20an%20area%20impacted%20by%20coalbed%20methane...%20-%20Wolfe%20%26%20Wilkin%20ES%26T%202017%20v51%20p1901.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-07-31",
            "references": [
                "https://doi.org/10.1021/acs.est.6b03709"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "ScienceHub data set for \"Detection of semi-volatile organic compounds in permeable pavement infiltrate\"",
            "description": "Observed permeable pavement infiltrate concentrations by  EPA (1996) method 8270C Semivolatile Organic Compounds by Gas Chromatography/Mass Spectrometry (GC/MS) with selected ion monitoring (SIM). \n\nThis dataset is associated with the following publication:\nOConnor , T. Detection of semi-volatile organic compounds in permeable pavement infiltrate.   JOURNAL OF ENVIRONMENTAL ENGINEERING. American Society of Civil Engineers  (ASCE), Reston, VA, USA, 3(2): 999-999, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1372637",
            "keyword": [
                "semi-volatile organic compound",
                "permeable pavement",
                "infiltrate",
                "Green Infrastructure"
            ],
            "contactPoint": {
                "fn": "Thomas Oconnor",
                "hasEmail": "mailto:oconnor.thomas@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHubdata.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372637/ScienceHubdata.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-07",
            "references": [
                "https://doi.org/10.1061/jswbay.0000822"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for: A field-based model of the relationship between extirpation of salt-intolerant benthic invertebrates and background conductivity",
            "description": "The data is provided in 2 zip files that share site identifiers. One data set contains biological (genus benthic invertebrate) data (Data Biological.zip) and the other contains water quality data (Data Environmental.zip), in particular specific conductivity that were used for analyses. A third zip file( XC95_20161120B-C model.zip) contains the XC95 for each genus for each stage data set in Column F of the .csv files.  Other columns contain effect specific conductivity effect levels determined by other analytical methods such as from generalized additive models (GAM), linear regression models (LRM) or a weighted optimum (WAopt). Column T (Trend) indicates if the XC95 is confident (+), approximate (~), or greater (>) than the XC95.  The pdf files provide plots of either the cumulative frequency distribution or the generalized additive models for each genus in each state data set. \n\nThis dataset is associated with the following publication:\nCormier, S., L. Zheng, and C. Flaherty. A field-based model of the relationship between extirpation of salt-intolerant benthic invertebrates and background conductivity.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 633: 1629-1636, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1371707",
            "keyword": [
                "conductivity",
                "total dissolved solids",
                "water quality",
                "Extirpation",
                "background",
                "streams",
                "benthic macroinvertebrate"
            ],
            "contactPoint": {
                "fn": "Susan Cormier",
                "hasEmail": "mailto:cormier.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data Biological.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371707/Data%20Biological.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Data Environmental.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371707/Data%20Environmental.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "XC95_20161120 B-C model.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371707/XC95_20161120%20B-C%20model.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-11-20",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.02.044"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1371707/documents/DataDictionaryCond_DataFileColumnMetadata_20161221.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for: Estimation of field-based benchmarks from a background specific conductivity",
            "description": "There are 3 data sets.  Two zip files contain paired biological (benthic macroinvertebrate genera) (Data Biological.zip)  and water quality data (Data Environmental.zip).  These were used to estimate background specific conductivity from these state data and estimate the HC05 using the field based extirpation concentration method (USEPA 2011).  \nThe zipped files (Griffith ion MG20150729) contains two csv miles with ions summaries and ion and specific conductivity data from the combined EPA survey data. \n\nThis dataset is associated with the following publication:\nCormier, S., L. Zheng, R. Novak, and C. Flaherty. A flow-chart for developing water quality criteria from two field-based methods.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 633: 1647-1656, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1371706",
            "keyword": [
                "benthic macroinvertebrate",
                "stream",
                "Specific Conductivity",
                "total dissolved solids",
                "water quality criteria",
                "field-based method",
                "background conductivity"
            ],
            "contactPoint": {
                "fn": "Susan Cormier",
                "hasEmail": "mailto:cormier.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Griffith ion_MG20150729.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371706/Griffith%20ion_MG20150729.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Data Biological.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371706/Data%20Biological.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Data Environmental.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371706/Data%20Environmental.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-11-20",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.01.137"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1371706/documents/DataDictionaryCond_DataFileColumnMetadata_20161221.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CMAQv5.1 with new dust IMPROVE site compare files",
            "description": "CMAQv5.1 with a new dust module IMPROVE sitex files containing 24-hr (every 3rd day) paired model/ob data for the IMPROVE network. \n\nThis dataset is associated with the following publication:\nForoutan, H., J. Young, S. Napelenok, L. Ran, W. Appel, R. Gilliam, and J. Pleim. Development and evaluation of a physics-based windblown dust emission scheme implemented in the CMAQ modeling system.   Journal of Advances in Modeling Earth Systems. John Wiley & Sons, Inc., Hoboken, NJ, USA, 9(1): 585-608, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1373103",
            "keyword": [
                "CMAQ",
                "Windblown Dust",
                "emission parametrization",
                "surface roughness"
            ],
            "contactPoint": {
                "fn": "Hosein Foroutan",
                "hasEmail": "mailto:foroutan.hosein@epa.gov"
            },
            "distribution": [
                {
                    "title": "IMPROVE_CMAQv51_NewDust.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1373103/IMPROVE_CMAQv51_NewDust.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-07-12",
            "references": [
                "https://doi.org/10.1002/2016ms000823"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1373103/documents/ForoutanHosein_A-83bv_Data_Dictionary_20170712.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Soil organic matter and amphibian exposure dataset.",
            "description": "Dermal uptake from soil is known to occur in amphibians, but predicting pesticide availability and bioconcentration across soil types is not well understood. The present study was designed to compare uptake of 5 current-use pesticides (imidacloprid, atrazine, triadimefon, fipronil, and pendimethalin) in American toads (Bufo americanus) from exposure on soils with significant organic matter content differences (14.1%\u2009=\u2009high organic matter and 3.1%\u2009=\u2009low organic matter). We placed toads on high- or low-organic matter soil after applying individual current-use pesticides on the soil surface for an 8-h exposure duration. Whole body tissue homogenates and soils were extracted and analyzed using liquid chromatography\u2013mass spectrometry to determine pesticide tissue and soil concentration, as well as bioconcentration factor in toads. Tissue concentrations were greater on the low-organic matter soil than the high-organic matter soil across all pesticides (average\u2009\u00b1\u2009standard error; 1.23\u2009\u00b1\u20090.35\u2009ppm and 0.78\u2009\u00b1\u20090.23\u2009ppm, respectively), and bioconcentration was significantly higher for toads on the low-organic matter soil (analysis of covariance p\u2009=\u20090.002). Soil organic matter is known to play a significant role in the mobility of pesticides and bioavailability to living organisms. Agricultural soils typically have relatively lower organic matter content and serve as a functional habitat for amphibians. The potential for pesticide accumulation in amphibians moving throughout agricultural landscapes may be greater and should be considered in conservation and policy efforts. This dataset is associated with the following publication:\nVanMeter, R., D. Glinski, T. Hong, M. Cyterski , M. Henderson , and T. Purucker. Estimating terrestrial amphibian pesticide body burden through dermal exposure.   ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 193: 262-268, (2014). NOTE: This dataset has been removed from public access due to revocation. Please refer inquiries regarding this dataset to the listed contact person.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1373748",
            "keyword": [
                "amphibians",
                "dermal exposure",
                "soil organic matter",
                "pesticides"
            ],
            "contactPoint": {
                "fn": "Steven Purucker",
                "hasEmail": "mailto:purucker.tom@epa.gov"
            },
            "distribution": [],
            "modified": "2017-07-06",
            "references": null,
            "publisher": {
                "name": "U.S. Environmental Protection Agency",
                "subOrganizationOf": {
                    "name": "U.S. Government"
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "amphibian_biomarker_data",
            "description": "Amphibian metabolite data used in Snyder, M.N., Henderson, W.M., Glinski, D.G., Purucker, S. T., 2017. Biomarker analysis of american toad (Anaxyrus americanus) and grey tree frog (Hyla versicolor) tadpoles following exposure to atrazine. Aquatic Toxicology, 182(184-193). doi: 10.1016/j.aquatox.2016.11.018. \n\nThis dataset is associated with the following publication:\nSnyder, M., M. Henderson, D. Glinski, and T. Purucker. Biomarker analysis of American toad (Anaxyrus americanus) and grey tree frog (Hyla versicolor) tadpoles following exposure to atrazine..   AQUATIC TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 182: 184-193, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1373743",
            "keyword": [
                "biomarkers",
                "amphibians",
                "pesticides",
                "Support vector machines",
                "Metabolites"
            ],
            "contactPoint": {
                "fn": "Steven Purucker",
                "hasEmail": "mailto:purucker.tom@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://github.com/puruckertom/snyderetal_2017_amphibian_biomarker_analysis/tree/master/data_in",
                    "accessURL": "https://github.com/puruckertom/snyderetal_2017_amphibian_biomarker_analysis/tree/master/data_in"
                }
            ],
            "modified": "2017-05-05",
            "references": [
                "https://doi.org/10.1016/j.aquatox.2016.11.018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Nationwide reconnaissance of contaminants of emerging concern in source and treated drinking waters of the Unites States: Pharmaceuticals",
            "description": "Data from pharmaceutical paper. \n\nThis dataset is associated with the following publication:\nFurlong, E., A. Batt, S. Glassmeyer, M. Noriega, D. Kolpin, H. Mash, and K. Schenck. Nationwide reconnaissance of contaminants of emerging concern in source and treated drinking waters of the United States: Pharmaceuticals.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 579: 1629\u20131642, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-cjt7-271",
            "keyword": [
                "drinking water",
                "source water",
                "pharmaceuticals",
                "microorganisms",
                "Per- and polyfluoroalkyl substances"
            ],
            "contactPoint": {
                "fn": "Susan Glassmeyer",
                "hasEmail": "mailto:glassmeyer.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Furlong_Pharm MS_Tables_for BAO Approval.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/271/Furlong_Pharm%20MS_Tables_for%20BAO%20Approval.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "DWTP Paper_Data Supporting Figures.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/271/DWTP%20Paper_Data%20Supporting%20Figures.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "DWTP Paper_Data Supporting Tables.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/271/DWTP%20Paper_Data%20Supporting%20Tables.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-05",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.03.128"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The importance of quality control in validating concentration of contaminants of emerging concern in source and treated drinking water samples.",
            "description": "Overview of the quality assurance and quality control that supports the data analysis across all papers. \n\nThis dataset is associated with the following publication:\nBatt , A., E. Furlong, H. Mash , S. Glassmeyer , and D. Kolpin. The importance of quality control in validating concentrations of contaminants of emerging concern in source and treated drinking water samples..   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 579: 1618-1628, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-cjt7-273",
            "keyword": [
                "mass spectrometry",
                "drinking water",
                "source water",
                "pharmaceuticals",
                "microorganisms",
                "Per- and polyfluoroalkyl substances"
            ],
            "contactPoint": {
                "fn": "Susan Glassmeyer",
                "hasEmail": "mailto:glassmeyer.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Copy of PhaseII-Method-comparison-SCHIHUB.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/273/Copy%20of%20PhaseII-Method-comparison-SCHIHUB.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-05",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.02.127"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Comparison of In Vitro Estrogenic Activity and Estrogen Concentrations in Source and Treated Waters from 25 Drinking Water Treatment Plants.",
            "description": "Compares results of bioassay with hormones measured using analytical chemistry. \n\nThis dataset is associated with the following publication:\nConley, J., H. Mash , N. Evans , K. Schenck , L. Rosenblum, S. Glassmeyer , E.T. Furlong, D.W. Kolpin, and V. Wilson. Comparison of in vitro estrogenic activity and estrogen concentrations in source and treated waters from 25 U.S. drinking water treatment plants.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS,  N/A, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "A-cjt7-274",
            "keyword": [
                "effect-based monitoring",
                "In vitro bioassay",
                "estrogen",
                "water quality",
                "T47D-KBluc",
                "drinking water",
                "source water",
                "pharmaceuticals",
                "microorganisms",
                "Per- and polyfluoroalkyl substances"
            ],
            "contactPoint": {
                "fn": "Susan Glassmeyer",
                "hasEmail": "mailto:glassmeyer.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Conley_2016_ScienceHub_data_file.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/274/Conley_2016_ScienceHub_data_file.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-05",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.02.093"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CMAQv5.1 with new dust AQS Hourly site compare files",
            "description": "CMAQv5.1 with a new dust module AQS Hourly sitex files containing hourly paired model/ob data for the AQS network. \n\nThis dataset is associated with the following publication:\nForoutan, H., J. Young, S. Napelenok, L. Ran, W. Appel, R. Gilliam, and J. Pleim. Development and evaluation of a physics-based windblown dust emission scheme implemented in the CMAQ modeling system.   Journal of Advances in Modeling Earth Systems. John Wiley & Sons, Inc., Hoboken, NJ, USA, 9(1): 585-608, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1373104",
            "keyword": [
                "CMAQ",
                "Windblown Dust",
                "emission parametrization",
                "surface roughness"
            ],
            "contactPoint": {
                "fn": "Hosein Foroutan",
                "hasEmail": "mailto:foroutan.hosein@epa.gov"
            },
            "distribution": [
                {
                    "title": "AQS_Hourly_CMAQv51_NewDust.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1373104/AQS_Hourly_CMAQv51_NewDust.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-07-12",
            "references": [
                "https://doi.org/10.1002/2016ms000823"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1373104/documents/ForoutanHosein_A-83bv_Data_Dictionary_20170712.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Riparian proper functioning condition assessment to improve watershed management for water quality",
            "description": "No data. This dataset is not publicly accessible because: No data. It can be accessed through the following means: No data. Format: No data. \n\nThis dataset is associated with the following publication:\nSwanson, S., D. Kozlowski, R. Hall , D. Heggem , and J. Lin. Riparian Proper Functioning Condition (PFC) Assessment to Improve Water Quality.   JOURNAL OF ENVIRONMENTAL QUALITY. American Society of Agronomy, MADISON, WI, USA, 72(2): 168-172, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "A-4j13-634",
            "keyword": [
                "water quality",
                "Tribal Sustainability",
                "proper functioning condition",
                "ecological condition assessment",
                "Environmenal health",
                "Ecological Health",
                "Vulnerable Groups"
            ],
            "contactPoint": {
                "fn": "Daniel Heggem",
                "hasEmail": "mailto:heggem.daniel@epa.gov"
            },
            "distribution": [],
            "modified": "2017-05-22",
            "references": [
                "https://doi.org/10.2489/jswc.72.2.168"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "In vitro screening of metal oxide nanoparticles for effects on neural function using cortical networks",
            "description": "Data describe the effects of metal oxide nanoparticles on total spikes and active electrodes after exposure to various concentrations for 1, 24 and 48 hrs, or after treatment with bicuculline. This dataset is not publicly accessible because: Each raw file contains at least 1 hour of recording time and is approximately 50 GB or larger. They cannot be uploaded due to file size. It can be accessed through the following means: Raw files are analyzed using scripts written in R-programming language and outputs from R included the graphs used in the publication. Summaries of the data, R-scripts and summary outputs from the R-analysis are located at the following locations: L:\\Lab\\NHEERL_MEA\\Crooks\\MEA_MetalOxides\r\n          This directory and its sub-directory contains over 30 output files from the R-script analysis including xcell files summarizing the parameters of different statistical models and visualizations of the data in the form of tiff files.\r\nL:\\Lab\\NHEERL_MEA\\nanoparticles\\Crooks MEA\\final analysis\r\n     This directory and its sub-directories include R-scripts used for analysis as well as folders with R-outputs summarizing statistics for different Fixed-dose trend, fixed interaction and fixed square root models used for analysis. There are over 50 files in this directory. Format: Raw data are derived from Axion Biosystems Maestro system using Axis 1.9 or later software. Data are saved as \"*.raw\" in a proprietary format on DROBO devices in the Shafer lab. The DROBO devices consist of five 2TB or larger hard drives and allows for self backing of files. Files are stored in folders based on the date the cell culture used for a particular experiment was made, and in subfolders for each experiment date for that culture. \n\nThis dataset is associated with the following publication:\nStrickland, J., W. Lefew , J. Crooks , D. Hall, J. Ortenzio, K. Dreher , and T. Shafer. In vitro screening of metal oxide nanoparticles for effects on neural function using cortical networks on microelectrode arrays.   Journal of Nanotoxicology. Taylor and Francis, Philadelphia, PA, USA, 10(5): 619-28, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-xppm-398",
            "keyword": [
                "Nanoparticles",
                "screening",
                "neurotoxicity",
                "Microelectrode array"
            ],
            "contactPoint": {
                "fn": "Timothy Shafer",
                "hasEmail": "mailto:shafer.tim@epa.gov"
            },
            "distribution": [],
            "modified": "2013-05-31",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "No data",
            "description": "Manuscript provides a look-up table to predict exposures from minimal information using ECETOC TRA software. This dataset is not publicly accessible because: There is no EPA-generated data. It can be accessed through the following means: Rosemarie Zaleski of ExxonMobile Biosciences created \"look-up table\" using freely available ECETOC TRA software *http://www.ecetoc.org/tools/targeted-risk-assessment-tra/download-integrated-tool/). Format: There is no EPA-generated data. \n\nThis dataset is associated with the following publication:\nDellarco, M., R. Zaleski , B. Gaborek , H. Qian, C. Bellin , P. Egeghy, N. Heard , O. Jolliet, D. Lander, N. Sunger , K. Stylianou  , and J. Tanir. Using exposure bands for rapid decision making in the RISK21 tiered exposureassessment.   CRITICAL REVIEWS IN TOXICOLOGY. CRC Press LLC, Boca Raton, FL, USA,  online, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-jm6m-594",
            "keyword": [
                "Exposure banding",
                "Exposure Assessment",
                "Risk Assessment",
                "high throughput",
                "RISK21",
                "screening",
                "ExpoCast"
            ],
            "contactPoint": {
                "fn": "Peter Egeghy",
                "hasEmail": "mailto:egeghy.peter@epa.gov"
            },
            "distribution": [],
            "modified": "2016-04-22",
            "references": [
                "https://doi.org/10.1080/10408444.2016.1270255"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "WRF Model Output",
            "description": "This dataset contains WRF model output.  There are three months of data: July 2012, July 2013, and January 2013.  For each month, several simulations were made: A control and two lightning assimilation runs using different suppression techniques.  For July 2012, and additional simulation was made with a third suppression technique.  Please refer to the manuscript for a full description of each simulation. This dataset is not publicly accessible because: The files are too large. It can be accessed through the following means: The data can be accessed through NCC's tape archival storage system (ASM) or by contacting the author. Format: WRF model output for July 2012, July 2013, and January 2013. \n\nThis dataset is associated with the following publication:\nHeath, N., J. Pleim, R. Gilliam, and D. Kang. A simple lightning assimilation technique for improving retrospective WRF simulations..   Journal of Advances in Modeling Earth Systems. John Wiley & Sons, Inc., Hoboken, NJ, USA, 8(4): 1806-1824, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1374152",
            "keyword": [
                "Lightning",
                "data assimilation",
                "WRF",
                "deep convection"
            ],
            "contactPoint": {
                "fn": "Nicholas Heath",
                "hasEmail": "mailto:heath.nicholas@epa.gov"
            },
            "distribution": [],
            "modified": "2017-02-09",
            "references": [
                "https://doi.org/10.1002/2016ms000735"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "PDP data download from https://www.ams.usda.gov/datasets/pdp",
            "description": "The Pesticide Data Program (PDP) is a national pesticide residue monitoring program and produces the most comprehensive pesticide residue database in the U.S. The Monitoring Programs Division administers PDP activities, including the sampling, testing, and reporting of pesticide residues on agricultural commodities in the U.S. food supply, with an emphasis on those commodities highly consumed by infants and children. The program is implemented through cooperation with State agriculture departments and other Federal agencies. PDP data. \n\nThis dataset is associated with the following publication:\nMelnyk , L., Z. Wang, Z. Li, and J. Xue. Prioritization of pesticides based on daily dietary exposure potential as determined from the SHEDS model.   FOOD AND CHEMICAL TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 96: 167-173, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1374555",
            "keyword": [
                "pesticides",
                "risk ranking",
                "dietary exposure",
                "adi"
            ],
            "contactPoint": {
                "fn": "Lisa Melnyk",
                "hasEmail": "mailto:melnyk.lisa@epa.gov"
            },
            "distribution": [
                {
                    "title": "pdpRankData.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374555/pdpRankData.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-02-21",
            "references": [
                "https://doi.org/10.1016/j.fct.2016.07.025"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Mutagenicity in Salmonella of Biodiesel Fractions",
            "description": "A description is included with the data. \n\nThis dataset is associated with the following publication:\nMutlu, E., S. Warren , P. Matthews, J. Schmid , I. Kooter, B. Linak , I. Gilmour , and D. DeMarini. Health Effects of Soy-Biodiesel Emissions: Bioassay-Directed Fractionation for Mutagenicity*.   INHALATION TOXICOLOGY. Informa Healthcare USA, New York, NY, USA, 27(11): 597-612, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-47dc-441",
            "keyword": [
                "Mutagenicity",
                "Salmonella",
                "bioassay-directed fractionation",
                "Complex Mixtures",
                "Diesel Exhaust",
                "Mutagenesis",
                "PAHs"
            ],
            "contactPoint": {
                "fn": "David Demarini",
                "hasEmail": "mailto:demarini.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science Hub Biodiesel Fractions Raw Mutagenicity Data 7-23-14.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/441/Science%20Hub%20Biodiesel%20Fractions%20Raw%20Mutagenicity%20Data%207-23-14.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2016-02-12",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Mutagenicity of Cookstove Emissions",
            "description": "Description is included with the dataset. \n\nThis dataset is associated with the following publication:\nMutlu, E., S. Warren , S. Ebersviller , I. Kooter, J. Schmid , J. Dye , B. Linak , I. Gilmour , J. Jetter , M. Higuchi , and D. DeMarini. Mutagenicity- and Pollutant-Emission Factors of\r\nSolid-Fuel Cookstoves: Comparison to Other\r\nCombustion Sources.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 124: 974-982, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "A-bzks-442",
            "keyword": [
                "Mutagenicity",
                "Salmonella",
                "cookstoves",
                "Complex Mixtures",
                "Combustion Emissions"
            ],
            "contactPoint": {
                "fn": "David Demarini",
                "hasEmail": "mailto:demarini.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science Hub Cookstove Data Set.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/442/Science%20Hub%20Cookstove%20Data%20Set.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-07-01",
            "references": [
                "https://doi.org/10.1289/ehp.1509852"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Mutagenicity of Swimming Pool and Hot Tub Water",
            "description": "Description is included in the dataset. \n\nThis dataset is associated with the following publication:\nDaiber, E., D. DeMarini , S. Ravuri, H. Liberatore, A. Cuthbertson, A. Thompson-Klemish, J. Byer, J. Schmid , M. Afifi, E. Blatchley, and S. Richardson. Progressive Increase in Disinfection Byproducts and Mutagenicity from Sourceto Tap to Swimming Pool and Spa Water:  Implications for Public Health.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(13): 6652-6662, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-j6qk-443",
            "keyword": [
                "Mutagenicity",
                "swimming pool",
                "hot tub",
                "spa",
                "disinfection byproducts"
            ],
            "contactPoint": {
                "fn": "David Demarini",
                "hasEmail": "mailto:demarini.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science Hub Pool ES&T Data Set.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/443/Science%20Hub%20Pool%20ES%26T%20Data%20Set.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-07-13",
            "references": [
                "https://doi.org/10.1021/acs.est.6b00808"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Hydrolysis Rate Data and Activation Energy Values (Supporting Information for doi 10.1021/acs.est.6b05412)",
            "description": "This dataset consists of rate constants, half-lives and activation energy values for hydrolysis of organic chemicals compiled from journal publications and regulatory reports.  The dataset was used to develop a ranked library of transformation reaction schemes for abiotic hydrolysis of organic chemicals under environmentally relevant conditions.  The spreadsheet file HydrolysisRateConstants_est6b05412.xlsx contains a compilation of 187 literature-reported hydrolysis half-lives adjusted to pH 5, 7 and 9 and temperature of 25\u00b0C.  The spreadsheet file HydrolysisActivationEnergy_est6b05412.xlsx contains a compilation of 58 literature-reported activation energies for hydrolysis reaction schemes. \n\nThis dataset is associated with the following publication:\nStevens, C., J. Patel, J. Jones, and E. Weber. Prediction of Hydrolysis Products of Organic Chemicals under Environmental pH Conditions.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(9): 5008\u20135016, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "A-4b8n-630",
            "keyword": [
                "hydrolysis",
                "transformations",
                "predictive models",
                "cheminformatics",
                "reaction library"
            ],
            "contactPoint": {
                "fn": "Caroline Stevens",
                "hasEmail": "mailto:stevens.caroline@epa.gov"
            },
            "distribution": [
                {
                    "title": "HydrolysisActivationEnergy_est6b05412.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/630/HydrolysisActivationEnergy_est6b05412.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "HydrolysisRateConstants_est6b05412.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/630/HydrolysisRateConstants_est6b05412.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-07-13",
            "references": [
                "https://doi.org/10.1021/acs.est.6b05412"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Experimental data sulfate and metal removal from mining impacted water collected at the Formosa Mine, OR, and sulfur speciation in the obtained solid residues.  ",
            "description": "The data set contains the elemental composition, pH, and sulfate content of the utilized mining impacted water used as influent in the columns study, the data for pH, Eh, Cd, Fe, Mn, Zn, sulfate and sulfate removal rate in the columns, and the data for an example XPS spectrum of sulfur from one of the collected solid residues from the bioactive column. \n\nThis dataset is associated with the following publication:\nAl-Abed, S., P. Pinto, J. McKernan, E. Feld-Cook, and S. Lomnicki. Mechanisms and Effectivity of Sulfate Reducing Bioreactors using a Chitinous Substrate in Treating Mining Influenced Water.  S.J. Allen, D. Dionysiou, G.B. Martin, J. Santamaria, K.L. Yeung, T. Aminabhavi, K. Chandran, and S.G. Pavlostathis  Chemical Engineering Journal. Elsevier BV, AMSTERDAM,  NETHERLANDS, 323: 270-277, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1374183",
            "keyword": [
                "passive remediation. sulfide",
                "acid mine drainage",
                "anaerobic biochemical reactors"
            ],
            "contactPoint": {
                "fn": "Souhail Al-Abed",
                "hasEmail": "mailto:al-abed.souhail@epa.gov"
            },
            "distribution": [
                {
                    "title": "meta deta set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374183/meta%20deta%20set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2012-07-23",
            "references": [
                "https://doi.org/10.1016/j.cej.2017.04.045"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1374183/documents/data%20dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Wilkin and Beak (2017) ChemGeol v462 p15",
            "description": "The dataset includes X-ray Diffraction, Raman spectroscopic, X-ray absorption spectroscopic, and aqueous data pertaining to the paper titled \"Uptake of nickel by synthetic mackinawite\" published in Chemical Geology (2017, volume 462, pages 15-29. \n\nThis dataset is associated with the following publication:\nWilkin, R., and D. Beak. Uptake of Nickel by Synthetic Mackinawite.   CHEMICAL GEOLOGY. Elsevier Science Ltd, New York, NY, USA, 462: 15-29, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1374560",
            "keyword": [
                "groundwater",
                "chromium",
                "arsenic",
                "nickel",
                "iron sulfides",
                "uranium"
            ],
            "contactPoint": {
                "fn": "Richard Wilkin",
                "hasEmail": "mailto:wilkin.rick@epa.gov"
            },
            "distribution": [
                {
                    "title": "Wilkin and Beak (2017) ChemGeol v462 p15.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374560/Wilkin%20and%20Beak%20%282017%29%20ChemGeol%20v462%20p15.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-08-10",
            "references": [
                "https://doi.org/10.1016/j.chemgeo.2017.04.023"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking water sources",
            "description": "This dataset shows the concentration of cyanobacteria cells/ml in fresh water bodies and estuaries of the Ohio and Florida derived from 300x300 meter MEdium Resolution Imaging Spectrometer (MERIS) satellite imagery. This dataset was produced through partnership with the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), the United States Geological Survey (USGS), and the United States Environmental Protection Agency (USEPA). This cyanobacteria dataset was derived using the European Space Agency (ESA) Envisat satellite and MERIS instrument. MERIS is a 68.5 degree field-of-view nadir-pointing imaging spectrometer which measures the solar radiation reflected by the Earth in 15 spectral bands (visible and near-infrared). MERIS imagery was used to identify long-wavelength spectral bands (from red through near-infrared portion of the spectrum) to locate algal blooms within freshwaters and estuaries of the continental United States. This dataset is not publicly accessible because: The dataset describing locations of surface drinking water intakes was obtained through Office of Water's Office of Ground Water and Drinking Water. This dataset is not publicly available for security reasons. While location data were used in our analysis, no intake locations were revealed and data were handled according to security specifications provided by OW. This dataset will therefore not be made available to the public through ScienceHub or any other outlet. It can be accessed through the following means: Contact corresponding author for additional information. Format: Assessing temporal frequency of cyanobacterial blooms at drinking water intakes using imagery from the Sentinel-3A satellite sensor. \n\nThis dataset is associated with the following publication:\nClark, J., B. Schaeffer, J. Darling, E. Urquhart, J. Johnston, A. Ignatius, M. Myer, K. Loftin, J. Werdell, and R. Stumpf. Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking water sources.   ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 80: 84-95, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1366973",
            "keyword": [
                "cyanobacteria index",
                "MERIS",
                "cyanobacteria",
                "drinking water",
                "recreational water",
                "satellite",
                "public water systems",
                "Harmful Algal Blooms"
            ],
            "contactPoint": {
                "fn": "Blake Schaeffer",
                "hasEmail": "mailto:schaeffer.blake@epa.gov"
            },
            "distribution": [],
            "modified": "2017-06-13",
            "references": [
                "https://doi.org/10.1016/j.ecolind.2017.04.046",
                "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6145495"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A case study on the use of exposure-activity ratios (EARs) to prioritize sites, chemicals, and bioactivities of concern in Great Lakes waters",
            "description": "As a case study, chemical occurrence data from a 2012 study in the Great Lakes Basin along with the ToxCast\u2122 effects database were used to calculate exposure-activity ratios (EARs) as a prioritization tool. Technical considerations of data processing and use of the ToxCast\u2122 database are presented and discussed. EAR prioritization identified multiple sites, biological pathways, and chemicals that warrant further investigation. Biological pathways were then linked to adverse outcome pathways to identify potential adverse outcomes and biomarkers for use in subsequent monitoring efforts. \n\nThis dataset is associated with the following publication:\nBlackwell, B., G. Ankley, S. Corsi, L.A.  DeCicco, K. Houck, R. Judson, S. Li, M. Martin, A. Schroeder, J. Swintek, D. Villeneuve, E. Murphy, and E. Smith. An \"EAR\" on environmental surveillance and monitoring: A case study on the use of exposure-activity ratios to prioritize sites, chemicals, and bioactivities of concern in Great Lakes waters.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(15): 8713\u20138724, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1371573",
            "keyword": [
                "exposure activity ratio",
                "Great Lakes Restoration Initiative",
                "adverse outcome pathway",
                "endocrine disruption",
                "ecotoxicology",
                "aquatic ecosystems",
                "screening and prioritization"
            ],
            "contactPoint": {
                "fn": "Brett Blackwell",
                "hasEmail": "mailto:blackwell.brett@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://dx.doi.org/10.1021/acs.est.7b01613",
                    "accessURL": "https://dx.doi.org/10.1021/acs.est.7b01613"
                }
            ],
            "modified": "2017-07-03",
            "references": [
                "https://doi.org/10.1021/acs.est.7b01613"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Association between adverse cardiovascular outcomes and PM2.5 data obtained from monitors, CMAQ models, and satellite models.",
            "description": "Background: Adverse cardiovascular events have been linked with PM2.5 exposure obtained primarily from air\nquality monitors, which rarely co-locate with participant residences. Modeled PM2.5 predictions at finer resolution\nmay more accurately predict residential exposure; however few studies have compared results across\ndifferent exposure assessment methods.\nMethods: We utilized a cohort of 5679 patients who had undergone a cardiac catheterization between\n2002\u20132009 and resided in NC. Exposure to PM2.5 for the year prior to catheterization was estimated using data\nfrom air quality monitors (AQS), Community Multiscale Air Quality (CMAQ) fused models at the census tract and\n12 km spatial resolutions, and satellite-based models at 10 km and 1 km resolutions. Case status was either a\ncoronary artery disease (CAD) index>23 or a recent myocardial infarction (MI). Logistic regression was used to\nmodel odds of having CAD or an MI with each 1-unit (\u03bcg/m3) increase in PM2.5, adjusting for sex, race, smoking\nstatus, socioeconomic status, and urban/rural status.\nResults: We found that the elevated odds for CAD>23 and MI were nearly equivalent for all exposure assessment\nmethods. One difference was that data from AQS and the census tract CMAQ showed a rural/urban difference\nin relative risk, which was not apparent with the satellite or 12 km-CMAQ models.\nConclusions: Long-term air pollution exposure was associated with coronary artery disease for both modeled and\nmonitored data. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Clinical data are located in:\r\nC:\\Users\\rdevlin\\OneDrive - Environmental Protection Agency (EPA)\\Excel Files\\Cathgen  \r\n\r\nSatellite data are located in : \r\nC:\\Users\\rdevlin\\OneDrive - Environmental Protection Agency (EPA)\\Excel Files\\New Ikm Satellite Data \r\nC:\\Users\\rdevlin\\OneDrive - Environmental Protection Agency (EPA)\\Excel Files\\Satellite Data \r\nCMAQ data are located in C:\\Users\\rdevlin\\OneDrive - Environmental Protection Agency (EPA)\\Excel Files\\CMAQ Data. Format: There are two types of datasets used in this study:  clinical data taken from patient records at the Duke Medical Center; and air pollution data (PM2.5) taken from a federal reference monitor located in Raleigh, CMAQ data obtained from collaborators at Georgia Tech and NERL/ORD, and satellite data obtained from collaborators at Harvard.  \r\n\r\nMetadata are in the form of Excel spreadsheets that contain columns of data that specify clinical and exposure information for each individual participating in the study. \n\nThis dataset is associated with the following publication:\nMcGuinn, L., C. Ward-Caviness, A. Schneider, Q. Di, A. Chudnovsky, J. Schwartz, P. Koutrakis, A. Russell, V. Garcia, W. Krause, E. Hauser, L. Neas, W. Cascio, D. Diaz-Sanchez, and R. Devlin. Fine Particulate Matter and Cardiovascular Disease: Comparison of Assessment Methods for Long-term Exposure.   ENVIRONMENTAL RESEARCH. Academic Press Incorporated, Orlando, FL, USA, 159: 16-23, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1375430",
            "keyword": [
                "Fine Particulate Matter",
                "air pollution",
                "cardiovascular disease",
                "epidemiology",
                "Exposure Assessment",
                "particulate matter"
            ],
            "contactPoint": {
                "fn": "Robert Devlin",
                "hasEmail": "mailto:devlin.robert@epa.gov"
            },
            "distribution": [],
            "modified": "2016-12-01",
            "references": [
                "https://doi.org/10.1016/j.envres.2017.07.041"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Performance Evaluation and Community Application of Low-Cost Sensors for Ozone and Nitrogen Dioxide Data Set",
            "description": "Data set contains data collected during the DISCOVER-AQ Mission that support the journal article results. \n\nThis dataset is associated with the following publication:\nDuvall , R., R. Long , M. Beaver , K. Kronmillwe, M. Wheeler, J. Szykman , M. Silverman, and J.H. Crawford. Performance Evaluation and Community Application of Low-Cost Sensors for Ozone and Nitrogen Dioxide.   Sensors. MDPI AG, Basel,  SWITZERLAND, 16(10): 1698, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1374981",
            "keyword": [
                "Sensors",
                "Ozone",
                "nitrogen dioxide",
                "citizen science",
                "DISCOVER-AQ",
                "FRM/FEM"
            ],
            "contactPoint": {
                "fn": "Rachelle Duvall",
                "hasEmail": "mailto:duvall.rachelle@epa.gov"
            },
            "distribution": [
                {
                    "title": "DuvallRachelle_A-fttw_Data Set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374981/DuvallRachelle_A-fttw_Data%20Set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://www-air.larc.nasa.gov/missions/discover-aq/discover-aq.html",
                    "accessURL": "https://www-air.larc.nasa.gov/missions/discover-aq/discover-aq.html"
                }
            ],
            "modified": "2017-08-14",
            "references": [
                "https://doi.org/10.3390/s16101698"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Method 1615 RT-qPCR data",
            "description": "EPA Method 1615 measures enteroviruses and noroviruses present in environmental and drinking waters. The viral ribonucleic acid (RNA) from water sample concentrates is extracted and tested for enterovirus and norovirus RNA using reverse transcription-quantitative PCR (RT-qPCR). Virus concentrations for the molecular assay are calculated in terms of genomic copies of viral RNA per liter based upon a standard curve. The method uses a number of quality controls to increase data quality and to reduce interlaboratory and intralaboratory variation. The method has been evaluated by examining virus recovery from ground and reagent grade waters seeded with poliovirus type 3 and murine norovirus as a surrogate for human noroviruses. Mean poliovirus recoveries were 20% in groundwaters and 44% in reagent grade water. Mean murine norovirus recoveries with the RT-qPCR assay were 31% in groundwaters and 4% in reagent grade water. \n\nThis dataset is associated with the following publication:\nFout , S., J. Cashdollar , S. Griffin , N. Brinkman , E. Varughese , and S. Parshionikar. EPA Method 1615. Measurement of Enterovirus and Norovirus Occurrence in Water by Culture and RT-qPCR. Part III. Virus Detection by RT-qPCR.   Journal of Visualized Experiments. JoVE, Somerville, MA, USA, 107: e52646, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1368685",
            "keyword": [
                "virus",
                "waterborne",
                "detection",
                "occurrence",
                "rt-qpcr"
            ],
            "contactPoint": {
                "fn": "Jennifer Cashdollar",
                "hasEmail": "mailto:cashdollar.jennifer@epa.gov"
            },
            "distribution": [
                {
                    "title": "Final Corrected molecular data for JoVE 29Jun17.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1368685/Final%20Corrected%20molecular%20data%20for%20JoVE%2029Jun17.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-29",
            "references": [
                "https://doi.org/10.3791/52646"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Literature review tables for Karna et al. 2017",
            "description": "N/A. Users will need to access the manuscript to see non-EPA data presented in tables and figures. This dataset is not publicly accessible because: The tables in the manuscript are summaries of non-EPA data. It can be accessed through the following means: Data in the tables of the review manuscript have notations to citations in the manuscript. Format: No EPA generated data used in the paper; all information was taken from previously published literature to format this review of waste materials. \n\nThis dataset is associated with the following publication:\nKarna, R., T. Luxton, K. Bronstein, J. Redmon, and K. Scheckel. State of the Science Review:  Potential for Beneficial Use of Waste By-Products for <I>In-situ</I> Remediation of Metal-Contaminated Soil and Sediment.  Scott Bradford  CRITICAL REVIEWS IN ENVIRONMENTAL SCIENCE AND TECHNOLOGY. CRC Press LLC, Boca Raton, FL, USA, 47(2): 65-129, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1372883",
            "keyword": [
                "soil amendments",
                "metals",
                "remediation",
                "waste reuse"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [],
            "modified": "2016-12-16",
            "references": [
                "https://doi.org/10.1080/10643389.2016.1275417"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Understanding arsenic dynamics in agronomic systems to predict and prevent uptake by crop plants",
            "description": "N/A. This is a review article and no data were generated in the process of the review. This dataset is not publicly accessible because: This is a review article and no data were generated in the process of the review. It can be accessed through the following means: Information is presented in the published manuscript. Format: This is a review article and no data were generated in the process of the review. \n\nThis dataset is associated with the following publication:\nPunshon, T., B. Jackson, A. Meharg, T. Warczak, K. Scheckel, and M.L. Guerinot. Understanding Arsenic Dynamics in Agronomic Systems to Predict and Prevent Uptake by Crop Plants.  D. Barcelo, and Jay Gan  SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 582: 209/220, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1372884",
            "keyword": [
                "arsenic",
                "soil",
                "crop agriculture",
                "mitigation",
                "bioavailability"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [],
            "modified": "2016-08-29",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.12.111"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Rainfall and Detention Basin Flows",
            "description": "Storm event data and flow rates in/out pre-post device installation. \n\nThis dataset is associated with the following publication:\nHawley, R., J. Goodrich, N. Korth, C. Rust, E. Fet, C. Frye, K. MacMannis, M. Wooten, M. Jacobs, and R. Sinha. Detention Outlet Retrofit Improves the Functionality of Existing Detention Basins by Reducing Erosive Flows in Receiving Channels.   JOURNAL OF AMERICAN WATER RESOURCES ASSOCIATION. American Water Resources Association, Middleburg, VA, USA,  1-16, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1374420",
            "keyword": [
                "storm events",
                "Hydraulic rates",
                "Detention basin flow control",
                "Wide area water decontamination"
            ],
            "contactPoint": {
                "fn": "James Goodrich",
                "hasEmail": "mailto:goodrich.james@epa.gov"
            },
            "distribution": [
                {
                    "title": "Copy of Figure and Table Data for EPA.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374420/Copy%20of%20Figure%20and%20Table%20Data%20for%20EPA.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Hawley_et_al-2017-JAWRA_Journal_of_the_American_Water_Resources_Association.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374420/Hawley_et_al-2017-JAWRA_Journal_of_the_American_Water_Resources_Association.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2014-06-05",
            "references": [
                "https://doi.org/10.1111/1752-1688.12548"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "NLCD - MODIS land cover- albedo dataset for the continental United States ",
            "description": "The NLCD-MODIS land cover-albedo database integrates high-quality MODIS albedo observations with areas of homogeneous land cover from NLCD. The spatial resolution (pixel size) of the database is 480m-x-480m aligned to the standardized UGSG Albers Equal-Area projection. The spatial extent of the database is the continental United States. \n\nThis dataset is associated with the following publication:\nWickham, J., M. Nash, and C.A. Barnes. Effect of land cover change on snow free surface albedo across the continental United States.   Global and Planetary Change. Elsevier BV, AMSTERDAM,  NETHERLANDS, 146: 1-9, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1375439",
            "keyword": [
                "climate change",
                "land cover change",
                "Landsat",
                "radiative forcing",
                "snow-cover albedo",
                "snow-free albedo"
            ],
            "contactPoint": {
                "fn": "James Wickham",
                "hasEmail": "mailto:wickham.james@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=A-3txd-117",
                    "accessURL": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=A-3txd-117"
                }
            ],
            "modified": "2017-08-10",
            "references": [
                "https://doi.org/10.1016/j.gloplacha.2016.09.005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://www.mrlc.gov/nlcdalbedo.php",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Watershed impervious cover relative to stream location ",
            "description": "Estimates of watershed (12-digit huc) impervious cover and impervious cover near streams and water body shorelines for three dates (2001, 2006, 2011) using NLCD data. Differences between watershed impervious cover and impervious cover near streams can be used to assess the spatial pattern of impervious cover within a watershed. \n\nThis dataset is associated with the following publication:\nWickham, J., S.V. Stehman, L. Gass, J.A. Dewitz, D.G. Sorenson, B.J. Granneman, R.V. Poss, and L.A. Baer. Thematic Accuracy Assessment of the 2011 National Land Cover Database (NLCD).   REMOTE SENSING OF ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 191: 328-341, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1375440",
            "keyword": [
                "Impervious cover",
                "National Land Cover Database (NLCD)",
                "Clean Water Act",
                "change detection",
                "roads",
                "spatial pattern"
            ],
            "contactPoint": {
                "fn": "James Wickham",
                "hasEmail": "mailto:wickham.james@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=A-3txd-118",
                    "accessURL": "https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=A-3txd-118"
                }
            ],
            "modified": "2017-08-10",
            "references": [
                "https://doi.org/10.1016/j.rse.2016.12.026"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1375440/documents/SciHub_Metadata.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "MEA 86 Compound data",
            "description": "This data file contains the full raw parameter data for the 86 compounds tested in the developmental MEA assay, as well as Area Under the Curve (AUC) calculations and plate normalized data.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1374038",
            "keyword": [
                "developmental neurotoxicity",
                "screening",
                "in vitro",
                "neuronal function",
                "Microelectrode array"
            ],
            "contactPoint": {
                "fn": "Timothy Shafer",
                "hasEmail": "mailto:shafer.tim@epa.gov"
            },
            "distribution": [
                {
                    "title": "MEA_86_Compound_Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374038/MEA_86_Compound_Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-07",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Chemical agnostic hazard prediction: Statistical inference of toxicity pathways - data for Figure 2",
            "description": "This dataset comprises one SigmaPlot 13 file containing measured survival data and survival data predicted from the model coefficients selected by the LASSO procedure. \n\nThis dataset is associated with the following publication:\nRoss, J., B. George, M. Bruno, and Y. Ge. Chemical-agnostic hazard prediction:  statistical inference of in vitro toxicity pathways from proteomics responses to chemical mixtures.   Computational Toxicology. Elsevier B.V., Amsterdam,  NETHERLANDS, 2: 39-44, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1376218",
            "keyword": [
                "survival",
                "model predictions",
                "in vitro assays",
                "Mixtures",
                "computational toxicology",
                "toxicity pathways",
                "proteomics"
            ],
            "contactPoint": {
                "fn": "Jeffrey Ross",
                "hasEmail": "mailto:ross.jeffrey@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data for Figure  2.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376218/Data%20for%20Figure%20%202.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-11-30",
            "references": [
                "https://doi.org/10.1016/j.comtox.2017.03.001"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset - Evaluation of Standardized Sample Collection, Packaging, and Decontamination Procedures to Assess Cross-Contamination Potential during Bacillus anthracis Incident Response Operations",
            "description": "Spore recovery data during sample packaging decontamination tests. \n\nThis dataset is associated with the following publication:\nCalfee, W., J. Tufts, K. Meyer, K. McConkey, L. Mickelsen, L. Rose, C. Dowell, L. Delaney, A. Weber, S. Morse, J. Chaitram, and M. Gray. Evaluation of standardized sample collection, packaging, and decontamination procedures to assess cross-contamination potential during Bacillus anthracis incident response operations.   JOURNAL OF OCCUPATIONAL AND ENVIRONMENTAL HYGIENE. Taylor & Francis, Inc., Philadelphia, PA, USA, 13(12): 12, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1373698",
            "keyword": [
                "efficacy",
                "bacillus atrophaeus",
                "recovery",
                "anthrax",
                "sampling",
                "Bacillus anthracis",
                "cross-contamination",
                "homeland security"
            ],
            "contactPoint": {
                "fn": "Michael Calfee",
                "hasEmail": "mailto:calfee.worth@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science Hub for JOEH 2016_Calfee.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1373698/Science%20Hub%20for%20JOEH%202016_Calfee.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-07-05",
            "references": [
                "https://www.ncbi.nlm.nih.gov/pubmed/27362274"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Compilation of colony forming unit data for Bacillus anthracis and B. atrophaeus before and after exposure to various fogging treatments using peracetic acid or hydrogen peroxide",
            "description": "Data set contains CFU data for positive controls and test coupons for each test, for each material, and for each microorganism used.  Also included are efficacy data in terms of log reductions. It also includes data on process and environmental conditions during fogging. \n\nThis dataset is associated with the following publication:\nRichter, W., J. Wood, M. Wendling, and J. Rogers. Inactivation of Bacillus anthracis spores to decontaminate subway railcar and related materials via the fogging of peracetic acid and hydrogen peroxide sporicidal liquids.   JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 206: 800-806, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1375628",
            "keyword": [
                "Decontamination",
                "Bacillus anthracis",
                "bacterial spores",
                "fog"
            ],
            "contactPoint": {
                "fn": "Joseph Wood",
                "hasEmail": "mailto:wood.joe@epa.gov"
            },
            "distribution": [
                {
                    "title": "data compilation.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375628/data%20compilation.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-20",
            "references": [
                "https://doi.org/10.1016/j.jenvman.2017.11.027"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "TEVA-SPOT-GUI - Containing Preliminary Flow Model",
            "description": "This ZIP file contains the developmental, test version of TEVA-SPOT-GUI's Flow Model.  The Flow Model is a new, event based water quality algorithm for EPANET.  The Flow Model is preliminary, i.e., it may not work for all models or all scenarios (i.e., release nodes in the network model).  If you want to examine the Flow Model code please go to the Github site at:\n\nhttps://github.com/ttaxon/EPANET/tree/flow-transport-model\n\nIf you have any questions, contact Robert Janke (janke.robert@epa.gov). \n\nThis dataset is associated with the following publication:\nJanke, R. Mass Imbalances in EPANET Water-quality Simulations.   Drinking Water Engineering and Science Discussions. Copernicus Gesellschaft mbH, Gottingen,  GERMANY,  25-47, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1375315",
            "keyword": [
                "TEVA-SPOT",
                "EPANET",
                "flow model",
                "Water Quality Algorithm",
                "Drinking water distribution system",
                "EPANET network models",
                "Mass Balance"
            ],
            "contactPoint": {
                "fn": "Robert Janke",
                "hasEmail": "mailto:janke.robert@epa.gov"
            },
            "distribution": [
                {
                    "title": "TEVA-SPOTInstaller-2.3.2-MSXb-20170110-DEV.ZIP",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375315/TEVA-SPOTInstaller-2.3.2-MSXb-20170110-DEV.ZIP",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-01-10",
            "references": [
                "https://doi.org/10.5194/dwes-11-25-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "EPANET INP files used in paper.",
            "description": "Text files with the \".inp\" extension that can be used in EPANET to simulate hydraulic and water quality analyses and which can be used in TEVA-SPOT-GUI. \n\nThis dataset is associated with the following publication:\nJanke, R. Mass Imbalances in EPANET Water-quality Simulations.   Drinking Water Engineering and Science Discussions. Copernicus Gesellschaft mbH, Gottingen,  GERMANY,  25-47, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1375314",
            "keyword": [
                "EPANET network models",
                "Drinking water distribution system",
                "EPANET",
                "Mass Balance",
                "Water Quality Algorithm"
            ],
            "contactPoint": {
                "fn": "Robert Janke",
                "hasEmail": "mailto:janke.robert@epa.gov"
            },
            "distribution": [
                {
                    "title": "Mass_Inbalances_EPANET_dataset.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375314/Mass_Inbalances_EPANET_dataset.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "https://cfpub.epa.gov/si/si_public_record_report.cfm?subject=Homeland%20Security%20Research&dirEntryId=257684",
                    "accessURL": "https://cfpub.epa.gov/si/si_public_record_report.cfm?subject=Homeland%20Security%20Research&dirEntryId=257684"
                }
            ],
            "modified": "2017-07-01",
            "references": [
                "https://doi.org/10.5194/dwes-11-25-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "USEEIO v1.1 - Elementary Flows and Life Cycle Impact Assessment (LCIA) Characterization Factors",
            "description": "This dataset is part of the USEEIO v1.1 model release. It provides the elementary flows used in the USEEIO v1.1 Satellite Tables (DOI: 10.23719/1365565) and their matching characterization factors for the various indicators. The indicators are described and categorized. An original mapping file is also provided that shows the correspondence between original source names for resources, emissions, land, etc and USEEIO elementary flows. This dataset supersedes USEEIO Elementary Flows and Life Cycle Impact Assessment (LCIA) Characterization Factors(https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B8A87EE76-F047-43E1-A4B3-9D83BAE110C4%7D). It can be exported as a .csv file and used with the exported satellite tables and BEA 2007 Make and Use tables to build USEEIO v1.1 using the IO Model Builder (https://github.com/USEPA/IO-Model-Builder). \n\nThis dataset is associated with the following publication:\nYang, Y., W. Ingwersen, T. Hawkins, and D. Meyer. USEEIO: A new and transparent United States environmentally extended input-output model.   JOURNAL OF CLEANER PRODUCTION. Elsevier Science Ltd, New York, NY, USA, 158: 308-318, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1368541",
            "keyword": [
                "elementary flows",
                "resource use factors",
                "environmental impact factors",
                "life cycle assessment",
                "life cycle inventory data",
                "sustainability",
                "input-output data"
            ],
            "contactPoint": {
                "fn": "Wesley Ingwersen",
                "hasEmail": "mailto:ingwersen.wesley@epa.gov"
            },
            "distribution": [
                {
                    "title": "USEEIOv1.1_ElementaryFlowsLCIAFactors.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1368541/USEEIOv1.1_ElementaryFlowsLCIAFactors.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-07",
            "references": [
                "https://doi.org/10.1016/j.jclepro.2017.04.150"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Coliphage and adenovirus concentrations at various points along the net-zero system",
            "description": "Coliphage and adenovirus concentrations per liter. \n\nThis dataset is associated with the following publication:\nGassie, L., J. Englehardt, J. Wang, N. Brinkman, J. Garland, P. Gardinali, and T. Guo. Mineralizing urban net-zero water treatment: Phase II field results and design recommendations.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 105: 496-506, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1376692",
            "keyword": [
                "coliphage",
                "adenovirus",
                "net-zero",
                "potable water reuse",
                "advanced oxidation"
            ],
            "contactPoint": {
                "fn": "Nichole Brinkman",
                "hasEmail": "mailto:brinkman.nichole@epa.gov"
            },
            "distribution": [
                {
                    "title": "BrinkmanNichole_A-80gm_dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376692/BrinkmanNichole_A-80gm_dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-11-20",
            "references": [
                "https://doi.org/10.1016/j.watres.2016.09.005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "National level POLYSYS data for Hellwinckel et al. (2015): Simulated impact of the renewable fuels standard on US Conservation Reserve Program enrollment and conversion",
            "description": "This is the data of national level land conversions, prices, assumptions, etc., in the POLYSYS runs to estimate the land use change impacts from a growing biofuels industry. The results are discussed in Detail in Hellwinckel et al. (2015): \"Simulated impact of the renewable fuels standard on US Conservation Reserve Program enrollment and conversion.\" Global Change Biology - Bioenergy (2015), doi: 10.1111/gcbb.12281. \n\nThis dataset is associated with the following publication:\nHellwinckel, C., C. Clark , M. Langholtz, L. Eaton, and P. Morefield. Impact of the Renewable Fuels Standard on U.S. Conservation Reserve Program Enrollment and Conversion. GCB Bioenergy. John Wiley & Sons, Inc., Hoboken, NJ, USA, 8(1): 245-256, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-31zh-372",
            "keyword": [
                "biofuels",
                "agro-economic modeling",
                "POLYSYS",
                "RFS",
                "Renewable Fuel Standard",
                "land use change",
                "CRP",
                "Conservation Reserve Program"
            ],
            "contactPoint": {
                "fn": "Christopher Clark",
                "hasEmail": "mailto:clark.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data For Science Hub_National level output_AllSimulations.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/372/Data%20For%20Science%20Hub_National%20level%20output_AllSimulations.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-08-18",
            "references": [
                "https://doi.org/10.1111/gcbb.12281"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Gomphid DNA sequence data",
            "description": "DNA sequence data for several genetic loci. This dataset is not publicly accessible because: It's already publicly available on GenBank. It can be accessed through the following means: GenBank/NCBI (http://www.ncbi.nlm.nih.gov/). Accession numbers KX890490-KX891168. Format: This dataset is DNA sequence data. It is available in GenBank. Accession numbers KX890490-KX891168. \n\nThis dataset is associated with the following publication:\nWare, J., E. Pilgrim, M. May, N. Donnelly, and K. Tennessen. Phylogenetic relationships of North American Gomphidae and their close relatives.   Systematic Entomology. John Wiley & Sons, Inc., Hoboken, NJ, USA, 42(2): 347-358, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1377811",
            "keyword": [
                "DNA Barcoding",
                "Odonata",
                "biomonitoring"
            ],
            "contactPoint": {
                "fn": "Erik Pilgrim",
                "hasEmail": "mailto:pilgrim.erik@epa.gov"
            },
            "distribution": [],
            "modified": "2017-06-15",
            "references": [
                "https://doi.org/10.1111/syen.12218"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "USEEIO v1.1 - Matrices",
            "description": "This dataset provides the basic building blocks for the USEEIO v1.1 model and life cycle results per $1 (2013 USD) demand for all goods and services in the model in the producer's price (see BEA 2015). The methodology underlying USEEIO is described in Yang, Ingwersen et al., 2017, with updates for v1.1 described in documentation supporting other USEEIO v1.1 datasets. This dataset is in the form of standard matrices. USEEIOv1.1 uses original names for goods and services, to distinguish them from the sector names provided by BEA which reflect industry names and not commodity names, but the BEA codes are maintained. The main model matrices are in green, A, B, and C; the result matrices are in gold, D, L, LCI, and U. Aggregate data quality scores are presented for B, D and U matrices in peach. Data quality scores use the US EPA data quality asssessment system, see US EPA 2016. Aggregated scores are calculated using a flow-weighted average approach as described in Edelen and Ingwersen 2017. \t\n\nReferences\nBEA (2015). Detailed Make and Use Tables in Producer Prices, 2007, Before Redefinitions. Bureau of Economic Analysis. https://www.bea.gov/iTable/index_industry_io.cfm\n\nEdelen, A. and W. Ingwersen (2017). \"The creation, management and use of data quality information for life cycle assessment.\" International Journal of Life Cycle Assessment. http://dx.doi.org/10.1007/s11367-017-1348-1\n\nUS EPA 2016. Guidance on Data Quality Assessment for Life Cycle Inventory Data. US Environmental Protection Agency, National Risk Management Research Laboratory, Life Cycle Assessment Research Center, Washington, DC. https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=321834\n\nYang, Y., Ingwersen, W. W., Hawkins, T. R., Srocka, M., & Meyer, D. E. (2017). USEEIO: A new and transparent United States environmentally-extended input-output model. Journal of Cleaner Production, 158, 308-318. \nhttp://dx.doi.org/10.1016/j.jclepro.2017.04.150. \n\nThis dataset is associated with the following publication:\nYang, Y., W. Ingwersen, T. Hawkins, and D. Meyer. USEEIO: A new and transparent United States environmentally extended input-output model.   JOURNAL OF CLEANER PRODUCTION. Elsevier Science Ltd, New York, NY, USA, 158: 308-318, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1369615",
            "keyword": [
                "life cycle results",
                "total requirements matrix",
                "life cycle impacts",
                "data quality scores",
                "life cycle assessment",
                "life cycle inventory data",
                "sustainability",
                "input-output data"
            ],
            "contactPoint": {
                "fn": "Wesley Ingwersen",
                "hasEmail": "mailto:ingwersen.wesley@epa.gov"
            },
            "distribution": [
                {
                    "title": "USEEIOv1.1_Matrices.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1369615/USEEIOv1.1_Matrices.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-14",
            "references": [
                "https://doi.org/10.1016/j.jclepro.2017.04.150"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Duke Forest Particle Nucleation Data",
            "description": "Particle size distribution expressed as number concentration per size bin. \n\nThis dataset is associated with the following publications:\nPillai, P., V. Aneja, J. Walker , and A. Khlystov. Observation and Analysis of Particle Nucleation at a Forest Site in the Southeast U.S..   Atmospheric Pollution Research. Turkish National Committee for Air Pollution Research and Control, Izmir,  TURKEY, 4(2): 72-93, (2013).\nYu, F., and J. Walker. Spring and summer contrast in new particle formation over nine forest areas in North America.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 15(24): 13993-14003, (2105).\nSullivan, R., P. Crippa, A.G. Hallar, L. Clarisse, W.R. Leaitch, J. Walker, A. Khlystov, and S.C. Pryor. Using satellite-based measurements to explore spatiotemporal scales and variability of drivers of new particle formation.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 121(20): 12217-12235, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1377393",
            "keyword": [
                "particle nucleation"
            ],
            "contactPoint": {
                "fn": "John Walker",
                "hasEmail": "mailto:walker.johnt@epa.gov"
            },
            "distribution": [
                {
                    "title": "ORD_SDH_Particle Nucleation.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377393/ORD_SDH_Particle%20Nucleation.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-05-26",
            "references": [
                "https://doi.org/10.3390/atmos4020072",
                "https://doi.org/10.5194/acp-15-13993-2015",
                "https://doi.org/10.1002/2016jd025568"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "USEEIOv1.1  - Satellite Tables",
            "description": "This dataset supersedes the original 'USEEIO satellite files' dataset (https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7B49F4F982-C5DB-4A62-878A-DE341A2099B6%7D). See the supporting documentation for a full description of updates to the satellite tables in this release. \n\nThis dataset is associated with the following publication:\nYang, Y., W. Ingwersen, T. Hawkins, and D. Meyer. USEEIO: A new and transparent United States environmentally extended input-output model.   JOURNAL OF CLEANER PRODUCTION. Elsevier Science Ltd, New York, NY, USA, 158: 308-318, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1365565",
            "keyword": [
                "life cycle assessment",
                "life cycle inventory data",
                "sustainability",
                "input-output data"
            ],
            "contactPoint": {
                "fn": "Wesley Ingwersen",
                "hasEmail": "mailto:ingwersen.wesley@epa.gov"
            },
            "distribution": [
                {
                    "title": "USEEIOv1.1SatelliteTables.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1365565/USEEIOv1.1SatelliteTables.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-06-22",
            "references": [
                "https://doi.org/10.1016/j.jclepro.2017.04.150",
                "https://pasteur.epa.gov/uploads/10.23719/1365565/documents/USEEIOv1.1-DescriptionofSatelliteTableUpdates.pdf",
                "https://pasteur.epa.gov/uploads/10.23719/1365565/documents/USEEIO1.0vs1.1.xlsx"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1365565/documents/USEEIO%20Data%20Dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "USEEIOv1.1 - openLCA",
            "description": "This is a version of the full USEEIO v1.1 model in the openLCA schema serialized as JSON-LD that can be imported into openLCA software (www.openlca.org) v1.5 and more recent versions. \n\nThis dataset is associated with the following publication:\nYang, Y., W. Ingwersen, T. Hawkins, and D. Meyer. USEEIO: A new and transparent United States environmentally extended input-output model.   JOURNAL OF CLEANER PRODUCTION. Elsevier Science Ltd, New York, NY, USA, 158: 308-318, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1375574",
            "keyword": [
                "USEEIO",
                "EEIO",
                "LCA",
                "input-output data",
                "openLCA",
                "LCI",
                "life cycle assessment",
                "life cycle inventory data",
                "sustainability"
            ],
            "contactPoint": {
                "fn": "Wesley Ingwersen",
                "hasEmail": "mailto:ingwersen.wesley@epa.gov"
            },
            "distribution": [
                {
                    "title": "USEEIOv1.1-JSONLD-foropenlca.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375574/USEEIOv1.1-JSONLD-foropenlca.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-08-15",
            "references": [
                "https://doi.org/10.1016/j.jclepro.2017.04.150",
                "https://pasteur.epa.gov/uploads/10.23719/1375574/documents/USEEIOv1.1_openlca_supportinginformation.txt"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://greendelta.github.io/olca-schema/",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Arsenic speciation results",
            "description": "Linear combination fitting results of synchrotron data to determine arsenic speciation in soil samples. \n\nThis dataset is associated with the following publication:\nWhitacre, S., N. Basta, B. Stevens, V. Hanley, R. Anderson, and K. Scheckel. Modification of an Existing In vitro Method to Predict Relative Bioavailable Arsenic in Soils.  Jacob de Boer, and Shane Snyder  CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 180: 545-552, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1377034",
            "keyword": [
                "Bioaccessibility",
                "metal bioavailability",
                "synchrotron speciation",
                "arsenic",
                "human health risk assessment"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "CAB Method Tables.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377034/CAB%20Method%20Tables.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-12-08",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2017.03.134"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "In situ analyses of Ag speciation in tissues of cucumber and wheat using synchrotron-based X-ray absorption spectroscopy",
            "description": "In situ analyses of Ag speciation in tissues of cucumber and wheat using synchrotron-based X-ray absorption spectroscopy showing spectral fitting and linear combination fitting results. \n\nThis dataset is associated with the following publication:\nWang, P., E. Lombi, S. Sun, K. Scheckel, A. Malysheva, B. McKenna, N. Menzies, F. Zhao, and P. Kopittke. Characterizing the Uptake, Accumulation and Toxicity of Silver Sulfide Nanoparticles in Plants.  Vicki Grassian  Environmental Science: Nano. RSC Publishing, Cambridge,  UK, 4(2): 448-460, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1377039",
            "keyword": [
                "synchrotron speciation",
                "silver nanoparticles",
                "plant uptake"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Ag Speciation Results.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377039/Ag%20Speciation%20Results.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-10-03",
            "references": [
                "https://doi.org/10.1039/c6en00489j"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Uranium and Iron XRF distribution and Fe speciation results",
            "description": "Dataset 1: XRF image of U and Fe distribution\r\nDataset 2: Fe linear combination fitting data. \n\nThis dataset is associated with the following publication:\nKoster van Groos, P., D. Kaplan, H. Chang, J. Seaman, D. Li, A. Peacock, K. Scheckel , and P. Jaffe. Uranium fate in wetland mesocosms:  Effects of plants at two iron loadings with different pH values.  Jacob de Boer, and Shane Snyder  CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 163: 116-124, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1377036",
            "keyword": [
                "synchrotron speciation",
                "uranium",
                "rhizosphere chemistry",
                "wetlands",
                "iron chemistry"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Fe and U distribution image.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377036/Fe%20and%20U%20distribution%20image.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Fe LCF Dataset.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377036/Fe%20LCF%20Dataset.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-02-25",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2016.08.012"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Pb speciation results in amended soils",
            "description": "The dataset shows the distribution of Pb phases resulting from various amendments to change Pb speciation. \n\nThis dataset is associated with the following publication:\nObrycki, J., K. Scheckel, and N. Basta. Soil solution interactions may limit Pb remediation using P amendments in an urban soil.  David Carpenter, Eddy Zeng  ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 220: 549-556, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1377037",
            "keyword": [
                "synchrotron speciation",
                "lead",
                "Bioaccessibility",
                "metal bioavailability",
                "in-situ amendments"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Pb LCF Data.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377037/Pb%20LCF%20Data.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-07-11",
            "references": [
                "https://doi.org/10.1016/j.envpol.2016.10.002"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Speciation of ZnO and CuO nanoparticles exposed to culture medium and lymphocyte cells",
            "description": "Spectral fits and linear combination data for ZnO and CuO nanoparticles exposure during toxicity testing. \n\nThis dataset is associated with the following publication:\nIvask, A., K. Scheckel, P. Kapruwan, V. Stone, H. Yin, N. Voelcker, and E. Lombi. Complete transformation of ZnO and CuO nanoparticles in culture medium and lymphocyte cells during toxicity testing.  Prof. Hakan Wallin, and Dr. Alison Elder  Nanotoxicology. Informa Healthcare, London,  UK, 11(2): 150-156, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1377038",
            "keyword": [
                "synchrotron speciation",
                "engineered nanomaterials",
                "ZnO",
                "CuO",
                "toxicity"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cu speciation results.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377038/Cu%20speciation%20results.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Zn speciation results.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377038/Zn%20speciation%20results.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-09-15",
            "references": [
                "https://doi.org/10.1080/17435390.2017.1282049"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Metadata from 12 international groundwater studies: virus and microbial indicator occurrence",
            "description": "This data set contains raw data from 12 international groundwater studies that monitored for human viruses and microbial indicators. Please see the first worksheet for identification of the studies used. \n\nThis dataset is associated with the following publication:\nFout, S., M. Karim, and M. Borchardt. Human virus and microbial indicator occurrence in public-supply groundwater systems: meta-analysis of international studies.   Hydrogeology Journal. Springer, Heidelburg,  GERMANY, 25(0): 903-919, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "A-0p2r-609",
            "keyword": [
                "Contamination",
                "drinking water",
                "enteric virus",
                "microbial indicators"
            ],
            "contactPoint": {
                "fn": "G Fout",
                "hasEmail": "mailto:fout.shay@epa.gov"
            },
            "distribution": [
                {
                    "title": "Virus data final.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/609/Virus%20data%20final.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-05-10",
            "references": [
                "https://doi.org/10.1007/s10040-017-1581-5"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "source files for manuscript in tex format",
            "description": "Source tex files used to create the manuscript including original figure files and raw data used in tables and inline text. \n\nThis dataset is associated with the following publication:\nBeck, M., J. Lehrter, L. Lowe, and B. Jarvis. Parameter sensitivity and identifiability for a biogeochemical model of hypoxia in the northern Gulf of Mexico.   ECOLOGICAL MODELLING. Elsevier Science BV, Amsterdam,  NETHERLANDS, 363: 17-30, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1377812",
            "keyword": [
                "Coastal General Ecosystem Model (CGEM)",
                "Gulf of Mexico (GOM)",
                "Hypoxia",
                "Sensitivity",
                "Identifiability"
            ],
            "contactPoint": {
                "fn": "Marcus Beck",
                "hasEmail": "mailto:beck.marcus@epa.gov"
            },
            "distribution": [
                {
                    "title": "source.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377812/source.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-08-18",
            "references": [
                "https://doi.org/10.1016/j.ecolmodel.2017.08.020"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Tables and figure datasets",
            "description": "Soil and air concentrations of asbestos in Sumas study. \n\nThis dataset is associated with the following publication:\nWroble, J., T. Frederick, A. Frame, and D. Vallero. Comparison of soil sampling and analytical methods for asbestos at the Sumas Mountain Asbestos Site\u2014Working towards a toolbox for better assessment.   PLoS ONE. Public Library of Science, San Francisco, CA, USA, 12(7): e0180210, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1378092",
            "keyword": [
                "asbestos",
                "sediment",
                "naturally occurring asbestos",
                "transmission electronic microscopy (TEM)"
            ],
            "contactPoint": {
                "fn": "Daniel Vallero",
                "hasEmail": "mailto:vallero.daniel@epa.gov"
            },
            "distribution": [
                {
                    "title": "5261809.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378092/5261809.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-07-31",
            "references": [
                "https://doi.org/10.1371/journal.pone.0180210"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1378092/documents/data%20dictionary_ValleroDaniel_A-02vb_SDMP_20170822.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Willis PM 10-2.5 Precision Results, pdf has summary table and SEM images ",
            "description": "Precision data from the SEM and SEM images from the samples. \n\nThis dataset is associated with the following publication:\nPeters, T., E. Sawvel, R. Willis, R. West, and G. Casuccio. Performance of Passive Samplers Analyzed by Computer Controlled Scanning Electron Microscopy to Measure PM10-2.5.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 50(0): 7581-7589, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1376844",
            "keyword": [
                "X-ray spectroscopy",
                "PM",
                "passive method",
                "cleveland",
                "microscopy",
                "particulate matter",
                "passive aerosol sampler",
                "single particle analysis"
            ],
            "contactPoint": {
                "fn": "Myriam Medina-Vera",
                "hasEmail": "mailto:medina-vera.myriam@epa.gov"
            },
            "distribution": [
                {
                    "title": "Willis_PM10-2.5 figures.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376844/Willis_PM10-2.5%20figures.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Willis PM 10-2.5 paper Copy of Precision results 11-17-15.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376844/Willis%20PM%2010-2.5%20paper%20Copy%20of%20Precision%20results%2011-17-15.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-01",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "data for Effects of an experimental water level drawdown on methane emissions",
            "description": "Time series of methane ebullition rates from 9 sites in Harsha Lake, Ohio, from May - Dec 2015. \n\nThis dataset is associated with the following publication:\nBeaulieu, J., A. Balz, M. Birchfield, J. Harrison, C. Nietch, M. Platz, S. Waldo, J. Walker, K. White, and J. Young. Effects of an experimental water-level drawdown on methane emissions from a eutrophic reservoir.   ECOSYSTEMS. Springer, New York, NY, USA, 21(4): 657-674, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1378469",
            "keyword": [
                "reservoirs",
                "impoundments",
                "water quality",
                "Methane"
            ],
            "contactPoint": {
                "fn": "Jake Beaulieu",
                "hasEmail": "mailto:beaulieu.jake@epa.gov"
            },
            "distribution": [
                {
                    "title": "BeaulieuJake_A-k0pk_data.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378469/BeaulieuJake_A-k0pk_data.txt",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2017-09-06",
            "references": [
                "https://doi.org/10.1007/s10021-017-0176-2"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1378469/documents/BeaulieuJake_A-k0pk_Metadata.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "biological relevance of reductions of testosterone production on the adverse effects of in utero phthalate combinations",
            "description": "RAW DATA, SAS FILES AND DATA MEANS. \n\nThis dataset is associated with the following publication:\nHowdeshell, K., C. Rider, V. Wilson , J. Furr , C. Lambright , and E. Gray. Dose addition models based on biologically-relevant reductions in fetal testosterone accurately predict postnatal reproductive tract alterations by a phthalate mixture in rats.   TOXICOLOGICAL SCIENCES. Society of Toxicology,    148(2): 488-502, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1377875",
            "keyword": [
                "Phthalates",
                "Mixtures",
                "dose addition",
                "in utero effects on reproductive development",
                "male rat"
            ],
            "contactPoint": {
                "fn": "Leon Gray",
                "hasEmail": "mailto:gray.earl@epa.gov"
            },
            "distribution": [
                {
                    "title": "megaphthalate f1 male malf DATA FILE SAS DATA 9 11 2017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377875/megaphthalate%20f1%20male%20malf%20DATA%20FILE%20SAS%20DATA%209%2011%202017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-30",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Conolly, R.B., Ankley, G.T., Cheng, WY., Mayo, M.L., Miller, D.H., Perkins, E.J., Villeneuve, D.L., and Watanable, K.H. (2017). Quantitative adverse outcome pathways and their application ot predictive toxicology. Environ. Sci. Technol. 51, 4661\u20134672",
            "description": "A publised mansucript describing a quantitative adverse outcome pathway (qAOP) and its relevance to risk assessment. This dataset is not publicly accessible because: This work describes computational modeling, not acquisition of laboratory data. It can be accessed through the following means: The mansucript is published in Environmental Science and Technology. Format: This ScienceHub entry is associated with the published manuscript:\r\n\r\nQuantitative Adverse Outcome Pathways and Their Application to\r\nPredictive Toxicology\r\nRory B. Conolly,*,\u2020 Gerald T. Ankley,\u2021 WanYun Cheng,\u2020 Michael L. Mayo,\u00a7 David H. Miller,\u2225\r\nEdward J. Perkins,\u00a7 Daniel L. Villeneuve,\u2021 and Karen H. Watanabe\u22a5\r\n\u2020U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research\r\nLaboratory, Integrated Systems Toxicology Division, Research Triangle Park, North Carolina 27709, United States\r\n\u2021U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research\r\nLaboratory, Mid-Continent Ecology Division, Duluth, Minnesota 55804, United States\r\n\u00a7Environmental Laboratory, U.S. Army Engineer Research and Development Center, Vicksburg, Mississippi 39180, United States\r\n\u2225U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research\r\nLaboratory, Mid-Continent Ecology Division, Grosse Isle, Michigan 48138, United States\r\n\u22a5School of Mathematical and Natural Sciences, Arizona State University, West Campus, Glendale, Arizona 85306, United States\r\n\r\nDOI: 10.1021/acs.est.6b06230\r\nEnviron. Sci. Technol. 2017, 51, 4661\u22124672. \n\nThis dataset is associated with the following publication:\nConolly, R., G. Ankley, W. Cheng, M. Mayo, D. Miller, E. Perkins, D. Villeneuve, and K. Watanabe. Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(8): 4661-4672, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1378322",
            "keyword": [
                "AOP",
                "qAOP",
                "hazard",
                "Risk",
                "computational model",
                "quantitative AOP",
                "adverse outcome pathway"
            ],
            "contactPoint": {
                "fn": "Rory Conolly",
                "hasEmail": "mailto:conolly.rory@epa.gov"
            },
            "distribution": [],
            "modified": "2017-03-29",
            "references": [
                "https://doi.org/10.1021/acs.est.6b06230"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Datasets will not be made accessible to the public due to the fact that they include household level data with PII.",
            "description": "Datasets will not be made accessible to the public due to the fact that they include household level data with PII. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Datasets will not be made accessible to the public due to the fact that they include household level data with PII. Format: Datasets will not be made accessible to the public due to the fact that they include household level data with PII. \n\nThis dataset is associated with the following publication:\nFulk , F., E. Haynes, T. Hilbert, D. Brown, D. Petersen , and T. Reponen. Comparison of stationary and personal air sampling with an air dispersion model for children\u2019s ambient exposure to manganese.   Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London,  UK,  online, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1378449",
            "keyword": [
                "Datasets will not be made accessible to the public due to the fact that they include household level data with PII.",
                "manganese",
                "ambient air"
            ],
            "contactPoint": {
                "fn": "Florence Fulk",
                "hasEmail": "mailto:fulk.florence@epa.gov"
            },
            "distribution": [],
            "modified": "2017-08-31",
            "references": [
                "https://doi.org/10.1038/jes.2016.30"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "An introduction to joint research by the USEPA and USGS on contaminants of emerging concern in source and treated drinking waters of the United States.",
            "description": "Paper serves as non-technical introduction to series of papers on the same drinking water study. \n\nThis dataset is associated with the following publication:\nKolpin, D., S. Glassmeyer, and E. Furlong. An introduction to joint research by the USEPA and USGS on contaminants of emerging concern in source and treated drinking waters of the United States.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 579: 1608\u20131609, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1378932",
            "keyword": [
                "drinking water",
                "source water",
                "pharmaceuticals",
                "microorganisms",
                "Per- and polyfluoroalkyl substances"
            ],
            "contactPoint": {
                "fn": "Susan Glassmeyer",
                "hasEmail": "mailto:glassmeyer.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Intro paper team picture.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378932/Intro%20paper%20team%20picture.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-09-07",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.03.052"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Flow and Rainfall Data used for SHC Headwatershed SWMM Calibration",
            "description": "Flow and rainfall data collected at the Shayler Crossing (SHC) stream monitoring station at 10 minute intervals over a two month period in 2009. \n\nThis dataset is associated with the following publication:\nLee, J., C. Nietch, and S. Panguluri. Drainage Area Characterization for Evaluating Green Infrastructure using the Storm Water Management Model.   HYDROLOGY AND EARTH SYSTEM SCIENCES. EGS,    22: 2615-2635, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1378947",
            "keyword": [
                "streamflow",
                "Rainfall",
                "Headwatershed scale",
                "Stormwater Modeling",
                "Spatial Discretization",
                "SWMM"
            ],
            "contactPoint": {
                "fn": "Christopher Nietch",
                "hasEmail": "mailto:nietch.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "FlowAndRainfallData_SHC-SWMM_SubcatchmentCharacterizationForGIModelingResearch.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378947/FlowAndRainfallData_SHC-SWMM_SubcatchmentCharacterizationForGIModelingResearch.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-06",
            "references": [
                "https://doi.org/10.5194/hess-2017-166"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for developing metamodels to assess the fate, transport, and bioaccumulation of organic chemicals in rivers. Chemicals have log Kow ranging from 3 to 14, and rivers have mean annual discharges ranging from 1.09 to 3240 m3/s. ",
            "description": "This dataset was developed to demonstrate how metamodels of high resolution, process-based models that simulate the fate, transport, and bioaccumulation of organic chemicals in rivers can be developed and applied for screening level exposure assessments. Chemicals of concern are assumed to be released from point sources (e.g., wastewater treatment works) and have log n-octanol/water partition coefficients (log Kow) ranging from 3 to 14. The rivers of concern have mean annual discharges ranging from 1.09 to 3240 m3/s. Five existing USEPA models are used to generate the required databases. The Chemical Transformation Simulator (CTS) and the High Throughput Stochastic Human Exposure and Dose Simulation Model (SHEDS-HT) are used to estimate the pchem properties and loading rates of the chemicals of interest, respectively. Using these data, the dissolved and total water concentrations, and total sediment concentrations for each chemical-loading combination in the rivers of interest are simulated using the Exposure Analysis Modeling System (EXAMS). Lastly, the Kow-based Aquatic BioAccumulation Model (KABAM) and the Bioaccumulation and Aquatic System Simulator (BASS) are used to estimate BCFs of periphyton and phytoplankton and BAFs of benthic invertebrates, zooplankton, and fish in the rivers of interest. Using these BCFs and BAFs and EXAMS dissolved water concentrations, expected whole-body concentrations of exposed fish and invertebrates are calculated for each chemical-loading-river combination. \n\nThis dataset is associated with the following publication:\nBarber, C., K. Isaacs, and C. Stevens. Developing and applying metamodels of high resolution process-based simulations for high throughput exposure assessment of organic chemicals in riverine ecosystems.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 605606: 471-481, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1379220",
            "keyword": [
                "integrated modeling",
                "fate and transport",
                "bioaccumulation",
                "Trophic transfer",
                "Brominated flame retardants",
                "BASS",
                "CTS",
                "EXAMS",
                "KABAM",
                "SHEDS-HT"
            ],
            "contactPoint": {
                "fn": "Mahlon Barber",
                "hasEmail": "mailto:barber.craig@epa.gov"
            },
            "distribution": [
                {
                    "title": "A-4xh5_EXAMS-KABAM.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379220/A-4xh5_EXAMS-KABAM.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "A-4xh5_BASS.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379220/A-4xh5_BASS.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-06",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2017.06.198"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1379220/documents/A-4xh5_data_dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Evaluation of a Low-Cost Volatile Organic Compound Passive Sampling Method and Laboratory Intercomparison",
            "description": "This project \u201cfenceline Passive Sampler and Sensor Studies\u201d contains information on several related field efforts that examine use of passive sorbent tubes and prototype fenceline sensor technologies near sources of volatile organic compounds, with particular emphasis on the compound benzene.  There are three primary data sets included with multiple journal articles linked to these data sets.  The data sets with metadata and data dictionaries are as follows:\n\nCorpus Christi Passive Sampler Study data set:  Two week duration time-integrated passive sampler concentration data, identity of passive samplers, sampling date and time periods for passive deployments, GPS locations of passive samplers, benzene data from automated gas chromatograph (TCEQ site), metrological data (TCEQ site).\n\nMultiregional Passive Sampler Study data set:  Two week duration time-integrated passive sampler concentration data, identity of passive samplers, sampling date and time periods for passive deployments, GPS locations of passive samplers, metrological data (local airports).\n\nPhiladelphia Sensor Studies data sets:  Baseline corrected five-minute time-resolved fenceline sensor (concetrion and wind field) data for (1) alpha version prototype system and (2) beta version prototype system, sampling time periods for utilized sensor deployments, GPS locations of all sensors,  five-minute time-resolved concentration data from co-located optical spectroscopy system (City of Philadelphia Air Measurements Services), metrological data (Philadelphia airport). \n\nThis dataset is associated with the following publications:\nThoma , E., H. Brantley , K. Oliver , D. Whitaker , S. Mukerjee , B. Mitchell , B. Squier , T. Wu , E. Escobar, T. Cousett, C. Gross-Davis , H. Schmidt , D. Sosna, and H. Weiss. South Philadelphia Passive Sampler and Sensor Studies.   JOURNAL OF AIR AND WASTE MANAGEMENT. Air & Waste Management Association, Pittsburgh, PA, USA, 66(10): 959-970, (2016).\nMukerjee , S., L. Smith, E. Thoma , K. Oliver , D. Whitaker , T. Wu , and C. Stallings. Spatial analysis of volatile organic compounds in South Philadelphia using passive samplers.   JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION. Air & Waste Management Association, Pittsburgh, PA, USA, 66(5): 492-498, (2016).\nEisele , A., S. Mukerjee , L. Smith, E. Thoma , D. Whitaker , K. Oliver , T. Wu , M. Colon , L. Alston, T. Cousett, M. Miller , D. Smith , and C. Stallings. Volatile organic compounds at oil and natural gas production well pads in Colorado and Texas using passive samplers.   JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION. Air & Waste Management Association, Pittsburgh, PA, USA, 66(4): 412-419, (2016).\nOliver, K., T. Cousett, D. Whitaker, L. Smith, S. Mukerjee, C. Stallings, E. Thoma, L. Alston, M. Colon, T. Wu, and S. Henkle. Sample integrity evaluation and EPA Method 325B interlaboratory comparison for select volatile organic compounds collected diffusively on Carbopack X sorbent tubes.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 163: 99-106, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1369030",
            "keyword": [
                "Passive Samplers",
                "Fenceline Monitoring",
                "Sensors",
                "SPod",
                "benzene"
            ],
            "contactPoint": {
                "fn": "Eben Thoma",
                "hasEmail": "mailto:thoma.eben@epa.gov"
            },
            "distribution": [
                {
                    "title": "Multiregional Passive Sampler Study Data Set and Dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1369030/Multiregional%20Passive%20Sampler%20Study%20Data%20Set%20and%20Dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "allReport_11_26_kdo_sorted.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1369030/allReport_11_26_kdo_sorted.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Field_Descriptions.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1369030/Field_Descriptions.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Uptake_Rates.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1369030/Uptake_Rates.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Molecular_Weights.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1369030/Molecular_Weights.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-04-27",
            "references": [
                "https://doi.org/10.1080/10962247.2016.1184724",
                "https://doi.org/10.1080/10962247.2016.1147505",
                "https://doi.org/10.1080/10962247.2016.1141808",
                "https://doi.org/10.1016/j.atmosenv.2017.05.042"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Microbial raw data for UV-C LED disinfection study",
            "description": "This study evaluated ultraviolet (UV) light emitting diodes (LEDs) emitting at 260 nm, 280 nm, and the combination of 260|280 nm together for their efficacy at inactivating Escherichia. coli, MS2 coliphage, human adenovirus type 2 (HAdV2), and Bacillus pumilus spores; research included an evaluation of genomic damage. Inactivation by the LEDs was compared with the efficacy of conventional UV sources, the low-pressure (LP) and medium-pressure (MP) mercury vapor lamps. The work also calculated the electrical energy per order of reduction of the microorganisms by the five UV sources.For E. coli, all five UV sources yielded similar inactivation rates. For MS2 coliphage, the 260 nm LED was most effective. For HAdV2 and B. pumilus, the MP UV lamp was significantly more effective than the LP UV and UVC LED sources. When considering electrical energy per order of reduction, the LP UV lamp was the most efficient for E. coli and MS2, and the MPUV and LPUV were equally efficient for HAdV2 and B. pumilus spores. Among the UVC LEDs, the 280 nm LED unit required the least energy per log reduction of E. coli and HAdV2. The 280 nm and 260|280 nm LED units were equally efficient per log reduction of B. pumilus spores, and the 260 nm LED unit required the lowest energy per order of reduction of MS2 coliphage. The combination of the 260 nm and 280 nm UV LED wavelengths was also evaluated for potential synergistic effects. No dual-wavelength synergy was detected for inactivation of all four microorganisms, nor for DNA/RNA damage. \n\nThis dataset is associated with the following publication:\nBeck, S., H. Ryu, L. Boczek, J. Cashdollar, K. Jeanis, J. Rosenblum, O. Lawal, and K. Linden. Evaluating UV-C LED disinfection performance and investigating potential dual-wavelength synergy.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 109: 207-216, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1379484",
            "keyword": [
                "Combined Wavelengths",
                "Electrical Energy per Order",
                "Human Adenovirus type 2",
                "Bacillus pumilus spores",
                "Nucleic Acid Damage"
            ],
            "contactPoint": {
                "fn": "Hodon Ryu",
                "hasEmail": "mailto:ryu.hodon@epa.gov"
            },
            "distribution": [
                {
                    "title": "Adenovirus_UV LED_ICC-qPCR and quantal results.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379484/Adenovirus_UV%20LED_ICC-qPCR%20and%20quantal%20results.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Adenovirus_UV LED_MPN data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379484/Adenovirus_UV%20LED_MPN%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Bacillus pumilus spore_UV LED.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379484/Bacillus%20pumilus%20spore_UV%20LED.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-06",
            "references": [
                "https://doi.org/10.1016/j.watres.2016.11.024"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The effectiveness of Light Rail transit in achieving regional CO2 emissions targets is linked to building energy use: insights from system dynamics modeling",
            "description": "Dataset is comprised of a series of journal publications  (in pdf form) that use system dynamics modeling to analyze the interactions among transportation, land use, economy and resources (water, energy) to yield sustainability outcomes, with a focus on achieving energy sustainability goals. In particular, the paper analyzes the tradeoffs and cumulative impacts of energy use across building and transportation types under a range of transportation and land use scenarios. In addition to the articles themselves, the dataset includes figures from the articles and a link to the model documentation, as well as tabular sources of input and calibration data and the full set of model output data. \n\nThis dataset is associated with the following publication:\nProcter, A., A. Bassi, J. Kolling, L. Cox, N. Flanders, N. Tanners, and R. Araujo. The effectiveness of Light Rail transit in achieving regional CO2 emissions targets is linked to building energy use: insights from system dynamics modeling.   CLEAN TECHNOLOGIES ENVIRONMENTAL POLICY. Springer, New York, NY, USA, 19(5): 1459-1474, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1377842",
            "keyword": [
                "energy",
                "emissions",
                "buildings",
                "integrated approaches",
                "sustainability",
                "light rail"
            ],
            "contactPoint": {
                "fn": "Rochelle Araujo",
                "hasEmail": "mailto:araujo.rochelle@epa.gov"
            },
            "distribution": [
                {
                    "title": "Procter et al. 2017_The effectiveness of light rail transit.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377842/Procter%20et%20al.%202017_The%20effectiveness%20of%20light%20rail%20transit.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Procter_Figures for Energy Paper.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377842/Procter_Figures%20for%20Energy%20Paper.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "D-O LRP SD Model Documentation Appendix B.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377842/D-O%20LRP%20SD%20Model%20Documentation%20Appendix%20B.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "D-O LRP Model_Base Scenario Outputs.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377842/D-O%20LRP%20Model_Base%20Scenario%20Outputs.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Historical and Projected Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377842/Historical%20and%20Projected%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=310977",
                    "accessURL": "https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=310977"
                }
            ],
            "modified": "2017-08-22",
            "references": [
                "https://doi.org/10.1007/s10098-017-1343-z"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Newton Decatur AL water sample polyfluor compound discovery",
            "description": "All the pertinent information for recreation of the published (hopefully) tables and figures. \n\nThis dataset is associated with the following publication:\nNewton, S., R. McMahen, J. Stoeckel, M. Chislock, A. Lindstrom, and M. Strynar. Novel Polyfluorinated Compounds Identified Using High Resolution Mass Spectrometry Downstream of Manufacturing Facilities near Decatur, Alabama.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(3): 1544-1552, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1375406",
            "keyword": [
                "non-targeted analysis",
                "per and polyfluorinated",
                "time of flight mass spectrometry"
            ],
            "contactPoint": {
                "fn": "Mark Strynar",
                "hasEmail": "mailto:strynar.mark@epa.gov"
            },
            "distribution": [
                {
                    "title": "Newton Sciencehub entry data 161003.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375406/Newton%20Sciencehub%20entry%20data%20161003.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-10-04",
            "references": [
                "https://doi.org/10.1021/acs.est.6b05330"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Haw River PFCs Data Set",
            "description": "PFAS concentrations in river and drinking water in and around the Haw River in North Carolina. \n\nThis dataset is associated with the following publication:\nSun, M., E. Arevalo, M. Strynar, A. Lindstrom, M. Richardson, B. Kearns, A. Pickett, C. Smith, and D.R.U. Knappe. Legacy and Emerging Perfluoroalkyl Substances Are Important Drinking Water Contaminants in the Cape Fear River Watershed of North Carolina.   Environmental Science & Technology Letters. American Chemical Society, Washington, DC, USA, 3(12): 415-419, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1375404",
            "keyword": [
                "Watershed",
                "water treatment",
                "occurrence and fate",
                "perfluoroalkyl",
                "PFAS"
            ],
            "contactPoint": {
                "fn": "Andrew Lindstrom",
                "hasEmail": "mailto:lindstrom.andrew@epa.gov"
            },
            "distribution": [
                {
                    "title": "ES-TL figures.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375404/ES-TL%20figures.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "mass flow.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375404/mass%20flow.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "adsorption kinetics.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375404/adsorption%20kinetics.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-22",
            "references": [
                "https://doi.org/10.1021/acs.estlett.6b00398"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Metabolomics for Informing Adverse Outcome Pathways: Androgen Receptor Activation and the Pharmaceutical Spironolactone",
            "description": "Metabolite Input Files for Determining Biochemical Pathways Impacted by Spironolactone Exposures of Fathead Minnows (Pimephales promelas) Using the Mummichog Software package. \n\nThis dataset is associated with the following publication:\nDavis, J., D. Skelton, D. Ekman, C. LaLone, G. Ankley, G. Ankley, J. Cavallin, D. Villeneuve, and T. Collette. Metabolomics for Informing Adverse Outcome Pathways: Androgen Receptor Activation and the Pharmaceutical Spironolactone.   AQUATIC TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 184(0): 103-115, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1378557",
            "keyword": [
                "spironolactone",
                "AOPs",
                "Mummichog",
                "mass spectrometry",
                "metabolomics"
            ],
            "contactPoint": {
                "fn": "Drew Ekman",
                "hasEmail": "mailto:ekman.drew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Davis et al. 2017_Input Files.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378557/Davis%20et%20al.%202017_Input%20Files.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-14",
            "references": [
                "https://doi.org/10.1016/j.aquatox.2017.01.001"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1378557/documents/Data%20Dictionary%20for%20Davis%20et%20al.%202017_Input%20File.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "UCMR3 data",
            "description": "Zipped UCMR3 data. \n\nThis dataset is associated with the following publication:\nHU, X., D. Andrews, T. Bruton, A. Lindstrom, L.  Schaider, P. Grandjean, R. Lohmann, C. Carignan, A. Blum, S. Balan, E. Sunderland, and C. Higgins. Detection of Poly- and Perfluoroalkyl Substances (PFASs) in U.S. Dinking Water: Linked to Industrial Sites, Military fire Training Areas and Wastewater Treatment Plants.   Environmental Science & Technology Letters. American Chemical Society, Washington, DC, USA, 3(0): 344-350, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1380229",
            "keyword": [
                "PFOS",
                "PFOA",
                "PFNA",
                "PFHxS",
                "Polyfluorinated Alkyl Substances (PFAS)",
                "UCMR3"
            ],
            "contactPoint": {
                "fn": "Andrew Lindstrom",
                "hasEmail": "mailto:lindstrom.andrew@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/dwucmr/occurrence-data-unregulated-contaminant-monitoring-rule#3",
                    "accessURL": "https://www.epa.gov/dwucmr/occurrence-data-unregulated-contaminant-monitoring-rule#3"
                }
            ],
            "modified": "2017-01-01",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "In vitro bioaccessibility of copper azole following simulated dermal transfer from pressure-treated wood",
            "description": "In vitro bioaccessibility of copper azole following simulated dermal transfer from pressure-treated wood. \n\nThis dataset is associated with the following publication:\nGriggs, J., K. Rogers, C. Nelson, T. Luxton, W. Platten, and K. Bradham. In vitro bioaccessibility of copper azole following simulated dermal transfer from pressure-treated wood.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 598: 413\u2013420, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1380225",
            "keyword": [
                "Bioaccessibility",
                "Human Exposure",
                "Micronized Copper",
                "stomach fluid",
                "wood preservative"
            ],
            "contactPoint": {
                "fn": "Kim Rogers",
                "hasEmail": "mailto:rogers.kim@epa.gov"
            },
            "distribution": [
                {
                    "title": "A-w0wk_JGriggs Data for science hub.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1380225/A-w0wk_JGriggs%20Data%20for%20science%20hub.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-03-01",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2017.03.227"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Fluorinated Compounds in U.S. Fast Food Packaging",
            "description": "Paper samples, paper extracts (known), paper extracts (unknown). \n\nThis dataset is associated with the following publication:\nSchaider, L., S. Balan, A. Blum, D. Andrews, M. Strynar, M. Dickinson, D. Lunderberg, J. Lang, and G. Peaslee. Fluorinated Compounds in U.S. Fast Food Packaging.   Environmental Science & Technology Letters. American Chemical Society, Washington, DC, USA, 4(3): 105\u2013111, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1380227",
            "keyword": [
                "polyfluorinated compounds",
                "paper board",
                "food contact",
                "fluorinated",
                "food contact packaging",
                "non-targeted analysis",
                "polyfluorinated"
            ],
            "contactPoint": {
                "fn": "Mark Strynar",
                "hasEmail": "mailto:strynar.mark@epa.gov"
            },
            "distribution": [
                {
                    "title": "10-3-16 Paper samples for PFAS extraction.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1380227/10-3-16%20Paper%20samples%20for%20PFAS%20extraction.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "10-14-16 paper extracts known PFAS.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1380227/10-14-16%20paper%20extracts%20known%20PFAS.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "10-19-16 paper extracts unknowns.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1380227/10-19-16%20paper%20extracts%20unknowns.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-18",
            "references": [
                "https://doi.org/10.1021/acs.estlett.6b00435"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Transitions for fipronil quant in surface water, Summary of Current Fipronil Water Data and Water Data for WWTPs",
            "description": "Comparison of fipronil sources in North Carolina surface water and identification of a novel fipronil transformation product in recycled wastewater. \n\nThis dataset is associated with the following publication:\nMcMahen, R.L., M. Strynar , L. McMillan, E. DeRose, and A. Lindstrom. Comparison of fipronil sources in North Carolina surface water and identification of a novel fipronil transformation product in recycled wastewater.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 569570: 880-887, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1380228",
            "keyword": [
                "water reuse",
                "novel transformation products",
                "biomarker of exposure",
                "fipronil",
                "pesticide",
                "wastewater"
            ],
            "contactPoint": {
                "fn": "Mark Strynar",
                "hasEmail": "mailto:strynar.mark@epa.gov"
            },
            "distribution": [
                {
                    "title": "4-23-2015 transitions for fipronil quant in surface water on acuity.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1380228/4-23-2015%20transitions%20for%20fipronil%20quant%20in%20surface%20water%20on%20acuity.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "7-25-14 Summary of current fipronil water data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1380228/7-25-14%20Summary%20of%20current%20fipronil%20water%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "8-7-14 Summary of current fipronil water data for WWTPs.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1380228/8-7-14%20Summary%20of%20current%20fipronil%20water%20data%20for%20WWTPs.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-18",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.05.085"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Ingestion of swimming pool water by recreational",
            "description": "Swimming pool water ingestion data. \n\nThis dataset is associated with the following publication:\nDufour, A., L. Wymer, M. Magnuson, T. Behymer, and R. Cantu. Ingestion of Swimming Pool Water by Recreational Swimmers.   JOURNAL OF WATER AND HEALTH. IWA Publishing, London,  UK, 15(3): 1-10, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1378318",
            "keyword": [
                "cyanuric acid",
                "swimming",
                "water ingestion",
                "water"
            ],
            "contactPoint": {
                "fn": "Alfred Dufour",
                "hasEmail": "mailto:dufour.alfred@epa.gov"
            },
            "distribution": [
                {
                    "title": "Ingestion Data Final_include TIW_last_ (002).xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378318/Ingestion%20Data%20Final_include%20TIW_last_%20%28002%29.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2002-07-01",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Arsenic Speciation in US Consumed Rice with an Emphasis on Bioaccessiblity and the Exposure Assessment Implications Dataset",
            "description": "Arsenic Speciation in US Consumed Rice with an Emphasis on Bioaccessiblity and the Exposure Assessment Implications. \n\nThis dataset is associated with the following publication:\nMantha, M., E. Yeary, J. Trent, P. Creed , K. Kubachka, T. Hanley, N. Ahockey, D. Heitkemper, J. Caruso, J. Xue , G. Rice , L. Wymer , and J. Creed. Journal Article-\"Estimating Inorganic Arsenic Exposure from\r\n\t\tU.S.Rice and Total Water Intakes\".   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 125(5): 1-10, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1389260",
            "keyword": [
                "arsenic",
                "rice",
                "ICP-MS",
                "Speciation",
                "drinking water",
                "Exposure Assessment",
                "inorganic arsenic"
            ],
            "contactPoint": {
                "fn": "John Creed",
                "hasEmail": "mailto:creed.jack@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data for Figure 2 Drinking Water Utility vs rice.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1389260/Data%20for%20Figure%202%20Drinking%20Water%20Utility%20vs%20rice.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Data for Table S6.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1389260/Data%20for%20Table%20S6.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Data for Table S7.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1389260/Data%20for%20Table%20S7.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Data for Table S8.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1389260/Data%20for%20Table%20S8.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 2 with data 5-15-13.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1389260/Figure%202%20with%20data%205-15-13.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-04-27",
            "references": [
                "https://doi.org/10.1289/ehp418"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Global Mercury Observation System (GMOS) surface observation data.",
            "description": "GMOS global surface elemental mercury (Hg0) observations from  2013 & 2014. \n\nThis dataset is associated with the following publication:\nSprovieri, F., N. Pirrone, M. Bencardino, F. D'Amore, F. Carbone, S. Cinnirella, V. Mannarino, M. Landis, R. Ebinghus, A. Weigelt, E. Brunke, C. Labuschagne, L. Martin, J. Munthe, I. Wangberg, P. Artaxo, F. Morais, W. Cairns, C. Barbante, M.d.C. Dieguez, P.E. Garcia, A. Dommergue, H. Angot, O. Magand, H. Skov, M. Horvat, J. Kotnik, K.A. Read, L. Mendes Neves, B. Manfred Gawlik, F. Sena, V. Arckadievich Obolkin, D. Wip, X.B. Feng, H. Zhang, X. Fu, N. Mashyanov, R. Ramachandran, D. Cossa, J. Knoery, N. Marusczak, M. Nerentrorp, and C. Norstrom. Atmospheric Mercury Concentrations Observed at Ground-Based Monitoring Sites Globally Distributed in the Framework of the GMOS Network.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 16(0): 11915-11935, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1379479",
            "keyword": [
                "Elemental Gaseous Mercury",
                "Global Observation System",
                "Tekran 2537"
            ],
            "contactPoint": {
                "fn": "Matthew Landis",
                "hasEmail": "mailto:landis.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Yearly Statistics 2013&2014.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379479/Yearly%20Statistics%202013%262014.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Monthly Statistics 2013&2014.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379479/Monthly%20Statistics%202013%262014.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-30",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dearborn GC-MS organic speciation data  ",
            "description": "Ambient particulate matter organic speciation data from July - August, 2011. \n\nThis dataset is associated with the following publication:\nLynam, M., T. Dvonch, J. Turlington, D. Olson, and M. Landis. Combustion-Related Organic Species in Temporally Resolved Urban Airborne Particulate Matter.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 0(0): 1-33, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1379480",
            "keyword": [
                "particulate matter",
                "PAH",
                "Hopane",
                "Point source",
                "Mobile source",
                "Urban environment"
            ],
            "contactPoint": {
                "fn": "Matthew Landis",
                "hasEmail": "mailto:landis.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Dearborn_organic_speciation.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379480/Dearborn_organic_speciation.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-02-01",
            "references": [
                "https://doi.org/10.1007/s11869-017-0482-z"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Puerto Rico Above Ground Biomass Map, 2000",
            "description": "This image dataset details the U.S. Commonwealth of Puerto Rico above-ground forest biomass (AGB) (baseline 2000) developed by the United States (US) Environmental Protection Agency (EPA). The USEPA AGB product (15 m) was created to support the development of landscape watershed predictor metrics for sediment and nutrient loadings associated with stream reaches. Above-ground forest biomass was estimated at a 15 m spatial resolution implementing methodology first posited by the Woods Hole Research Center where they developed the National Biomass and Carbon Dataset (NBCD2000) \u2500 an above-ground forest biomass map (30 m) for the conterminous United States. For EPA\u2019s effort, spatial predictor layers for AGB estimation included derived products from the United States Geologic Survey (USGS) National Land Cover Dataset 2001 (NLCD) cover type and tree canopy density data, the USGS Gap Analysis Program (GAP) forest type classification data, USGS National Elevation Dataset (NED) topographic data, and the National Aeronautical and Space Administration\u2019s (NASA\u2019s) Shuttle Radar Topography Mission (SRTM) tree height data. These predictor variables and Forest Inventory and Analysis (FIA) response variables (observed canopy height and AGB) were related through multivariate tree-based regression models. Units for this AGB map are in Mg/ha for each 15m pixel. Mean biomass (forest only) for the 15 m pixels was 72.59 Mg/ha (\u03c3 = 26.83). This estimate is close in agreement to an assessment of structure and condition of PR forests (2003) (Brandeis, 2006) where mean AGB was estimated at 80 Mg/ha. \r\n\r\nBrandeis, T.J., M.B. Delaney, R. Parresol, L. Royer, 2006. Development of equations for predicting Puerto Rican subtropical dry forest biomass and volume, Forest Ecology and Management, 233:133-142. This dataset is not publicly accessible because: This data exceeds one GB in size and cannot be stored directly on ScienceHub. It can be accessed through the following means: ftp://newftp.epa.gov/Exposure/A-tqkc/. Format: This dataset is in an ERDAS Imagine *.img format which is easily converted to other formats in software packages such as ESRI ArcMap. \n\nThis dataset is associated with the following publication:\nIiames , J., J. Riegel, and R. Lunetta. The Development and Evaluation of a High-Resolution Above Ground Biomass Product for the Commonwealth of Puerto Rico (2000).   Ecosystem Services. Elsevier Online, New York, NY, USA, 83(4): 293-306, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1389273",
            "keyword": [
                "Puerto Rico",
                "Forests",
                "Aboveground biomass",
                "Shuttle",
                "radar",
                "MODIS"
            ],
            "contactPoint": {
                "fn": "John Iiames",
                "hasEmail": "mailto:iiames.john@epa.gov"
            },
            "distribution": [],
            "modified": "2012-12-20",
            "references": [
                "https://doi.org/10.14358/pers.83.4.293"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1389273/documents/DataDictionary_PRUSVI.txt",
            "describedByType": "text/plain",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Global Mercury Observation System (GMOS) surface observation data from around the world.",
            "description": "GMOS Network Data. This dataset is associated with the following publication:\nDe Simone, F., P. Artaxo, M. Bencardino, S. Cinnirella, F. Carbone, F. D'Amore, A. Dommergue, X. Bin Feng, C. Gencarelli, I. Hedgecock, M. Landis, F. Sprovieri, N. Suzuki, I. Wangberg, and N. Pirrone. Particulate-phase mercury emissions from biomass burning and impact on resulting deposition: a modelling assessment.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 17: 1881-1899, (2017). NOTE: This dataset has been removed from public access due to revocation. Please refer inquiries regarding this dataset to the listed contact person.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1379481",
            "keyword": [
                "Particulate Phase Mercury",
                "Wildland Fire",
                "Global Fire Emissions Database",
                "ECHMERIT",
                "MOZART"
            ],
            "contactPoint": {
                "fn": "Matthew Landis",
                "hasEmail": "mailto:landis.matthew@epa.gov"
            },
            "distribution": [],
            "modified": "2016-07-29",
            "references": null,
            "publisher": {
                "name": "U.S. Environmental Protection Agency",
                "subOrganizationOf": {
                    "name": "U.S. Government"
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Sustainable pathway to furanics from biomass via heterogeneous organo-catalysis",
            "description": "Electronic supplementary information provides all the data. \n\nThis dataset is associated with the following publication:\nVarma, R., M. Nadagouda, S. Verma, R.B.N. Baig, and C. Len. Sustainable pathway to furanics from biomass via heterogeneous organo-catalysis.   GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge,  UK, 19(1): 164-168, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1389321",
            "keyword": [
                "Sustainable pathway",
                "Heterogeneous catalysis",
                "biomass",
                "Furonics",
                "heterogeneous",
                "Organocatalysis"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://pubs.rsc.org/en/content/articlehtml/2017/gc/c6gc02551j",
                    "accessURL": "https://pubs.rsc.org/en/content/articlehtml/2017/gc/c6gc02551j"
                }
            ],
            "modified": "2017-01-13",
            "references": [
                "https://doi.org/10.1039/c6gc02551j",
                "https://www.rsc.org/suppdata/c6/gc/c6gc02551j/c6gc02551j1.pdf"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Photocatalytic oxidation of aromatic amines using MnO2@g-C3N4",
            "description": "An efficient and direct oxidation of aromatic amines to aromatic azo-compounds has been achieved using a MnO2@g-C3N4 catalyst under visible light as a source of energy at room temperature. \n\nThis dataset is associated with the following publication:\nVerma, S., and R. Varma. Photocatalytic oxidation of aromatic amines using MnO2@g-C3N4.   Advanced Materials Letters. VBRI Press,   SWEDEN, 8(7): 754-758, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1389322",
            "keyword": [
                "Graphitic carbon nitride",
                "manganese dioxide",
                "aromatic azo-compounds",
                "photo-catalyst",
                "Heterogeneous catalysis"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "Adv. Mater. Letters- Vol. 8 pp754-756 (2017)-Photocat. Oxdn. of Aromatic Amines using MnO2@g-C3N4.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1389322/Adv.%20Mater.%20Letters-%20Vol.%208%20pp754-756%20%282017%29-Photocat.%20Oxdn.%20of%20Aromatic%20Amines%20using%20MnO2%40g-C3N4.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2017-09-07",
            "references": [
                "https://doi.org/10.5185/amlett.2017.1453",
                "https://www.vbripress.com/aml/volumes/issusenavigation/8/7/July",
                "https://pasteur.epa.gov/uploads/10.23719/1389322/documents/Supporting%20Information-Advanced%20Materials%20Letters.docx"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1389322/documents/Adv.%20Mater.%20Letters-%20Vol.%208%20pp754-756%20%282017%29-Photocat.%20Oxdn.%20of%20Aromatic%20Amines%20using%20MnO2%40g-C3N4.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Photocatalytic C-H activation of Hydrocarbons over VO@g-C3N4",
            "description": "A highly selective and sustainable method has been developed for the oxidation of methyl arenes and their analogues. The VO@g-C3N4 catalyst is very efficient in the C-H activation and oxygen insertion reaction resulting in formation of the corresponding carbonyl compounds and phenols. \n\nThis dataset is associated with the following publication:\nVerms, S., R.B.N. Baig, M. Nadagouda, and R. Varma. Photocatalytic C\u2013H Activation of Hydrocarbons over VO@g-C3N4.   ACS Sustainable Chemistry & Engineering. American Chemical Society, Washington, DC, USA, 4(4): 2333-2336, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1389542",
            "keyword": [
                "Graphitic carbon nitride",
                "Heterogeneous catalysis",
                "photo-catalyst",
                "Vanadium oxide",
                "C-H Activation"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://pubs.acs.org/doi/suppl/10.1021/acssuschemeng.6b00006",
                    "accessURL": "https://pubs.acs.org/doi/suppl/10.1021/acssuschemeng.6b00006"
                }
            ],
            "modified": "2016-04-13",
            "references": [
                "https://doi.org/10.1021/acssuschemeng.6b00006",
                "https://pubs.acs.org/doi/abs/10.1021/acssuschemeng.6b00006",
                "https://pasteur.epa.gov/uploads/10.23719/1389542/documents/sc-2016-00006k-Re-Revised%20Supplementary%20Information.docx"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Hydroxylation of Benzene via C-H Activation Using Bimetallic CuAg@g-C3N4",
            "description": "Bimetallic CuAg@g-C3N4 catalyst system has been designed and synthesized by impregnating copper and silver nanoparticles over the graphitic carbon nitride surface. Its application has been demonstrated in the hydroxylation of benzene under visible light. \n\nThis dataset is associated with the following publication:\nVerma, S., R.B.N. Baig, M. Nadagouda, and R. Varma. Hydroxylation of Benzene via C-H Activation Using Bimetallic CuAg@g-C3N4.   ACS Sustainable Chemistry & Engineering. American Chemical Society, Washington, DC, USA, 5(5): 3637-3640, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1389543",
            "keyword": [
                "Graphitic carbon nitride",
                "Bimetallic heterogeneous catalyst",
                "Hydroxylation of benzene",
                "Visible light",
                "C-H Activation"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://pubs.acs.org/doi/abs/10.1021/acssuschemeng.7b00772",
                    "accessURL": "https://pubs.acs.org/doi/abs/10.1021/acssuschemeng.7b00772"
                }
            ],
            "modified": "2017-05-16",
            "references": [
                "https://doi.org/10.1021/acssuschemeng.7b00772",
                "https://pubs.acs.org/doi/abs/10.1021/acssuschemeng.7b00772",
                "https://pasteur.epa.gov/uploads/10.23719/1389543/documents/sc-2017-007729.R1-Supporting%20Information.docx"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Fixation of carbon dioxide into dimethyl carbonate over titanium-based zeolitic thiophene-benzimidazolate framework",
            "description": "A titanium-based zeolitic thiophene-benzimidazolate framework has been designed for the direct synthesis of dimethyl carbonate (DMC) from methanol and carbon dioxide. The developed catalyst activates carbon dioxide and delivers over 16% yield of DMC without the use of any dehydrating agent or requirement for azeotropic distillation. \n\nThis dataset is associated with the following publication:\nVarma, R., M. Nadagouda, S. Verma, and R.B.N. Baig. Fixation of carbon dioxide into dimethyl carbonate over titanium-based zeolitic thiophene-benzimidazolate framework.   Scientific Reports. Nature Publishing Group, London,  UK, issue}: 655, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1389544",
            "keyword": [
                "carbon dioxide",
                "dimethyl carbonate",
                "titanium-based",
                "zeolitic thiophene-benzimidazolate framework"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.nature.com/articles/s41598-017-00736-1",
                    "accessURL": "https://www.nature.com/articles/s41598-017-00736-1"
                }
            ],
            "modified": "2017-06-16",
            "references": [
                "https://doi.org/10.1038/s41598-017-00736-1",
                "https://www.nature.com/articles/s41598-017-00736-1",
                "https://pasteur.epa.gov/uploads/10.23719/1389544/documents/SREP-16-53348-Supporting%20Information.pdf"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A sustainable approach to empower the bio-based future: upgrading of biomass via process intensification",
            "description": "An economically viable and environmentally benign continuous flow intensified process has been developed that demonstrates its ability to upgrade biomass into potential biofuels, solvents, and pharmaceutical feedstocks using a bimetallic AgPd@g-C3N4 catalyst. \n\nThis dataset is associated with the following publication:\nVarma, R., M. Gonzalez, S. Verma, and K. Tadele. A sustainable approach to empower the bio-based future: upgrading of biomass via process intensification.   GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge,  UK, 19(7): 1624-1627, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1389545",
            "keyword": [
                "Graphitic carbon nitride",
                "biomass",
                "bio-based future",
                "process intensification",
                "sustainable"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://pubs.rsc.org/en/content/articlelanding/2017/gc/c6gc03568j#!divAbstract",
                    "accessURL": "https://pubs.rsc.org/en/content/articlelanding/2017/gc/c6gc03568j#!divAbstract"
                }
            ],
            "modified": "2017-04-25",
            "references": [
                "https://doi.org/10.1039/c6gc03568j",
                "https://www.rsc.org/suppdata/c6/gc/c6gc03568j/c6gc03568j1.pdf"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "European Centre for Medium-Range Weather Forecasts",
            "description": "Global sea surface temperature (SST) anomalies can affect terrestrial precipitation via ocean-atmosphere interaction known as climate teleconnection. Non-stationary and non-linear characteristics of the ocean-atmosphere system make the identification of the teleconnection signals difficult to be detected at a local scale as it could cause large uncertainties when using linear correlation analysis only. This paper explores the relationship between global SST and terrestrial precipitation with respect to long-term non-stationary teleconnection signals during 1981-2010 over three regions in North America and one in Central America. Empirical mode decomposition as well as wavelet analysis is utilized to extract the intrinsic trend and the dominant oscillation of the SST and precipitation time series in sequence.  After finding possible associations between the dominant oscillation of seasonal precipitation and global SST through lagged correlation analysis, the statistically significant SST regions are extracted based on the correlation coefficient. With these characterized associations, individual contribution of these SST forcing regions linked to the related precipitation responses are further quantified through nonlinear modeling with the aid of extreme learning machine. Results indicate that the non-leading SST regions also contribute a salient portion to the terrestrial precipitation variability compared to some known leading SST regions. In some cases, these estimated contributions reveals some clues of the coupling interactions between oceanic and atmospheric processes. \n\nThis dataset is associated with the following publication:\nChang, N., S. Imen, K. Bai, and J. Yang. Multi-scale Quantitative Precipitation Forecasting Using Nonlinear and Nonstationary Teleconnection Signals and Artificial Neural Network Models.   JOURNAL OF HYDROLOGY. Elsevier Science Ltd, New York, NY, USA, 548: 305-321, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1389860",
            "keyword": [
                "Sea Surface Temperature",
                "climate change",
                "precipitation",
                "Teleconnection",
                "north america",
                "Central America."
            ],
            "contactPoint": {
                "fn": "Yingping Yang",
                "hasEmail": "mailto:yang.jeff@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.esrl.noaa.gov/psd/data/gridded/data.gpcc.html",
                    "accessURL": "https://www.esrl.noaa.gov/psd/data/gridded/data.gpcc.html"
                }
            ],
            "modified": "2017-05-15",
            "references": [
                "https://doi.org/10.1016/j.jhydrol.2017.03.003"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "U.S. Domestic Cats as Sentinels for Perfluoroalkyl Substances",
            "description": "Legacy PFC work.  Data stored in Phillip Bost\u2019s Lab Notebook #1778; Room D286 (Lindstrom) RTP, NC EPA office. \n\nThis dataset is associated with the following publication:\nBost, P., M. Strynar, J. Reiner, J. Zweigenbaum, P. Secoura, A. Lindstrom, and J. Dye. U.S. Domestic Cats as Sentinels for Perfluoroalkyl Substances: Associations with Housing, Obesity and Chronic Disease.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 151(0): 145-153, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390061",
            "keyword": [
                "perfluorinated",
                "cats",
                "obesity",
                "perfluorohexane  sulfonate",
                "PFAS"
            ],
            "contactPoint": {
                "fn": "Mark Strynar",
                "hasEmail": "mailto:strynar.mark@epa.gov"
            },
            "distribution": [
                {
                    "title": "A-rfjw_Dataset Information Document.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390061/A-rfjw_Dataset%20Information%20Document.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2008-01-15",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Hall et al., 2016 Artificial Turf Surrogate Surface Methods Paper Data File",
            "description": "Mercury dry deposition data quantified via static water surrogate surface (SWSS) and artificial turf surrogate surface (ATSS) collectors. \n\nThis dataset is associated with the following publication:\nHall, N., T. Dvonch, F. Marsik, J. Barres, and M. Landis. An Artificial Turf-Based Surrogate Surface Collector for the Direct Measurement of Atmospheric Mercury Dry Deposition.   International Journal of Environmental Research and Public Health. Molecular Diversity Preservation International, Basel,  SWITZERLAND, 14(2): 173, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390063",
            "keyword": [
                "mercury",
                "Dry Deposition",
                "surrogate surface",
                "turf"
            ],
            "contactPoint": {
                "fn": "Matthew Landis",
                "hasEmail": "mailto:landis.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "turf_paper_data_science_hub_summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390063/turf_paper_data_science_hub_summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-25",
            "references": [
                "https://doi.org/10.3390/ijerph14020173"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CFD Model Data",
            "description": "Data associated with the development of the CFD model for spore deposition in respiratory systems of rabbits and humans. \n\nThis dataset is associated with the following publication:\nKabilan, S., K. Recknagle, R. Jacob, D. Einstein, A. Kuprat, J. Carson, S. Colby, J. Saunders, S. Hines, J. Teeguarden, S. Taft , and R. Corley. Computational Fluid Dynamics Modeling of Bacillus anthracis Spore Deposition in Rabbit and Human Respiratory Airways  [HS4.44.02].   JOURNAL OF AEROSOL SCIENCE. Elsevier Science Ltd, New York, NY, USA,  14, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1377593",
            "keyword": [
                "Bacillus anthracis",
                "Three-dimensional computational fluid dynamics  model",
                "Lagrangian particle deposition models",
                "rabbit",
                "human",
                "spore deposition"
            ],
            "contactPoint": {
                "fn": "Sarah Taft",
                "hasEmail": "mailto:taft.sarah@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data_CFD_Model.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377593/Data_CFD_Model.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Human Deposition Calculations_Kabilan.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377593/Human%20Deposition%20Calculations_Kabilan.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Rabbit Deposition Calculations_HIGH_Kabilan.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377593/Rabbit%20Deposition%20Calculations_HIGH_Kabilan.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Rabbit Deposition Calculations_LOW_Kabilan.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377593/Rabbit%20Deposition%20Calculations_LOW_Kabilan.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://pubmed.ncbi.nlm.nih.gov/33311732/",
                    "accessURL": "https://pubmed.ncbi.nlm.nih.gov/33311732/"
                }
            ],
            "modified": "2014-09-01",
            "references": [
                "https://doi.org/10.1016/j.jaerosci.2016.01.011",
                "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7731948",
                "https://pasteur.epa.gov/uploads/10.23719/1377593/documents/Supporting%20information%20for%20model_Kabilan.docx"
            ],
            "publisher": {
                "name": "U.S. Environmental Protection Agency",
                "subOrganizationOf": {
                    "name": "U.S. Government"
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for \"Estimates of reservoir methane emissions based on a spatially balanced probabilistic-survey\"",
            "description": "Measured diffusive and ebullitive methane emission rates from 115 sites in William H Harsha Lake.  File also contains fields required for GRTS analysis. \n\nThis dataset is associated with the following publication:\nBeaulieu , J., M. McManus , and C. Nietch. Estimates of reservoir methane emissions based on a spatially balanced probabilistic-survey.   LIMNOLOGY AND OCEANOGRAPHY. American Society of Limnology and Oceanography, Lawrence, KS, USA, 61(1): S27-S40, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1390077",
            "keyword": [
                "GRTS",
                "ebullition",
                "diffusion",
                "reservoir",
                "Methane",
                "harsha lake",
                "greenhouse gas inventory"
            ],
            "contactPoint": {
                "fn": "Jake Beaulieu",
                "hasEmail": "mailto:beaulieu.jake@epa.gov"
            },
            "distribution": [
                {
                    "title": "scienceHubScID-A-vx17.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390077/scienceHubScID-A-vx17.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2015-10-01",
            "references": [
                "https://doi.org/10.1002/lno.10284"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Inactivation Data.xlsx",
            "description": "The data set is a spreadsheet that contains results of inactivation experiments that were conducted to to determine the effectiveness of chlorine in inactivating B. anthracis spore surrogates in wash waters similar to waters that would be generated during building decontamination activities. \n\nThis dataset is associated with the following publication:\nGallardo, V., D. Schupp, J. Heckman, R. Krishnan, and E. Rice. Inactivation of Bacillus Spores in Wash Waters Using Dilute Chlorine Bleach Solutions at Different Temperatures and pH Levels.   WATER ENVIRONMENT RESEARCH. Water Environment Federation, Alexandria, VA, USA,  1-36, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1390123",
            "keyword": [
                "Indoor outdoor decontamination",
                "biological",
                "water treatment",
                "anthrax",
                "Bacillus",
                "inactivation",
                "wastewater",
                "wash water",
                "hypochlorite",
                "bleach",
                "Chlorine"
            ],
            "contactPoint": {
                "fn": "Vicente Gallardo",
                "hasEmail": "mailto:gallardo.vincente@epa.gov"
            },
            "distribution": [
                {
                    "title": "Inactivation Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390123/Inactivation%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-01-06",
            "references": [
                "https://doi.org/10.2175/106143017x14902968254719"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1390123/documents/Data%20Dictionary.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Effects of Chronic Exposure to Triclosan on Reproductive and Thyroid Endpoints in the Adult Wistar Female Rat",
            "description": "This dataset includes the results of a long term adult female rat oral exposure to triclosan and includes hormone, estrous cyclicity, thyroid histology and liver gene expression data. \n\nThis dataset is associated with the following publication:\nLouis, G., D. Hallinger, J. Braxton, A. Kamel, and T. Stoker. Effects of Chronic Exposure to Triclosan on Reproductive and Thyroid Endpoints in the Adult Wistar Female Rat.   JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. Taylor & Francis, Inc., Philadelphia, PA, USA,  236-249, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390129",
            "keyword": [
                "Estrous cyclicity",
                "thyroid",
                "Triclosan",
                "endocrine"
            ],
            "contactPoint": {
                "fn": "Tammy Stoker",
                "hasEmail": "mailto:stoker.tammy@epa.gov"
            },
            "distribution": [
                {
                    "title": "Final Triclosan Paper for Sciencehub4.3.17.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390129/Final%20Triclosan%20Paper%20for%20Sciencehub4.3.17.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-31",
            "references": [
                "https://doi.org/10.1080/15287394.2017.1287029"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Human Health Screening and Public Health Significance of Contaminants of Emerging Concern Detected in Public Water Supplies",
            "description": "Background information for human health margin of exposure paper. \n\nThis dataset is associated with the following publication:\nBenson , B., O. Conerly , W. Sander, A. Batt , E. Furlong, S. Glassmeyer , D. Koplin, H. Mash , K. Schenck , J. Simmons , and S. Boone. Human Health Screening and Public Health Significance of Contaminants of Emerging Concern Detected in Public Water Supplies.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 579: 1643-1648, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1390158",
            "keyword": [
                "margin of exposure",
                "human health",
                "drinking water",
                "source water",
                "pharmaceuticals",
                "microorganisms",
                "Per- and polyfluoroalkyl substances"
            ],
            "contactPoint": {
                "fn": "Susan Glassmeyer",
                "hasEmail": "mailto:glassmeyer.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Copy of Data Summary MOE by DWTP- Overall.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390158/Copy%20of%20Data%20Summary%20MOE%20by%20DWTP-%20Overall.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-05",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2016.03.146"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Predicting Thermal Behavior of Secondary Organic Aerosols",
            "description": "Volume concentrations of secondary organic aerosol (SOA) are measured in 139 steady-state, single precursor hydrocarbon oxidation experiments after passing through a temperature controlled inlet. The response to change in temperature is well predicted through a feedforward Artificial Neural Network. The most parsimonious model, as indicated by Akaike\u2019s Information Criterion, Corrected (AIC,C), utilizes 11 input variables, a single hidden layer of 4 tanh activation function nodes, and a single linear output function. This model predicts thermal behavior of single precursor aerosols to less than \u00b1 5%, which is within the measurement uncertainty, while limiting the problem of overfitting. Prediction of thermal behavior of SOA can be achieved by a concise number of descriptors of the precursor hydrocarbon including the number of internal and external double bonds, number of methyl- and ethyl- functional groups, molecular weight, number of ring structures, in addition to the volume of SOA formed, and an indicator of which of four oxidant precursors was used to initiate reactions (NOx photo-oxidation, photolysis of H2O2, ozonolysis, or thermal decomposition of N2O5). Additional input variables, such as, chamber volumetric residence time, relative humidity, initial concentration of oxides of nitrogen, reacted hydrocarbon concentration, and further descriptors of the precursor hydrocarbon, including carbon number, number of oxygen atoms, and number of aromatic ring structures, lead to over fit models, and are unnecessary for an efficient, accurate predictive model of thermal behavior of SOA.  This work indicates that predictive statistical modeling methods may be complementary to descriptive techniques for use in parameterization of air quality models. \n\nThis dataset is associated with the following publication:\nOffenberg, J., M. Lewandowski, T. Kleindienst, K. Docherty, J. Krug, T. Riedel, D. Olson, and M. Jaoui. Predicting Thermal Behavior of Secondary Organic Aerosols.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(17): 9911-9919, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1372660",
            "keyword": [
                "enthalpy of vaporization",
                "Artificial Neural Network",
                "air quality",
                "Secondary Organic Aerosol",
                "air toxics",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Michael Lewandowski",
                "hasEmail": "mailto:lewandowski.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Offenberg Thermal Properties Figures1-5.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372660/Offenberg%20Thermal%20Properties%20Figures1-5.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-26",
            "references": [
                "https://doi.org/10.1021/acs.est.7b01968"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cyanobacteria Index (MERIS) ",
            "description": "This dataset shows the concentration of cyanobacteria cells/ml in fresh water bodies and estuaries of the Ohio and Florida derived from 300x300 meter MEdium Resolution Imaging Spectrometer (MERIS) satellite imagery. This dataset was produced through partnership with the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), the United States Geological Survey (USGS), and the United States Environmental Protection Agency (USEPA). This cyanobacteria dataset was derived using the European Space Agency (ESA) Envisat satellite and MERIS instrument. MERIS is a 68.5 degree field-of-view nadir-pointing imaging spectrometer which measures the solar radiation reflected by the Earth in 15 spectral bands (visible and near-infrared). MERIS imagery was used to identify long-wavelength spectral bands (from red through near-infrared portion of the spectrum) to locate algal blooms within freshwaters and estuaries of the continental United States. \n\nThis dataset is associated with the following publication:\nUrquhart, E., B. Schaeffer, R. Stumpf, K. Loftin, and J. Wedell. .A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing.   Harmful Algae. Elsevier B.V., Amsterdam,  NETHERLANDS, 67: 144-152, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1364346",
            "keyword": [
                "Harmful Algal Blooms",
                "cyanobacteria",
                "remote sensing",
                "MERIS",
                "Sentinel-3",
                "inland waters",
                "lakes",
                "reservoirs"
            ],
            "contactPoint": {
                "fn": "Blake Schaeffer",
                "hasEmail": "mailto:schaeffer.blake@epa.gov"
            },
            "distribution": [
                {
                    "title": "A-vq8t.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1364346/A-vq8t.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-05-08",
            "references": [
                "https://doi.org/10.1016/j.hal.2017.06.001"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Autism and green space_clean",
            "description": "Autism and green space metrics in California elementary school districts. \n\nThis dataset is associated with the following publication:\nWu, J., and L. Jackson. Inverse Relationship Between Urban Green Space and Childhood Autism in California Elementary School Districts.   ENVIRONMENT INTERNATIONAL. Elsevier Science Ltd, New York, NY, USA, 107: 140-145, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1374806",
            "keyword": [
                "Green space",
                "Social economical status",
                "autism case",
                "near-road tree canopy",
                "autism spectrum disorder",
                "greenness",
                "air pollution",
                "school children",
                "human health"
            ],
            "contactPoint": {
                "fn": "Jianyong Wu",
                "hasEmail": "mailto:wu.jianyong@epa.gov"
            },
            "distribution": [
                {
                    "title": "autism and green space_clean.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374806/autism%20and%20green%20space_clean.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-08-11",
            "references": [
                "https://doi.org/10.1016/j.envint.2017.07.010"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1374806/documents/Data%20dictonary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Constraints on primary and secondary particulate carbon sources using chemical tracer and 14C methods during CalNex-Bakersfield",
            "description": "The present study investigates primary and secondary sources of organic carbon for  Bakersfield, CA, USA as part of the 2010 CalNex study. The method used here involves integrated sampling that is designed to allow for detailed and specific chemical analysis of particulate matter (PM) in the Bakersfield airshed. To achieve this objective, filter samples were taken during thirty-four 23-hr periods between 19 May and 26 June 2010 and analyzed for organic tracers by gas chromatography \u2013 mass spectrometry (GC-MS). Contributions to organic carbon (OC) were determined by two organic tracer-based techniques:  primary OC by chemical mass balance and secondary OC by a mass fraction method. Radiocarbon (14C) measurements of the total organic carbon were also made to determine the split between the modern and fossil carbon and thereby constrain unknown sources of OC not accounted for by either tracer-based attribution technique. \r\nFrom the analysis, OC contributions from four primary sources and four secondary sources were determined, which comprised three sources of modern carbon and five sources of fossil carbon. The major primary sources of OC were from vegetative detritus (9.8%), diesel (2.3%), gasoline (<1.0%), and lubricating oil impacted motor vehicle exhaust (30%); measured secondary sources resulted from isoprene (1.5%), \u03b1-pinene (<1.0%), toluene (<1.0%), and naphthalene (<1.0%, as an upper limit) contributions. The average observed organic carbon (OC) was 6.42  \u00b1 2.33 \u03bcgC m-3. The 14C derived apportionment indicated that modern and fossil components were nearly equivalent on average; however, the fossil contribution ranged from 32-66% over the five week campaign. With the fossil primary and secondary sources aggregated, only 25% of the fossil organic carbon could not be attributed. Whereas, nearly 80% of the modern carbon could not be attributed to primary and secondary sources accessible to this analysis, which included tracers of biomass burning, vegetative detritus and secondary biogenic carbon. The results of the current study contributes source-based evaluation of the carbonaceous aerosol at CalNex Bakersfield. \n\nThis dataset is associated with the following publication:\nSheesley, R., P. Dev Nallathamby, J. Surratt, A. Lee, M. Lewandowski, J. Offenberg, M. Jaoui, and T. Kleindienst. Constraints on primary and secondary particulate carbon sources using chemical tracer and 14C methods during CalNex-Bakersfield.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 166: 204-214, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1373284",
            "keyword": [
                "CalNex",
                "Source Attribution",
                "14C",
                "air quality",
                "Secondary Organic Aerosol",
                "air toxics",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Michael Lewandowski",
                "hasEmail": "mailto:lewandowski.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Sheesley Fig 1 data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1373284/Sheesley%20Fig%201%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Sheesley Fig 2 data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1373284/Sheesley%20Fig%202%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-25",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2017.07.025"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Measuring urban tree loss dynamics across residential landscapes",
            "description": "The spatial arrangement of urban vegetation depends on urban morphology and socio-economic settings.  Urban vegetation changes over time because of human management.  Urban trees are removed due to hazard prevention or aesthetic preferences.  Previous research attributed tree\nloss to decreases in canopy cover.  However, this provides little information about location and structural characteristics of trees lost, as well as environmental and social factors affecting tree loss dynamics.  This is particularly relevant in residential landscapes where access to residential parcels for field surveys is limited.  We tested whether multi-temporal airborne LiDAR and multi-spectral imagery collected at a 5-year interval can be used to investigate urban tree loss dynamics across residential landscapes in Denver, CO and Milwaukee, WI, covering 400,705 residential parcels in 444 census tracts.  Position and stem height of trees lost were extracted from canopy height models calculated as the difference between final (year 5) and initial (year 0) vegetation height derived from LiDAR.  Multivariate regression models were used to predict number and height of tree stems lost in residential parcels in each census tract based on urban morphological and socio-economic variables.  A total of 28,427 stems were lost from residential parcels in Denver and Milwaukee over 5 years.  Overall, 7% of residential parcels lost one stem, averaging 90.87 stems per km2.  Average stem height was 10.16 m, though trees lost in Denver were taller compared to Milwaukee.  The number of stems lost was higher in neighborhoods with higher canopy cover and developed before the 1970s.  However, socio-economic characteristics had little effect on tree loss dynamics.  The study provides a robust method for measuring urban tree loss dynamics within and across entire cities, and represents a first step towards high resolution assessments of the three-dimensional change of urban vegetation at large spatial scales. \n\nThis dataset is associated with the following publication:\nOssola, A., and M. Hopton. Measuring urban tree loss dynamics across residential landscapes.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 612: 940-949, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1375181",
            "keyword": [
                "multi-temporal LiDAR",
                "urban forestry",
                "remote sensing",
                "vegetation dynamics",
                "socio-ecological systems",
                "urban ecology",
                "ecosystem services"
            ],
            "contactPoint": {
                "fn": "Matthew Hopton",
                "hasEmail": "mailto:hopton.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "RcodeManuscript.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375181/RcodeManuscript.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "DataDenverMilwaukee.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375181/DataDenverMilwaukee.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-29",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2017.08.103"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Comparison of Five Modeling Approaches to Quantify and Estimate the Effect of Clouds on the Radiation Amplification Factor (RAF) for Solar Ultraviolet Radiation",
            "description": "Ultraviolet Radiation (UV) data collected at 21 US Environmental Protection Agency sites throughout the continental US, Alaska, Hawaii, and the US Virgin Islands from 1996 through 2004. \n\nThis dataset is associated with the following publication:\nHall, E. Comparison of Five Modeling Approaches to Quantify and Estimate the Effect of Clouds on the Radiation Amplification Factor (RAF) for Solar Ultraviolet Radiation.   ATMOSPHERE. MDPI AG, Basel,  SWITZERLAND, 8(8): 153, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1376728",
            "keyword": [
                "Radiation Amplification Factor (RAF)",
                "Diffey-weighted ultraviolet radiation (DUV)",
                "Solar Zenith Angle (SZA)",
                "Dobson Unit (DU)",
                "ultraviolet radiation (UV)",
                "cloudiness"
            ],
            "contactPoint": {
                "fn": "Eric Hall",
                "hasEmail": "mailto:hall.erics@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/hesc/rsig-data-inventory",
                    "accessURL": "https://www.epa.gov/hesc/rsig-data-inventory"
                }
            ],
            "modified": "2004-12-31",
            "references": [
                "https://doi.org/10.3390/atmos8080153",
                "https://pasteur.epa.gov/uploads/10.23719/1376728/documents/QAPP_68-D-04-001_JAN2004.pdf",
                "https://pasteur.epa.gov/uploads/10.23719/1376728/documents/QA%20Review%20Form_esh_02JUN2017.signed.pdf",
                "https://pasteur.epa.gov/uploads/10.23719/1376728/documents/Performance_Work_Specification_68-D-04-001_30OCT2003.pdf",
                "https://pasteur.epa.gov/uploads/10.23719/1376728/documents/atmosphere-08-00153-v2.pdf"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1376728/documents/UV%20Data%20Dictionary-MetadataA-6hf0_20170703.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset for Calibration and performance of synchronous SIM/scan mode for simultaneous targeted and discovery (non-targeted) analysis of exhaled breath samples from firefighters",
            "description": "This dataset includes the tables and supplementary information from the journal article. \n\nThis dataset is associated with the following publication:\nWallace, A., J. Pleil, S. Mentese, K. Oliver, D. Whitaker, and K. Fent. Calibration and performance of synchronous SIM/scan mode for simultaneous targeted and discovery (non-targeted) analysis of exhaled breath samples from firefighters.   JOURNAL OF CHROMATOGRAPHY A. Elsevier Science Ltd, New York, NY, USA, 1516: 114-124, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1380226",
            "keyword": [
                "Selected ion monitoring/scan (SIM/scan)",
                "Gas chromatography-mass spectrometry (GC/MS)",
                "Automatic thermal desorption (ATD)",
                "Volatile organic compound (VOC)",
                "Polyaromatic hydrocarbon (PAH)",
                "breath research"
            ],
            "contactPoint": {
                "fn": "Michelle Wallace",
                "hasEmail": "mailto:wallace.ariel@epa.gov"
            },
            "distribution": [
                {
                    "title": "WallaceMichelle_A-6hdz_Data_20170508.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1380226/WallaceMichelle_A-6hdz_Data_20170508.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-05-09",
            "references": [
                "https://doi.org/10.1016/j.chroma.2017.07.082"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Aerobic oxidation of alcohols in visible light on Pd-grafted Ti cluster",
            "description": "The titanium cluster with the reduced band gap has been synthesized having the palladium nanoparticles over the surface, which not only binds to the atmospheric oxygen but also catalyzes the oxidation of alcohols under visible light. \n\nThis dataset is associated with the following publication:\nVerma, S., R.B.N. Baig, M. Nadagouda, and R. Varma. Aerobic oxidation of alcohols in visible light on Pd-grafted Ti cluster.   TETRAHEDRON. Elsevier Science Ltd, New York, NY, USA, 73(38): 5577-5580, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1389569",
            "keyword": [
                "Titanium cluster",
                "Heterogeneous catalysis",
                "Palladium nanoparticle",
                "Aerial oxidation",
                "Photoactive",
                "Visible light"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.sciencedirect.com/science/article/pii/S0040402016307281",
                    "accessURL": "https://www.sciencedirect.com/science/article/pii/S0040402016307281"
                }
            ],
            "modified": "2017-08-25",
            "references": [
                "https://doi.org/10.1016/j.tet.2016.07.070",
                "https://www.sciencedirect.com/science/article/pii/S0040402016307281?via%3Dihub",
                "https://pasteur.epa.gov/uploads/10.23719/1389569/documents/TET-D-16-00678R1-Supporting%20Information.docx"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Triclosan Concentration Data for Lydon et al., 2017",
            "description": "Pharmaceuticals and personal care products, including antimicrobials, can be found at trace levels in treated wastewater effluent. Impacts of chemical contaminants on coastal aquatic microbial community structure and pathogen abundance are unknown despite the potential for selection through antimicrobial resistance. In particular, Vibrio, a marine bacterial genus that includes several human pathogens, displays resistance to the ubiquitous antimicrobial compound triclosan. Here we demonstrated through use of natural seawater microcosms that triclosan (at a concentration of ~5 ppm) can induce a significant Vibrio growth response (68\u20131,700 fold increases) in comparison with no treatment controls for three distinct coastal ecosystems: Looe Key Reef (Florida Keys National Marine Sanctuary), Doctors Arm Canal (Big Pine Key, FL), and Clam Bank Landing (North Inlet Estuary, Georgetown, SC). Additionally, microbial community analysis by 16 S rRNA gene sequencing for Looe Key Reef showed distinct changes in microbial community structure with exposure to 5 ppm triclosan, with increases observed in the relative abundance of Vibrionaceae (17-fold), Pseudoalteromonadaceae (65-fold), Alteromonadaceae (108-fold), Colwelliaceae (430-fold), and Oceanospirillaceae (1,494-fold). While the triclosan doses tested were above concentrations typically observed in coastal surface waters, results identify bacterial families that are potentially resistant to triclosan and/or adapted to use triclosan as a carbon source. The results further suggest the potential for selection of Vibrio in coastal environments, especially sediments, where triclosan may accumulate at high levels. \n\nThis dataset is associated with the following publication:\nLydon, K.A., D. Glinski, J. Westrich, M. Henderson, and E. Lipp. Effects of triclosan on bacterial community composition and Vibrio populations in natural seawater microcosms.   Elementa: Science of the Anthropocene. University of California Press (UC Press), Oakland, CA, USA, 5(22): 1-16, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390180",
            "keyword": [
                "tricolsan",
                "antimicrobial resistance",
                "vibrio",
                "pharmaceuticals",
                "Triclosan",
                "antimicrobials"
            ],
            "contactPoint": {
                "fn": "William Henderson",
                "hasEmail": "mailto:henderson.matt@epa.gov"
            },
            "distribution": [
                {
                    "title": "Lydon et al., 2017_SciHub Dataset.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390180/Lydon%20et%20al.%2C%202017_SciHub%20Dataset.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-09-14",
            "references": [
                "https://doi.org/10.1525/elementa.141"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Concentration and Quantification of Somatic and F+ Coliphages from Recreational Waters",
            "description": "Dataset describes performance of a culture-based method to concentrate and quantify somatic and F+ coliphages. \n\nThis dataset is associated with the following publication:\nMcMinn, B., E. Huff, E. Rhodes, and A. Korajkic. Concentration and Quantification of Somatic and F+ Coliphage from Recreational Waters.   JOURNAL OF VIROLOGICAL METHODS. Elsevier Science Ltd, New York, NY, USA, 249: 58-65, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1378317",
            "keyword": [
                "coliphage",
                "Ultrafiltration",
                "recreational water",
                "wastewater",
                "Bacteriophage"
            ],
            "contactPoint": {
                "fn": "Asja Korajkic",
                "hasEmail": "mailto:korajkic.asja@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378317/ScienceHub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-10",
            "references": [
                "https://doi.org/10.1016/j.jviromet.2017.08.006"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dilbit Data",
            "description": "The data is in the form of degradation of hydrocarbons over time at two temperatures and the relative abundance of bacterial taxa identified in the microcosms. This dataset is associated with the following publication:\nConmy, R., M. Barron, J. Santodomingo, and R. Deshpande. Characterization and Behavior of Cold Lake Blend and Western Canadian Select Diluted Bitumen Products. U.S. Environmental Protection Agency, Washington, DC, USA, 2017. NOTE: This dataset has been removed from public access due to revocation. Please refer inquiries regarding this dataset to the listed contact person.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390705",
            "keyword": [
                "hydrocarbon",
                "dilbit degradation",
                "dilbit"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [],
            "modified": "2017-09-05",
            "references": null,
            "publisher": {
                "name": "U.S. Environmental Protection Agency",
                "subOrganizationOf": {
                    "name": "U.S. Government"
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Accumulibacter data",
            "description": "Number of gene copies associated with phosphate accumulation using qPCR and relative abundance of bacterial groups. This dataset is associated with the following publication:\nCamejo, P., J. Santodomingo, K. McMahon, and D. Noguera. Genome-enabled insights into the ecophysiology of the comammox bacterium Ca. Nitrospira nitrosa.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 2(5): 1-16, (2017). NOTE: This dataset has been removed from public access due to revocation. Please refer inquiries regarding this dataset to the listed contact person.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1390706",
            "keyword": [
                "water and wastewater treatment",
                "phosphate accumulation",
                "low dissolve oxygen"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [],
            "modified": "2017-09-05",
            "references": null,
            "publisher": {
                "name": "U.S. Environmental Protection Agency",
                "subOrganizationOf": {
                    "name": "U.S. Government"
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Pilot Plant data for nitrogen removal",
            "description": "Different phylogenetic groups that were identified in this study. \n\nThis dataset is associated with the following publication:\nKeene, N.A., S.R. Reusser, M. Scarborough, A. Grooms, M. Seib, J. Santodomingo, and D. Noguera. Pilot Plant Demonstration of Stable and Efficient High Rate Biological Nutrient Removal with Low Dissolved Oxygen Conditions.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 121: 72-85, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1390709",
            "keyword": [
                "biological nutrient removal",
                "low dissolved oxygen"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [
                {
                    "title": "Keene et al Pilot Plant ScId A-70s7.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390709/Keene%20et%20al%20Pilot%20Plant%20ScId%20A-70s7.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-09-05",
            "references": [
                "https://doi.org/10.1016/j.watres.2017.05.029"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Lye-data-compiled-scihub ",
            "description": "The data contained in this worksheet provides the quantitative detection of potentially pathogenic fungi in treated and untreated rainwater samples. \n\nThis dataset is associated with the following publication:\nKim, T., D. Lye , M. Donohue , J. Mistry , S. Pfaller , S. Vesper , and M.J. Kirisits. Harvested rainwater quality before and after treatment in six full-scale residential systems.   JOURNAL OF AMERICAN WATER WORKS ASSOCIATION. American Water Resources Association, Middleburg, VA, USA, 108(11): E571-E584, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1390510",
            "keyword": [
                "Aspergillus",
                "legionella",
                "Mycobacterium",
                "rainwater harvesting",
                "rainwater",
                "treatment"
            ],
            "contactPoint": {
                "fn": "Eric Villegas",
                "hasEmail": "mailto:villegas.eric@epa.gov"
            },
            "distribution": [
                {
                    "title": "Lye-data-compiled-scihub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390510/Lye-data-compiled-scihub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-19",
            "references": [
                "https://doi.org/10.5942/jawwa.2016.108.0182"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "DEVELOPMENT OF A SCREENING APPROACH TO DETECT THYROID DISRUPTING CHEMICALS THAT INHIBIT THE HUMAN SODIUM IODIDE SYMPORTER (NIS)",
            "description": "Data pertaining to a NIS-expressing cell line, hNIS-HEK293T-EPA, and its screening capabilities for determining inhibitors of NIS-mediated iodide uptake. \n\nThis dataset is associated with the following publication:\nHallinger, D., A. Murr, A. Buckalew, S. Simmons, T. Stoker, and S. Laws. Development of a Screening Approach to Detect Thyroid Disrupting Chemicals that Inhibit the Human Sodium/Iodide Symporter (NIS).   TOXICOLOGY IN VITRO. Elsevier Science Ltd, New York, NY, USA,  66-78, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1389264",
            "keyword": [
                "thyroid",
                "Endocrine Disruptors",
                "Sodium Iodide Symporter",
                "Chemical Screening"
            ],
            "contactPoint": {
                "fn": "Susan Laws",
                "hasEmail": "mailto:laws.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "A-jm6k.Data.Completed.by.DRH.20161219.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1389264/A-jm6k.Data.Completed.by.DRH.20161219.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-12-20",
            "references": [
                "https://doi.org/10.1016/j.tiv.2016.12.006"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Corexit 9500 microcosm data",
            "description": "Relative abundance of bacterial groups in the microcosms. \n\nThis dataset is associated with the following publication:\nTechtman, S., M. Zhuang, P. Campo-Moreno, E. Holder, R. Conmy, J. Santodomingo, and T. Hazen. Corexit 9500 Enhances Oil Biodegradation and Changes Active Bacterial Community Structure of Oil-Enriched Microcosms.   APPLIED AND ENVIRONMENTAL MICROBIOLOGY. American Society for Microbiology, Washington, DC, USA, 83(10): e03462-16, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1391743",
            "keyword": [
                "Polyaromatic hydrocarbon (PAH)",
                "degradation"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [
                {
                    "title": "Copy of differential_Temp.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1391743/Copy%20of%20differential_Temp.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-01",
            "references": [
                "http://aem.asm.org/content/83/10/e03462-16"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Bioinformatics data for paper",
            "description": "Data for sequence comparison of commamox genomes and genes identified. \n\nThis dataset is associated with the following publication:\nCamejo, P., J. Santodomingo, K. McMahon, and D. Noguera. Genome-enabled insights into the ecophysiology of the comammox bacterium Ca. Nitrospira nitrosa.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 2(5): 1-16, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1391774",
            "keyword": [
                "commamox",
                "nitrification"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [
                {
                    "title": "Camejo et al dataset ScID A-gf29.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1391774/Camejo%20et%20al%20dataset%20ScID%20A-gf29.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-09-14",
            "references": [
                "https://doi.org/10.1128/msystems.00059-17"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Identifying Known Unknowns Using the USEPA CompTox Chemistry Dashboard AnalytBioanlytChem Data",
            "description": "In this research, the performance of the Dashboard for identifying \u201cknown unknowns\u201d was evaluated against that of the online ChemSpider database, one of the primary resources used by mass spectrometrists, using multiple previously studied datasets reported in the peer-reviewed literature totaling 162 chemicals. These chemicals were examined using both applications via molecular formula and monoisotopic mass searches followed by rank-ordering of candidate compounds by associated references or data sources.  A greater percentage of chemicals ranked in the top position when using the Dashboard, indicating an advantage of this application over ChemSpider for identifying known unknowns using data source ranking. Additional approaches are being developed for inclusion into a non-targeted analysis workflow as part of the CompTox Chemistry Dashboard. \n\nThis dataset is associated with the following publication:\nMcEachran, A., J. Sobus, and A. Williams. (Analytical and Bioanalytical Chemistry) Identifying known unknowns using the US EPAs CompTox Chemistry Dashboard.   Analytical and Bioanalytical Chemistry. Springer, New York, NY, USA,  1-7, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1390250",
            "keyword": [
                "non-targeted analysis",
                "suspect screening",
                "high-resolution mass spectrometry",
                "DSSTox",
                "Chemistry Dashboard",
                "dashboards"
            ],
            "contactPoint": {
                "fn": "Antony Williams",
                "hasEmail": "mailto:williams.antony@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/McEachranAndrew",
                    "accessURL": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/McEachranAndrew"
                }
            ],
            "modified": "2017-01-19",
            "references": [
                "https://doi.org/10.1007/s00216-016-0139-z"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Datasets used in the manuscript titled \"Nitrate radicals and biogenic volatile organic compounds: oxidation, mechanisms and organic aerosol\"",
            "description": "This dataset documents that all of the data used in the manuscript \"Nitrate radicals and biogenic volatile organic compounds: oxidation, mechanisms, and organic aerosol\" were from previously published works; no original data is presented as this is a review of the state of the science. \n\nThis dataset is associated with the following publication:\nNg, N., S. Brown, A. Archibald, E. Atlas, R. Cohen, J. Crowley, D. Day, N. Donahue, J. Fry, H. Fuchs, R. Griffin, M. Guzman, H. Herrmann, A. Hodzic, Y. Iinuma, J. Jimenez, A. Kiendler-Scharr, B. Lee, D. Luecken, J. Mao, R. McLaren, A. Mutzel, H. Osthoff, B. Ouyang, B. Picquet-Varrault, U. Platt, H. Pye, Y. Rudich, R. Schwantes, M. Shiraiwa, J. Stutz, J. Thornton, A. Tilgner, B.J. Williams, and R. Zaveri. Nitrate radicals and biogenic volatile organic compounds: oxidation, mechanisms, and organic aerosol.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 17: 2103-2162, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1375313",
            "keyword": [
                "nitrate",
                "BVOCs",
                "isoprene",
                "monoterpenes"
            ],
            "contactPoint": {
                "fn": "Deborah Luecken",
                "hasEmail": "mailto:luecken.deborah@epa.gov"
            },
            "distribution": [
                {
                    "title": "Ng_etal_DataStatement.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375313/Ng_etal_DataStatement.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-12-29",
            "references": [
                "https://doi.org/10.5194/acp-17-2103-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Assembled cross-species perchlorate dose-response data ",
            "description": "This data set contains dose-response data for perchlorate exposure in multiple species.  These data were assembled from peer-reviewed studies.  Species included in this dataset are: rats (Rattus sp.), meadow voles (Microtus sp.), rabbits (Oryctolagus cuniculus), the African clawed frog (Xenopus laevis), zebrafish (Danio rerio), mosquito fish (Gambusia holbrooki), the bobwhite quail (Colinus virginianus), earthworms (Eisenia foetida), mosquito larvae (Culex quinquefasciatus), the water flea (Daphnia magna), and the sand dollar (Peronella japonica). \n\nThis dataset is associated with the following publication:\nHines, D., S. Edwards, R. Conolly, and A. Jarabek. The Aggregate Exposure Pathway (AEP) and Adverse Outcome Pathway (AOP) frameworks facilitate the integration of human health and ecological endpoints for Cumulative Risk Assessment (CRA).   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(2): 839-849, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:062"
            ],
            "identifier": "https://doi.org/10.23719/1375712",
            "keyword": [
                "perchlorate",
                "cumulative risk assessment",
                "ecotoxicology",
                "human health",
                "Aggregate exposure"
            ],
            "contactPoint": {
                "fn": "Stephen Edwards",
                "hasEmail": "mailto:edwards.stephen@epa.gov"
            },
            "distribution": [
                {
                    "title": "Perchlorate_studies.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375712/Perchlorate_studies.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-11",
            "references": [
                "https://doi.org/10.1021/acs.est.7b04940"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1375712/documents/data_dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Synchrotron data of Pb, As, and Fe speciation in soils",
            "description": "Linear combination data showing the percent distribution of Pb, As, and Fe phases in soil samples exposed to simulated lung fluid. \n\nThis dataset is associated with the following publication:\nKastury, F., E. Smith, R. Karna, K. Scheckel, and A. Juhasz. An inhalation-ingestion bioaccessibility assay (IIBA) for the assessment of exposure to metal(loid)s in PM10.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS,  92-104, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390507",
            "keyword": [
                "metal bioavailability",
                "in vitro bioaccessibility",
                "synchrotron speciation",
                "contaminated soil",
                "Inhalation exposures"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Table 3 Kastury Lung IVBA Paper.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390507/Table%203%20Kastury%20Lung%20IVBA%20Paper.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-07-27",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.02.337"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "LCF data for aging of Cu NPs in soil",
            "description": "Linear combination fitting data for Cu NPs in five soils as a function of aging time. \n\nThis dataset is associated with the following publication:\nSekine, R., E. Marzouk, M. Khaksar, K. Scheckel, J. Stegemeier, G. Lowry, E. Donner, and E. Lombi. Aging of Dissolved Copper and Copper-based Nanoparticles in Five Different Soils: Short term Kinetics vs. Long term Fate.  Edward Gregorich  JOURNAL OF ENVIRONMENTAL QUALITY. American Society of Agronomy, MADISON, WI, USA, 46(6): 1198-1205, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1390506",
            "keyword": [
                "copper nanoparticles",
                "synchrotron speciation",
                "fate and transport",
                "Aging"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Mot CuNPs LCF Table.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390506/Mot%20CuNPs%20LCF%20Table.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-06-19",
            "references": [
                "https://doi.org/10.2134/jeq2016.12.0485"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Karna Particle Size Dataset for Tables and Figures",
            "description": "This dataset contains 1) table of bulk Pb-XAS LCF results, 2) table of bulk As-XAS LCF results, 3) figure data of particle size distribution, and 4) figure data for the relationship of As and Pb %IVBA in the <250 \u00b5m sieved size fraction vs sieved <250 \u00b5m to >150 \u00b5m, <150 \u00b5m to >75 \u00b5m, <75 \u00b5m to >38 \u00b5m, and <38 \u00b5m; and <250 \u00b5m ground, and <150 \u00b5m sieved and ground. \n\nThis dataset is associated with the following publication:\nKarna, R., M. Noerpel, A. Betts, and K. Scheckel. Lead and Arsenic Bioaccessibility and Speciation as a Function of Soil Particle Size.  Emmanuel Doelsch  JOURNAL OF ENVIRONMENTAL QUALITY. American Society of Agronomy, MADISON, WI, USA, 46(6): 1225-1235, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390505",
            "keyword": [
                "Bioaccessibility",
                "metal bioavailability",
                "synchrotron speciation",
                "particle size distribution",
                "lead",
                "arsenic"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Karna Particle Size Dataset.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390505/Karna%20Particle%20Size%20Dataset.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-03-06",
            "references": [
                "https://doi.org/10.2134/jeq2016.10.0387"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "EXAFS fit parameters for U sorption to nanoparticles in high salt water",
            "description": "Table showing samples and associated scattering paths, interatomic distance, coordination number, energy shift, and error factors. \n\nThis dataset is associated with the following publication:\nLi, D., S. Egodawatte, D. Kaplan, S. Larsen, S. Serkiz, J. Seaman, K. Scheckel, J. Lin, and Y. Pan. Sequestration of U(VI) from Acidic, Alkaline, and High Ionic-Strength Aqueous Media by Functionalized Magnetic Mesoporous Silica Nanoparticles: Capacity and Binding Mechanisms.  David Sedlak  ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(24): 14330-14341, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390504",
            "keyword": [
                "uranium",
                "seawater",
                "Engineered nanoparticles (NP)",
                "synchrotron speciation",
                "chemical binding"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Uranium EXAFS fit parameters.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390504/Uranium%20EXAFS%20fit%20parameters.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-07-10",
            "references": [
                "https://doi.org/10.1021/acs.est.7b03778"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Draft Genome Sequence of Mycobacterium chimaera Type Strain Fl-0169T version MRBR00000000.1",
            "description": "The dataset contains the first draft genome sequence of the type strain of Mycobacterium chimaera, Fl-0169. \n\nThis dataset is associated with the following publication:\nPfaller, S., V. Tokarev, C. Kessler, C. McLimans, V. Gomez-Alvarez, J. Wright, D. King, and R. Lamendella. Draft Genome Sequence of Mycobacterium chimaera Type Strain Fl-0169.   Genome Announcements. American Society for Microbiology, Washington, DC, USA, 5(8): e01620-16, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1379478",
            "keyword": [
                "Mycobacterium chimaera",
                "genome",
                "drinking water",
                "Pathogen"
            ],
            "contactPoint": {
                "fn": "Stacy Pfaller",
                "hasEmail": "mailto:pfaller.stacy@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.ncbi.nlm.nih.gov/Traces/wgs/?val=MRBR01#contigs",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/Traces/wgs/?val=MRBR01#contigs"
                }
            ],
            "modified": "2016-12-06",
            "references": [
                "https://doi.org/10.1128/genomea.01620-16"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A laboratory comparison of emission factors, number size distributions and morphology of ultrafine particles from eleven different household cookstove-fuel systems ",
            "description": "This dataset includes all data used to generate figures in the manuscript and supporting information for the publication entitled \"Emission factors, number size distributions and morphology of ultrafine particles in cookstove smoke: A laboratory comparison of different household stove-fuel systems.\". \n\nThis dataset is associated with the following publication:\nShen, G., C. Gaddam, S. Ebersviller, R. Vander Wal, C. Williams, J. Faircloth, J. Jetter, and M. Hays. Emission factors, number size distributions and morphology of ultrafine particles in cookstove smoke: A laboratory comparison of different household stove-fuel systems.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(11): 6522-6532, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1375761",
            "keyword": [
                "ultrafine particles",
                "number size distributions",
                "cookstoves",
                "particle morphology",
                "cookstove",
                "stove",
                "emission",
                "efficiency"
            ],
            "contactPoint": {
                "fn": "James Jetter",
                "hasEmail": "mailto:jetter.jim@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data in Cookstove UFP paper - 2017Aug17.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375761/Data%20in%20Cookstove%20UFP%20paper%20-%202017Aug17.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-10-14",
            "references": [
                "https://doi.org/10.1021/acs.est.6b05928"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Regeneration Study Test Data",
            "description": "Data (2 excel files) consist of the analytical test results on water sample collected from the two adsorption media tanks of the arsenic removal system during the regeneration processes conducted multiply times over a five-year period.  Data set also includes the companion bed volumes of water treated by the tank of media at the time the water samples were collected. \n\nThis dataset is associated with the following publications:\nSorg, T., A. Chen, L. Wang, and R. Kolich. Regeneration of a Full-Scale Arsenic Removal Adsorptive Media System,Part 1: The Regeneration Process.   JOURNAL OF AMERICAN WATER WORKS ASSOCIATION. American Water Resources Association, Middleburg, VA, USA, 109(5): 13-24, (2017).\nSorg, T., R. Kolich, A.S.C. Chen, and L. Wang. Regeneration of a Full-Scale Arsenic Removal Adsorptive Media System,Part 2: The Performance and Cost.   JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA, 109(5): E122-E128, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1392538",
            "keyword": [
                "drinking water",
                "arsenic",
                "drinking water treatment",
                "regeneration",
                "Field demonstration"
            ],
            "contactPoint": {
                "fn": "Thomas Sorg",
                "hasEmail": "mailto:sorg.thomas@epa.gov"
            },
            "distribution": [
                {
                    "title": "Regeneration Paper 1 - Fig 1 & 2 - Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1392538/Regeneration%20Paper%201%20-%20Fig%201%20%26%202%20-%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Regeneration Paper 2 - Fig 1 & 2 - Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1392538/Regeneration%20Paper%202%20-%20Fig%201%20%26%202%20-%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-06",
            "references": [
                "https://doi.org/10.5942/jawwa.2017.109.0045",
                "https://doi.org/10.5942/jawwa.2017.109.0046"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data supporting study of Ecosystem Metabolism in Pensacola Bay estuary",
            "description": "These files house the data collected during 2013 in lower Pensacola Bay. The data were used to estimate aquatic primary production and respiration. \n\nThis dataset is associated with the following publication:\nCaffrey, J., M. Murrell , K. Amacker, J. Harper, S. Phipps, and M. Woodrey. Seasonal and interannual patterns in primary production, respiration and net ecosystem metabolism in three estuaries in the northeast Gulf of Mexico.   Estuaries and Coasts. Estuarine Research Federation, Port Republic, MD, USA,  20, (2013).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1393578",
            "keyword": [
                "Primary Production",
                "Plankton Community Respiration",
                "Net Ecosystem Metabolism",
                "dissolved oxygen",
                "estuary",
                "eutrophication"
            ],
            "contactPoint": {
                "fn": "Michael Murrell",
                "hasEmail": "mailto:murrell.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "SPAM_2013_Master_Mar17.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393578/SPAM_2013_Master_Mar17.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-01",
            "references": [
                "https://doi.org/10.1007/s12237-013-9701-5"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Prioritization of Contaminants of Emerging Concern in Wastewater Treatment Plant Discharges using Chemical:Gene Interactions in Caged Fish. ",
            "description": "We examined whether contaminants present in surface waters could be prioritized for further assessment by linking the presence of specific chemicals to gene expression changes in exposed fish. Fathead minnows were deployed in cages for 2, 4, or 8 days at three locations near two different waste water treatment plant discharge sites in the Saint Louis Bay, Duluth, MN and one upstream control site. The biological impact of 51 chemicals detected in the surface water was determined using biochemical endpoints, exposure activity ratios for biological and estrogenic responses; known chemical:gene interactions from biological pathways and knowledge bases, and analysis of the co-variance of ovary gene expression with surface water chemistry. Thirty-two chemicals were significantly linked by co-variance with expressed genes. No estrogenic impact on biochemical endpoints was observed in male or female minnows. However, bisphenol A was identified by chemical:gene co-variation as the most impactful chemical across the exposure sites. This was consistent with identification of estrogenic effects on gene expression, high exposure activity ratios across all test sites, and historical analysis of the area. Overall, this approach appears useful in examining the impacts of complex mixtures on fish and offers a potential route in linking chemical exposure to adverse outcomes that reduce population sustainability. \n\nThis dataset is associated with the following publication:\nPerkins, E., T. Habib, B. Escalon, J. Cavallin, L. Thomas, M. Weberg, M. Hughes, K. Jensen, M. Kahl, D. Villeneuve, G. Ankley, and N. Garcia-Reyero. Prioritization of contaminants of emerging concern in wastewater treatment plant discharges using chemical: Gene interactions in caged fish.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(15): 8701-8712, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1393796",
            "keyword": [
                "adverse outcome pathway",
                "endocrine disruption",
                "Great Lakes Restoration Initiative",
                "screening and prioritization",
                "transcriptomic",
                "wastewater",
                "ecotoxicology",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "DS Harbor 2010 data for Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393796/DS%20Harbor%202010%20data%20for%20Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE96678",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE96678"
                }
            ],
            "modified": "2017-03-07",
            "references": [
                "https://doi.org/10.1021/acs.est.7b01567"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data used for Raimondo et al. 2016 \"Effects of Louisiana Crude Oil on the Sheepshead Minnow (Cyprinodon variegatus) During a Life-Cycle Exposure to Laboratory Oiled Sediment\"",
            "description": "Data are provided describing reproduction, length, weight, liver weight, and ovary weight in fish exposed to sediment spiked with weathered oil. Data are also provided on analytical chemistry of water and sediment to which fish were exposed in various treatments. \n\nThis dataset is associated with the following publication:\nRaimondo , S., B. Hemmer , C. Lilavois , J. Krzykwa , A. Almario , J. Awkerman , and M. Barron. Effects of Louisiana crude oil on the sheepshead minnow (Cyprinodon variegatus) during a life-cycle exposure to laboratory oiled sediment.   ENVIRONMENTAL TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 31(11): 1627-1639, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1371699",
            "keyword": [
                "wet weight",
                "length",
                "reproduction",
                "water chemistry",
                "sediment chemistry",
                "sediment exposure",
                "chronic toxicity",
                "fish",
                "oil",
                "Reproductive effects",
                "growth effects",
                "polycyclic"
            ],
            "contactPoint": {
                "fn": "Sandra Raimondo",
                "hasEmail": "mailto:raimondo.sandy@epa.gov"
            },
            "distribution": [
                {
                    "title": "Raimondo 2016 Env Tox_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371699/Raimondo%202016%20Env%20Tox_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-18",
            "references": [
                "https://doi.org/10.1002/tox.22167"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "In vitro dermal absorption of decabromodiphenyl ethane in rat and human skin",
            "description": "In vitro dermal absorption of decabromodiphenyl ethane in rat and human skin. \n\nThis dataset is associated with the following publication:\nKnudsen, G., J.M. Sanders, M. Hughes, E. Hull, and L. Birnbaum. The biological fate of decabromodiphenyl ethane following oral, dermal or intravenous administration.   XENOBIOTICA. Taylor & Francis, Inc., Philadelphia, PA, USA, 47(10): 894-902, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1393853",
            "keyword": [
                "brominated flame retardant",
                "skin"
            ],
            "contactPoint": {
                "fn": "Michael Hughes",
                "hasEmail": "mailto:hughes.michaelf@epa.gov"
            },
            "distribution": [
                {
                    "title": "DBDPE dermal in vitro data_092017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393853/DBDPE%20dermal%20in%20vitro%20data_092017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-20",
            "references": [
                "https://doi.org/10.1080/00498254.2016.1250180"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Adrenal-derived stress hormones modulate ozone-induced lung injury and inflammation",
            "description": "This data set shows high throughput gene expression assessment using RNAseq to examine how ozone-induced transcriptional changes in the lung are influenced by adrenalectomy or adrenal demedullation in rats. \nWe have previously observed that lung injury and inflammation are diminished in adrenalectomized rats and this study was planned to understand if circulating stress hormones influence ozone transcriptional effects and what ozone-induced pathway changes might be impacted by removal of adrenal glands. \n\nThis dataset is associated with the following publication:\nHenriquez, A., J. House, D. Miller, S. Snow, A. Fisher, H. Ren, M. Schladweiler, A. Ledbetter, F. Wright, and U. Kodavanti. Adrenal-derived stress hormones modulate ozone-induced lung injury and inflammation.   TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 329: 249-258, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1393585",
            "keyword": [
                "Ozone",
                "lung",
                "Stress hormones",
                "adrenalectomy",
                "RNASeq"
            ],
            "contactPoint": {
                "fn": "Urmila Kodavanti",
                "hasEmail": "mailto:kodavanti.urmila@epa.gov"
            },
            "distribution": [
                {
                    "title": "Henriquez 2017 Manuscript for TAAP- Data for ScienceHub - Kodavanti.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393585/Henriquez%202017%20Manuscript%20for%20TAAP-%20Data%20for%20ScienceHub%20-%20Kodavanti.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-03",
            "references": [
                "https://doi.org/10.1016/j.taap.2017.06.009"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Keyword analysis of community planning documents",
            "description": "This file contains total hits per keyword expressed as percentage of total hits for the eight domains of the human well-being index.  Additional categorical data is given for each community planning document based on publicly available demographic data for the community.  These demographic data include population size, proportion of population in a series of categories: education level, median income, and race.  Additional categorical variables are community assignment based on a community typology.  A full description of the community typology can be found in the associated supplementary material. \n\nThis dataset is associated with the following publication:\nFulford, R., M. Russell, J. Harvey, and M. Harwell. Sustainability at the community level: Searching for common ground as a part of a national strategy for decision support. U.S. Environmental Protection Agency, Washington, DC, USA, 2016.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1393795",
            "keyword": [
                "ecosystem services",
                "human well-being",
                "Community Decision-Making",
                "fundamental objectives"
            ],
            "contactPoint": {
                "fn": "Richard Fulford",
                "hasEmail": "mailto:fulford.richard@epa.gov"
            },
            "distribution": [
                {
                    "title": "KeywordComparison_SciHub.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393795/KeywordComparison_SciHub.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2017-08-24",
            "references": [
                "https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100PIKG.txt"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Fine-Tuning ADAS Algorithm Parameters ",
            "description": "With the development of the Connected Vehicle technology that facilitates wirelessly communication among vehicles and road-side infrastructure, the Advanced Driver Assistance Systems (ADAS) can be adopted as an effective tool for accelerating traffic safety and mobility optimization at various highway facilities. To this end, the traffic management centers identify the optimal ADAS algorithm parameter set that enables the maximum improvement of the traffic safety and mobility performance, and broadcast the optimal parameter set wirelessly to individual ADAS-equipped vehicles. After adopting the optimal parameter set, the ADAS-equipped drivers become active agents in the traffic stream that work collectively and consistently to prevent traffic conflicts, lower the intensity of traffic disturbances, and suppress the development of traffic oscillations into heavy traffic jams. Successful implementation of this objective requires the analysis capability of capturing the impact of the ADAS on driving behaviors, and measuring traffic safety and mobility performance under the influence of the ADAS. To address this challenge, this research proposes a synthetic methodology that incorporates the ADAS-affected driving behavior modeling and state-of-the-art microscopic traffic flow modeling into a virtually simulated environment. Building on such an environment, the optimal ADAS algorithm parameter set is identified through an optimization programming framework to enable the maximum safety and mobility improvement. The developed methodology is tested at a freeway facility under both low and high ADAS market penetration rate scenarios. The identified optimal ADAS algorithm parameter set can be used to establish multiple traffic management strategies. These strategies form a pool of candidate plans for the traffic management team to select when they face different control objectives (e.g., safety improvement more important, mobility improvement more important, or balanced safety and mobility improvement). It is also found that the traffic system optimization becomes easier to achieve as the ADAS penetration rate becomes higher. \n\nThis dataset is associated with the following publication:\nLiu, H., H. Wei, T. Zuo, Z. Li, and J. Yang. Fine-Tuning ADAS Algorithm Parameters for Optimizing Traffic Safety and Mobility in Connected Vehicle Environment.   TRANSPORTATION RESEARCH. Elsevier Science Ltd, New York, NY, USA, 76: 132-149, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390778",
            "keyword": [
                "traffic safety and mobility optimization",
                "Advanced Driver Assistance System (ADAS)",
                "driver behavior modeling",
                "microscopic traffic flow modeling"
            ],
            "contactPoint": {
                "fn": "Yingping Yang",
                "hasEmail": "mailto:yang.jeff@epa.gov"
            },
            "distribution": [
                {
                    "title": "Supplemental Data File_Fine-Tuning ADAS Algorithm Parameters .docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390778/Supplemental%20Data%20File_Fine-Tuning%20ADAS%20Algorithm%20Parameters%20.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-01-04",
            "references": [
                "https://doi.org/10.1016/j.trc.2017.01.003"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "An approach to measure parameter sensitivity in watershed hydrologic modeling",
            "description": "Abstract   Hydrologic responses vary spatially and temporally according to watershed characteristics. In this study, the hydrologic models that we developed earlier for the Little Miami River (LMR) and Las Vegas Wash (LVW) watersheds were used for detail sensitivity analyses. To compare the relative sensitivities of the hydrologic parameters of these two models, we used Normalized Root Mean Square Error (NRMSE). By combining the NRMSE index with the flow duration curve analysis, we derived an approach to measure parameter sensitivities under different flow regimes. Results show that the parameters related to groundwater are highly sensitive in the LMR watershed, whereas the LVW watershed is primarily sensitive to near surface and impervious parameters. The high and medium flows are more impacted by most of the parameters. Low flow regime was highly sensitive to groundwater related parameters. Moreover, our approach is found to be useful in facilitating model development and calibration. \n\nThis dataset is associated with the following publication:\nRanatunga, T., S. Tong, and J. Yang. An approach to measure parameter sensitivity in watershed hydrologic modeling.   Hydrological Sciences Journal. IAHS LIMITED, Oxford,  UK, 62(1): 76-92, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1390229",
            "keyword": [
                "flow duration curve",
                "words sensitivity analysis",
                "words  sensitivity analysis",
                "HSPF",
                "NRMSE",
                "model development"
            ],
            "contactPoint": {
                "fn": "Yingping Yang",
                "hasEmail": "mailto:yang.jeff@epa.gov"
            },
            "distribution": [
                {
                    "title": "Supplemental Data File_An approach to measure parameter sensitivity.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390229/Supplemental%20Data%20File_An%20approach%20to%20measure%20parameter%20sensitivity.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-01-16",
            "references": [
                "https://doi.org/10.1080/02626667.2016.1174335"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Mixing at double-Tee junctions with unequal pipe sizes in water distribution systems",
            "description": "Pipe flow mixing with various solute concentrations and flow rates at pipe junctions is investigated. The degree of mixing affects the spread of contaminants in a water distribution system. Many studies have been conducted on the mixing at the cross junctions. Yet few have focused on double-Tee junctions of unequal pipe sizes. To investigate the solute mixing at double-Tee junctions with unequal pipe sizes, a series of experiments were conducted in a turbulent regime (Re=12500\u201350000) with different Reynolds number ratios and connecting pipe lengths. It is found that dimensionless outlet concentrations depended on mixing mechanism at the impinging interface of pipe junctions. Junction with a larger pipe size ratio is associated with more complete mixing. The inlet Reynolds number ratio affects mixing more strongly than the outlet Reynolds number ratio. Furthermore, the dimensionless connecting pipe length in a double-Tee played an important and complicated role in the flow mixing. Based on these results, two-dimensional isopleth maps were developed for the calculation of normalized north outlet concentration. This dataset is not publicly accessible because: The present research is funded by the National Natural Science Foundation of China (No. 51208457 and 51478417), the Major Science and Technology Program for Water Pollution Control and Treatment in China (2012ZX07408-002 and 2012ZX07403-004), and the Fundamental Research Funds for the Central Universities. It can be accessed through the following means: Yang.jeff@epa.gov. Format: Secondary data not available. \n\nThis dataset is associated with the following publication:\nYu, T., H. Qiu, J. Yang, y. shao, and L. Tao. Mixing at double-Tee junctions with unequal pipe sizes in water distribution systems.   Water Science and Technology:  Water Supply. IWA Publishing, London,  UK, 16(6): 1595-1602, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1390232",
            "keyword": [
                "double-Tee junctions",
                "unequal pipe sizes",
                "solute mixing",
                "water distribution systems"
            ],
            "contactPoint": {
                "fn": "Yingping Yang",
                "hasEmail": "mailto:yang.jeff@epa.gov"
            },
            "distribution": [],
            "modified": "2016-12-14",
            "references": [
                "https://doi.org/10.2166/ws.2016.076"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "GMAP Charleston data",
            "description": "GMAP mobile monitoring data from Charleston study and C-PORT results. \n\nThis dataset is associated with the following publication:\nIsakov, V., T. Barzyk, B. Smith, S. Arunachalam , B. Naess , and A. Venkatram. A web-based screening tool for near-port air quality assessments.   ENVIRONMENTAL MODELLING & SOFTWARE. Elsevier Science, New York, NY,   98: 21-34, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390112",
            "keyword": [
                "air pollution",
                "dispersion modeling",
                "emissions",
                "exposure",
                "ports"
            ],
            "contactPoint": {
                "fn": "Vladilen Isakov",
                "hasEmail": "mailto:isakov.vlad@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figures4EMS2017paper.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390112/Figures4EMS2017paper.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-12-22",
            "references": [
                "https://doi.org/10.1016/j.envsoft.2017.09.004"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "18 excel spreadsheets by species and year giving reproduction and growth data.  One excel spreadsheet of herbicide treatment chemistry.",
            "description": "Excel spreadsheets by species (4 letter code is abbreviation for genus and species used in study, year 2010 or 2011 is year data collected, SH indicates data for Science Hub, date is date of file preparation).   The data in a file are described in a read me file which is the first worksheet in each file.  Each row in a species spreadsheet is for one plot (plant).  The data themselves are in the data worksheet.  \r\nOne file includes a read me description of the column in the date set for chemical analysis.  In this file one row is an herbicide treatment and sample for chemical analysis (if taken). \n\nThis dataset is associated with the following publication:\nOlszyk , D., T. Pfleeger, T. Shiroyama, M. Blakely-Smith, E. Lee , and M. Plocher. Plant reproduction is altered by simulated herbicide drift toconstructed plant communities.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 36(10): 2799-2813, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390141",
            "keyword": [
                "herbicides",
                "native plants",
                "dicamba",
                "glyphosate",
                "phytotoxicology"
            ],
            "contactPoint": {
                "fn": "David Olszyk",
                "hasEmail": "mailto:olszyk.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "CALE 2010 SH 042417.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/CALE%202010%20SH%20042417.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "CALE 2011 SH 042417.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/CALE%202011%20SH%20042417.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "ELGL 2010 SH 042417.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/ELGL%202010%20SH%20042417.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "ERLA 2010 SH 042417.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/ERLA%202010%20SH%20042417.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "ERLA 2011 SH 042417.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/ERLA%202011%20SH%20042417.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "FRVI 2010 SH 042417.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/FRVI%202010%20SH%20042417.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "FRVI 2011 SH 042417.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/FRVI%202011%20SH%20042417.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "IRTE 2010 SH 042417.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/IRTE%202010%20SH%20042417.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "POGR 2010 SH 042417.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/POGR%202010%20SH%20042417.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "POGR 2011SH 042417.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/POGR%202011SH%20042417.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "PRVU 2010 SH 050817.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/PRVU%202010%20SH%20050817.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "RAOC 2010 SH 042417.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/RAOC%202010%20SH%20042417.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Solution Chemistry 050817.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/Solution%20Chemistry%20050817.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "RAOC 2011 SH 080724.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/RAOC%202011%20SH%20080724.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "PRVU 2011 SH 081224.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/PRVU%202011%20SH%20081224.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "IRTE 2011 SH 080724.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/IRTE%202011%20SH%20080724.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "FEID 2011 SH 080724.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/FEID%202011%20SH%20080724.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "FEID 2010 SH 080824.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/FEID%202010%20SH%20080824.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "ELGL 2011 SH 080724.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390141/ELGL%202011%20SH%20080724.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2022-10-04",
            "references": [
                "https://doi.org/10.1002/etc.3839",
                "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6130323"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Bioaerosol concentrations - Figure 3 and Figure 4",
            "description": "Bioaerosol concentrations. \n\nThis dataset is associated with the following publication:\nChattopadhyay, S., S. Perkins, M. Shaw, and T. Nichols. Evaluation of Exposure to Brevundimonas diminuta and Pseudomonas aeruginosa during Showering   [HS7.44.02].   JOURNAL OF AEROSOL SCIENCE. Elsevier Science Ltd, New York, NY, USA, 114: 77-93, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1373293",
            "keyword": [
                "Bioaerosol sampler; Aerosol concentration",
                "Pathogen",
                "Exposure Assessment",
                "Brevundimonas diminuta",
                "Pseudomonas aeruginosa",
                "Bioaerosols"
            ],
            "contactPoint": {
                "fn": "Sandip Chattopadhyay",
                "hasEmail": "mailto:chattopadhyay.sandip@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure 3 and Figure 4.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1373293/Figure%203%20and%20Figure%204.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-12-13",
            "references": [
                "https://doi.org/10.1016/j.jaerosci.2017.08.008"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supplemental information",
            "description": "Supplemental information showing results of inter-comparison between C-PORT, AERMOD and R-LINE dispersion algorithms. \n\nThis dataset is associated with the following publication:\nIsakov, V., T. Barzyk, B. Smith, S. Arunachalam , B. Naess , and A. Venkatram. A web-based screening tool for near-port air quality assessments.   ENVIRONMENTAL MODELLING & SOFTWARE. Elsevier Science, New York, NY,   98: 21-34, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1374998",
            "keyword": [
                "dispersion algorithms",
                "evaluation",
                "air pollution",
                "dispersion modeling",
                "emissions",
                "exposure",
                "ports"
            ],
            "contactPoint": {
                "fn": "Vladilen Isakov",
                "hasEmail": "mailto:isakov.vlad@epa.gov"
            },
            "distribution": [
                {
                    "title": "Supplement.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374998/Supplement.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-08-15",
            "references": [
                "https://doi.org/10.1016/j.envsoft.2017.09.004"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Ozonolysis of \u03b1/\u03b2-farnesene mixture: analysis of gas-phase and particulate reaction products",
            "description": "Atmospheric oxidation of sesquiterpenes has been of considerable interest recently because of their likely contribution to ambient organic aerosol, but farnesene oxidation has been reported in only a few studies and with limited data. In the present study, a detailed chemical analysis of the organic fraction of gas and particle phases originating from the ozonolysis of a mixture of \u03b1-farnesene and \u03b2-farnesene was carried out in a 14.5 m3 smog chamber. More than 80 organic compounds bearing OH functionality were detected for the first time in this system in the gas and particle phases. The major secondary organic aerosol (SOA) components included conjugated \u03b1 farnesene trienols, hydroxyl carboxylic acid and its corresponding lactones, C3\u2013C7 linear dicarboxylic acids, and hydroxy/carbonyl/carboxylic compounds. Of particular importance was 5,6-dihydroxy-6-methylheptan-2-one (DHMHO), which was detected at high concentration. In the gas phase, the main species identified were trienols and their corresponding epoxides and diepoxides. Proposed reaction schemes are provided for selected compounds. A similar analysis was performed for ambient PM2.5 samples collected during summer 2013 as part of the SOAS to determine farnesene contributions to PM2.5. Gas chromatography\u2013mass spectrometry analysis were consistent with the occurrence of several farnesene SOA compounds, indicating the potential impact of farnesene on the regional aerosol burden. The high abundance of DHMHO in chamber SOA and its presence in ambient PM2.5 is particularly important because to our knowledge it is specific to farnesene and therefore could serve as an indicator for farnesene emitted into ambient aerosol. In the absence of authentic standards, however, it is difficult to accurately quantify the contribution of SOA originating from farnesene to ambient PM2.5. \n\nThis dataset is associated with the following publication:\nJaoui, M., M. Lewandowski, J. Offenberg, K. Docherty, and T. Kleindienst. Ozonolysis of \u03b1/\u03b2-farnesene mixture: Analysis of gas-phase and particulate reaction products.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 169: 175-192, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1376685",
            "keyword": [
                "Sesquiterpenes",
                "\u03b1-Farnesene",
                "pm2.5",
                "Conjugated triene-ol",
                "air quality",
                "Secondary Organic Aerosol",
                "air toxics",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Michael Lewandowski",
                "hasEmail": "mailto:lewandowski.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Jaoui_Farnesene_Ozone_Figures 1-9.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376685/Jaoui_Farnesene_Ozone_Figures%201-9.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-25",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2017.08.065",
                "https://pasteur.epa.gov/uploads/10.23719/1376685/documents/Farnesene_Ozone_Chromatographs.zip"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "High-Throughput Dietary Exposure Predictions for Chemical Migrants from Food Contact Substances for Use in Chemical Prioritization",
            "description": "Under the ExpoCast program, United States Environmental Protection Agency (EPA) researchers have developed a high-throughput (HT) framework for estimating aggregate exposures to chemicals from multiple pathways to support rapid prioritization of chemicals. Here, we present methods to estimate HT exposures to chemicals migrating into food from food contact substances (FCS). These methods consisted of combining an empirical model of chemical migration with estimates of daily population food intakes derived from food diaries from the National Health and Nutrition Examination Survey (NHANES). A linear regression model for migration at equilibrium was developed by fitting available migration measurements as a function of temperature, food type (i.e., fatty, aqueous, acidic, alcoholic), initial chemical concentration in the FCS (C0) and chemical properties. The most predictive variables in the resulting model were C0, molecular weight, log Kow, and food type (R2=0.71, p<0.0001). Migration-based concentrations for 1009 chemicals identified via publicly-available data sources as being present in polymer FCSs were predicted for 12 food groups (combinations of 3 storage temperatures and food type). The model was parameterized with screening-level estimates of C0 based on the functional role of chemical in FCS. By combining these concentrations with daily intakes for food groups derived from NHANES, population ingestion exposures of chemical in mg/kg-bodyweight/day (mg/kg-BW/day) were estimated. Calibrated aggregate exposures were estimated for 1931 chemicals by fitting HT FCS and consumer product exposures to exposures inferred from NHANES biomonitoring (R2=0.61, p<0.001); both FCS and consumer product pathway exposures were significantly predictive of inferred exposures. Including the FCS pathway significantly impacted the ratio of predicted exposures to those estimated to produce steady-state blood concentrations equal to in-vitro bioactive concentrations. While these HT methods have large uncertainties (and thus may not be appropriate for assessments of single chemicals), they can provide critical refinement to aggregate exposure predictions used in risk-based chemical priority\u2013setting. \n\nThis dataset is associated with the following publication:\nBiryol, D., C. Nicolas, J. Wambaugh, K. Phillips, and K. Isaacs. High-throughput dietary exposure predictions for chemical migrants from food contact substances for use in chemical prioritization.   ENVIRONMENT INTERNATIONAL. Elsevier Science Ltd, New York, NY, USA, 108: 185-194, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1374398",
            "keyword": [
                "exposure",
                "high throughput",
                "chemical prioritization",
                "food contact substances",
                "food packaging",
                "ExpoCast",
                "SHEDS"
            ],
            "contactPoint": {
                "fn": "Kristin Isaacs",
                "hasEmail": "mailto:isaacs.kristin@epa.gov"
            },
            "distribution": [
                {
                    "title": "All_Datasets.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374398/All_Datasets.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-08",
            "references": [
                "https://doi.org/10.1016/j.envint.2017.08.004"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1374398/documents/DataDictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Climiate Resilience Screening Index and Domain Scores",
            "description": "CRSI and related-domain scores for all 50 states and 3135 counties in the U.S. This dataset is not publicly accessible because: They are already available within the product. It can be accessed through the following means: Interested audiences can copy the relevant table(s) from the appropriate appendix and copy into another software package, such as Excel, for use. Format: Table-formatted results as appendices within the product (report). \n\nThis dataset is associated with the following publication:\nSummers, K., L. Harwell, K. Buck, L. Smith, J. Harvey, D. Vivian, J. Bousquin, M. McLaughlin, and S. Hafner. Development of a Climate Resilience Screening Index (CRSI): An Assessment of Resilience to Acute Meteorological Events and Selected Natural Hazards. U.S. Environmental Protection Agency, Washington, DC, USA, 2017.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1393586",
            "keyword": [
                "resilience",
                "indicators",
                "community",
                "governance",
                "natural hazards",
                "CRSI"
            ],
            "contactPoint": {
                "fn": "James Summers",
                "hasEmail": "mailto:summers.kevin@epa.gov"
            },
            "distribution": [],
            "modified": "2017-07-10",
            "references": [
                "https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100SSN6.txt"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Retrospective_Mining_of_Tox_Data_Anemia_Case_Study_RegToxPharm Data",
            "description": "Data from a study to critically examine some of the issues of using data from ToxRefDB, a database largely composed of guideline studies for pesticidal active ingredients, using a case study focusing on chemically-induced anemia. \n\nThis dataset is associated with the following publication:\nJudson, R.S., M. Martin, G. Patlewicz, and C.E. Wood. (Reg. Tox. Pharm.) Retrospective Mining of Toxicology Data to Discover Multispecies and Chemical Class Effects: Anemia as a Case Study.   REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 86: 74-92, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1392996",
            "keyword": [
                "ToxRefDB",
                "ACToR"
            ],
            "contactPoint": {
                "fn": "Richard Judson",
                "hasEmail": "mailto:judson.richard@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/comptox/STAFF/rjudson/publications/Judson%20Anemia%202017/",
                    "accessURL": "https://gaftp.epa.gov/comptox/STAFF/rjudson/publications/Judson%20Anemia%202017/"
                }
            ],
            "modified": "2017-02-21",
            "references": [
                "https://doi.org/10.1016/j.yrtph.2017.02.015"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "This file contains data used to generate figures shown in Phelps et al. Microbial colonization is required for normal neurobehavioral development in zebrafish. Scientific Reports. 2017.",
            "description": "Data used to generate figures shown in Phelps et al. \n\nThis dataset is associated with the following publication:\nPhelps, D., N. Brinkman, S. Keely, E. Anneken, T. Catron, D. Betancourt, C. Wood, S. Espenschied, J. Rawls, and T. Tal. Microbial colonization is required for normal neurobehavioral development in zebrafish.   Scientific Reports. Nature Publishing Group, London,  UK, 11(7): 11244, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1393821",
            "keyword": [
                "zebrafish",
                "microbiome",
                "microbiota",
                "DNT",
                "developmental neurotoxicity",
                "Children's Environmental Health"
            ],
            "contactPoint": {
                "fn": "Tamara Tal",
                "hasEmail": "mailto:tal.tamara@epa.gov"
            },
            "distribution": [
                {
                    "title": "20170830_ScienceHub_FINAL.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393821/20170830_ScienceHub_FINAL.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-30",
            "references": [
                "https://doi.org/10.1038/s41598-017-10517-5",
                "https://pasteur.epa.gov/uploads/10.23719/1393821/documents/20170830_ScienceHub_FINAL.xlsx"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Tissue disposition of bifenthrin in the rat",
            "description": "Tissue disposition of bifenthrin in the rat and oral and intravenous administration. \n\nThis dataset is associated with the following publication:\nHughes , M., D. Ross , B. Edwards , M. DeVito, and J. Starr. Tissue time course and bioavailability of the pyrethroid insecticide bifenthrin in the Long-Evans rat.   XENOBIOTICA. Taylor & Francis, Inc., Philadelphia, PA, USA, 46(5): 430-438, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390107",
            "keyword": [
                "bifenthrin",
                "bioavailability",
                "pyrethroid",
                "pesticides",
                "pyrethroids",
                "disposition"
            ],
            "contactPoint": {
                "fn": "Michael Hughes",
                "hasEmail": "mailto:hughes.michaelf@epa.gov"
            },
            "distribution": [
                {
                    "title": "bifenthrin tissue concentration normalized by dose.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390107/bifenthrin%20tissue%20concentration%20normalized%20by%20dose.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Serial blood bifenthrin concentrations after oral or iv admin.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390107/Serial%20blood%20bifenthrin%20concentrations%20after%20oral%20or%20iv%20admin.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-05-01",
            "references": [
                "https://doi.org/10.3109/00498254.2015.1081710"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Computational Model of Secondary Palate Fusion and Disruption ChemResTox Data",
            "description": "Morphogenetic events are driven by cell-generated physical forces and complex cellular dynamics. To improve our capacity to predict developmental effects from cellular alterations, we built a multi-cellular agent-based model in CompuCell3D that recapitulates the cellular networks and collective cell behavior underlying growth and fusion of the mammalian secondary palate. The model incorporated multiple signaling pathways (TGF?, BMP, FGF, EGF, SHH) in a biological framework to recapitulate morphogenetic events from palatal outgrowth through midline fusion. It effectively simulated higher-level phenotypes (e.g., midline contact, medial edge seam (MES) breakdown, mesenchymal confluence, fusion defects) in response to genetic or environmental perturbations. Perturbation analysis of various control features revealed model functionality with respect to cell signaling systems and feedback loops for growth and fusion, diverse individual cell behaviors and collective cellular behavior leading to physical contact and midline fusion, and quantitative analysis of the TGF/EGF switch that controls MES breakdown \u2013 a key event in morphogenetic fusion. The virtual palate model was then executed with theoretical chemical perturbation scenarios to simulate switch behavior leading to a disruption of fusion following chronic (e.g., dioxin) and acute (e.g., retinoic acid, hydrocortisone) toxicant exposures. This computer model adds to similar systems models toward a \u2018virtual embryo\u2019 for simulation and quantitative prediction of adverse developmental outcomes following genetic perturbation and/or environmental. \n\nThis dataset is associated with the following publication:\nHutson, S., M. Leung, N. Baker, R. Spencer, and T. Knudsen. (CHEMICAL RESEARCH IN TOXICOLOGY) Computational Model of Secondary Palate Fusion and Disruption.   CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, USA, 30(4): 965-979, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1395041",
            "keyword": [
                "Computational Biology",
                "Morphogenetic fusion",
                "Predictive Toxicology",
                "Children\u2019s Health",
                "Agent-Based Model",
                "CompuCell3D",
                "Developmental Toxicity",
                "vEmbryo",
                "virtual embryo",
                "virtual tissues",
                "tipping points"
            ],
            "contactPoint": {
                "fn": "Thomas Knudsen",
                "hasEmail": "mailto:knudsen.thomas@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/Knudsen/Computational_Model_of_Secondary_Palate_Fusion/",
                    "accessURL": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/Knudsen/Computational_Model_of_Secondary_Palate_Fusion/"
                }
            ],
            "modified": "2017-09-26",
            "references": [
                "https://doi.org/10.1021/acs.chemrestox.6b00350"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Stachler et al. 2017 Figure 2 data",
            "description": "Estimated mean log10 concentration of genetic markers for CQQ_056, CPQ_064, HF183/BacR287, and HumM2 genetic markers in nine sewage and two surface water samples. \n\nThis dataset is associated with the following publication:\nStachler, E., C. Kelty, M. Sivaganesan, X. Li, K. Bibby, and O. Shanks. Quantitative CrAssphage PCR Assays for Human Fecal Pollution Measurement.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(16): 9146-9154, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1395008",
            "keyword": [
                "Microbial Source Tracking",
                "human fecal pollution",
                "qPCR",
                "CrAssphage",
                "water quality"
            ],
            "contactPoint": {
                "fn": "Orin Shanks",
                "hasEmail": "mailto:shanks.orin@epa.gov"
            },
            "distribution": [
                {
                    "title": "Stachler et al 2017_Data Set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395008/Stachler%20et%20al%202017_Data%20Set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-18",
            "references": [
                "https://doi.org/10.1021/acs.est.7b02703"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supporting data for Suen et al_A-0zpd ",
            "description": "Tables, Figures, and Supplemental Materials for doi: 10.1158/1541-7786.MCR-16-0084. \n\nThis dataset is associated with the following publication:\nSuen, A., W. Jefferson, C. Wood, E. Padilla-Banks, V. Bae-Jump, and C. Williams. SIX1 Oncoprotein as a Biomarker in a Model of Hormonal Carcinogenesis and in Human Endometrial Cancer..   Molecular Cancer Research. American Association for Cancer Research, Inc., Philadelphia, PA, USA, 14(9): 849-858, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1395063",
            "keyword": [
                "biomarker",
                "oncofetal",
                "diethylstilbestrol",
                "estrogenic chemicals",
                "estrogen",
                "uterine cancer"
            ],
            "contactPoint": {
                "fn": "Charles Wood",
                "hasEmail": "mailto:wood.charles@epa.gov"
            },
            "distribution": [
                {
                    "title": "Suen et al_A-0zpd_Tables 1-2, S1, S2_v2.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395063/Suen%20et%20al_A-0zpd_Tables%201-2%2C%20S1%2C%20S2_v2.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Suen et al_A-0zpd_Figures 1-4,S1_v2.7.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395063/Suen%20et%20al_A-0zpd_Figures%201-4%2CS1_v2.7.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2016-02-24",
            "references": [
                "https://doi.org/10.1158/1541-7786.mcr-16-0084"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "County Level Risk scores broken down into three land-types (natural, dual-benefit, and built) as well as three year-ranges (2000-2005, 2005-2010, and 2010-2015). ",
            "description": "The data set contains four tables with all U.S. counties.  Three of the data tables are for the 5-year ranges, while the fourth contains the overall risk score.  Within each table is a breakdown of risk by land type (natural, dual-benefit, and built) along with an overall risk score. \n\nThis dataset is associated with the following publications:\nSummers, K., L. Harwell, K. Buck, L. Smith, J. Harvey, D. Vivian, J. Bousquin, M. McLaughlin, and S. Hafner. Development of a Climate Resilience Screening Index (CRSI): An Assessment of Resilience to Acute Meteorological Events and Selected Natural Hazards. U.S. Environmental Protection Agency, Washington, DC, USA, 2017.\nBuck, K., K. Summers, S. Hafner, L. Harwell, and L. Smith. Development of a Multi-Hazard Landscape for Exposure and Risk Interpretation: The PRISM Approach.   Current Environmental Engineering. Bentham Science Publishers, Ltd., Oak Park, IL, USA, 6(1): 74-94, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1394633",
            "keyword": [
                "Risk",
                "resilience",
                "multiple stressors",
                "natural hazards",
                "technological hazards",
                "counties"
            ],
            "contactPoint": {
                "fn": "Kyle Buck",
                "hasEmail": "mailto:buck.kyle@epa.gov"
            },
            "distribution": [
                {
                    "title": "PRISM_ScienceHubEntry.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394633/PRISM_ScienceHubEntry.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-28",
            "references": [
                "https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100SSN6.txt",
                "https://doi.org/10.2174/2212717806666190204103455"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Nickel proteomics data",
            "description": "The dataset include the following figures and tables: 1)Changes in protein expression of the 14 pathway regulators induced by Ni (II). 2)Hierarchical clustering of 12 differentially expressed or phosphorylated proteins in BEAS-2B cells treated with Ni (II). 3) Relative cell survival (X-axis) vs. protein expression or phosphorylation levels (Y-axis) in BEAS-2B control cells treated with Ni (II) at 4 different concentrations 4)Four representative proteins, PDIA1, ACADM, RUVBL1, PRDX2 identified using 2-DE profiling were either increased or decreased in a concentration responsive manner 5)Networks of proteins showing inter-relationships and pathways which was obtained using IPA 6)Schematic representation of the interplay of the core proteins and cytotoxicity pathways mediated by Ni (II).  7) some supplementary data. \n\nThis dataset is associated with the following publication:\nGe , Y., M. Bruno , N. Coates , K. Wallace , D. Andrews , A. Swank , W. Winnik , and J. Ross. Proteomic Assessment of Biochemical Pathways That Are Critical to Nickel-Induced Toxicity Responses in Human Epithelial Cells.   PLoS ONE. Public Library of Science, San Francisco, CA, USA, 11(9): 1-20, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1395012",
            "keyword": [
                "nickel proteomic profile",
                "nickel",
                "dose response",
                "protein expression",
                "phosphorylation",
                "proteomics",
                "cytotoxicity",
                "metals",
                "sys-tems biology",
                "ELISA",
                "human epithelial cells"
            ],
            "contactPoint": {
                "fn": "Yue Ge",
                "hasEmail": "mailto:ge.yue@epa.gov"
            },
            "distribution": [
                {
                    "title": "Nickel data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395012/Nickel%20data.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "data  for figure 1 3 and 4B.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395012/data%20%20for%20figure%201%203%20and%204B.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-18",
            "references": [
                "https://doi.org/10.1371/journal.pone.0162522"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1395012/documents/data%20%20for%20figure%201.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data Set for the manuscript entitled, \"Sample Processing Approach for Detection of Ricin in Surface Samples.\"",
            "description": "Figure. \n\nThis dataset is associated with the following publication:\nShah, S., S. Kane, A.M. Erler, and T. Alfaro. Sample Processing Approach for Detection of Ricin in Surface Samples  [HS7.52.04 - 0671].   JOURNAL OF IMMUNOLOGICAL METHODS. Elsevier Science Ltd, New York, NY, USA,  9, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390124",
            "keyword": [
                "Ricin",
                "Sample Processing",
                "Indoor-Outdoor Decontamination",
                "Biotoxin"
            ],
            "contactPoint": {
                "fn": "Sanjivkumar Shah",
                "hasEmail": "mailto:shah.sanjiv@epa.gov"
            },
            "distribution": [
                {
                    "title": "ShahSanjivkumar_HS7-52-04-0641_Data-Metadata_RicinSampleprocessingManuscript_20170331.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390124/ShahSanjivkumar_HS7-52-04-0641_Data-Metadata_RicinSampleprocessingManuscript_20170331.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-12-21",
            "references": [
                "https://doi.org/10.1016/j.jim.2017.08.008"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1390124/documents/ShahSanjivkumar_HS7-52-04-0641_Data-Metadata_RicinSampleprocessingManuscript_20170227.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Potential Wetland Restoration Indicators data for the EnviroAtlas",
            "description": "Data is based on overlap of topographic, soil drainage, and national wetland inventory areas. \n\nThis dataset is associated with the following publication:\nHorvath, E., J. Christensen, M. Mehaffey, and A. Neale. Building a Potential Wetland Restoration Indicator for the Contiguous United States..   ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 83: 462-473, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1371467",
            "keyword": [
                "compound topographic index",
                "soil drainage",
                "national wetland inventory",
                "wetland restoration",
                "mapping methods",
                "contiguous United States",
                "ecosystem services",
                "EnviroAtlas",
                "geographic information systems"
            ],
            "contactPoint": {
                "fn": "Elena Horvath",
                "hasEmail": "mailto:horvath.elena@epa.gov"
            },
            "distribution": [
                {
                    "title": "Table1_SoilDrainageandTopography.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371467/Table1_SoilDrainageandTopography.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table2_PotentialWetlandandNWI.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371467/Table2_PotentialWetlandandNWI.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table3_PotentiallyRestorableWetland.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371467/Table3_PotentiallyRestorableWetland.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://www.epa.gov/enviroatlas/enviroatlas-data",
                    "accessURL": "https://www.epa.gov/enviroatlas/enviroatlas-data"
                },
                {
                    "title": "https://edg.epa.gov/metadata/rest/document?id=%7B669E59E0-F583-4D98-A0D6-6C68E2E97C76%7D",
                    "accessURL": "https://edg.epa.gov/metadata/rest/document?id=%7B669E59E0-F583-4D98-A0D6-6C68E2E97C76%7D"
                }
            ],
            "modified": "2017-04-19",
            "references": [
                "https://doi.org/10.1016/j.ecolind.2017.07.026"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Recreational freshwater fishing drives non-native aquatic species richness patterns at a continental scale",
            "description": "Aim. Mapping the geographic distribution of non-native aquatic species is a critically important precursor to understanding the anthropogenic and environmental factors that drive freshwater biological invasions. Such efforts are often limited to local scales and/or to single species, due to the challenges of data acquisition at larger scales. Here we map the distribution of exotic freshwater species richness across the continental United States and investigate the role of human activity in driving macroscale patterns of aquatic invasion. \n\nLocation. The continental United States.\n\nMethods. We assembled maps of non-native aquatic species richness by compiling occurrence data on exotic animal and plant species from publicly accessible databases. Using a dasymetric model of human population density and a spatially explicit model of recreational freshwater fishing demand we analyzed the effect of these metrics of human influence on the degree of invasion at the watershed scale, while controlling for spatial and sampling bias. We also assessed the effects that a temporal mismatch between occurrence data (collected since 1815) and cross-sectional predictors (developed using 2010 data) may have on model fit. \n\nResults. Non-native aquatic species richness exhibits a highly patchy distribution, with hotspots in the Northeast, Great Lakes, Florida, and human population centers on the Pacific coast. These richness patterns are correlated with population density, but are much more strongly predicted by patterns of recreational fishing demand. These relationships are strengthened by temporal matching of datasets and are robust to corrections for sampling effort.\n\nMain Conclusions. Distributions of aquatic invasive species across the continental US are better predicted by freshwater recreational fishing than by human population density. This suggests that observed patterns are driven by a mechanistic link between recreational activity and aquatic invasive species richness, and are not merely the outcome of sampling bias associated with human population density. \n\nThis dataset is associated with the following publication:\nDavis, A., and J. Darling. Recreational freshwater fishing drives non-native aquatic species richness patterns at a continental scale (journal).   Diversity and Distributions. Blackwell Publishing Limited, Oxford,  UK, 23(6): 692-702, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1377814",
            "keyword": [
                "Aquatic invasive species",
                "non-native species richness",
                "populations density",
                "recreational water",
                "sampling effort",
                "rarefaction",
                "non-indigenous aquatic species",
                "biodiversity",
                "threatened and endangered species",
                "geospatial analysis",
                "EnviroAtlas"
            ],
            "contactPoint": {
                "fn": "John Darling",
                "hasEmail": "mailto:darling.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "JohnDarling_A-c86j_DDdata_20170831.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377814/JohnDarling_A-c86j_DDdata_20170831.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-06-14",
            "references": [
                "https://doi.org/10.1111/ddi.12557"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1377814/documents/JohnDarling_A-c86j_DDmetadata_20170831.xml",
            "describedByType": "application/xml",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "HTTK R Package v1.4 - JSS Article on HTTK: R Package for High-Throughput Toxicokinetics",
            "description": "httk: High-Throughput Toxicokinetics\n\nFunctions and data tables for simulation and statistical analysis of chemical toxicokinetics (\"TK\") using data obtained from relatively high throughput, in vitro studies. Both physiologically-based (\"PBTK\") and empirical (e.g., one compartment) \"TK\" models can be parameterized for several hundred chemicals and multiple species. These models are solved efficiently, often using compiled (C-based) code. A Monte Carlo sampler is included for simulating biological variability and measurement limitations. Functions are also provided for exporting \"PBTK\" models to \"SBML\" and \"JARNAC\" for use with other simulation software. These functions and data provide a set of tools for in vitro-in vivo extrapolation (\"IVIVE\") of high throughput screening data (e.g., ToxCast) to real-world exposures via reverse dosimetry (also known as \"RTK\"). \n\nThis dataset is associated with the following publication:\nPearce , R., C. Strope , W. Setzer , N. Sipes , and J. Wambaugh. (Journal of Statistical Software) HTTK: R Package for High-Throughput Toxicokinetics.   Journal of Statistical Software. American Statistical Association, Alexandria, VA, USA, 79(4): 1-26, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1390267",
            "keyword": [
                "in vitro to in vivo extrapolation (IVIVE)",
                "PBPK-reverse dosimetry",
                "pbpk",
                "ToxCast",
                "toxicokinetics",
                "physiologically-based pharmacokinetic model",
                "httk",
                "high throughput toxicokinetics",
                "ExpoCast",
                "exposure"
            ],
            "contactPoint": {
                "fn": "John Wambaugh",
                "hasEmail": "mailto:wambaugh.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://cran.r-project.org/web/packages/httk/index.html",
                    "accessURL": "https://cran.r-project.org/web/packages/httk/index.html"
                }
            ],
            "modified": "2016-02-03",
            "references": [
                "https://doi.org/10.18637/jss.v079.i04",
                "https://www.jstatsoft.org/article/view/v079i04"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "HTTK R Package v1.5 - Identifying populations sensitive to environmental chemicals by simulating toxicokinetic variability",
            "description": "httk: High-Throughput Toxicokinetics\n\nFunctions and data tables for simulation and statistical analysis of chemical toxicokinetics (\"TK\") using data obtained from relatively high throughput, in vitro studies. Both physiologically-based (\"PBTK\") and empirical (e.g., one compartment) \"TK\" models can be parameterized for several hundred chemicals and multiple species. These models are solved efficiently, often using compiled (C-based) code. A Monte Carlo sampler is included for simulating biological variability and measurement limitations. Functions are also provided for exporting \"PBTK\" models to \"SBML\" and \"JARNAC\" for use with other simulation software. These functions and data provide a set of tools for in vitro-in vivo extrapolation (\"IVIVE\") of high throughput screening data (e.g., ToxCast) to real-world exposures via reverse dosimetry (also known as \"RTK\"). \n\nThis dataset is associated with the following publication:\nRing, C., R. Pearce, W. Setzer, B. Wetmore, and J. Wambaugh. (Environment International)  Refining high-throughput prioritization of environmental chemicals to include inter-individual variability across subpopulations.   ENVIRONMENT INTERNATIONAL. Elsevier Science Ltd, New York, NY, USA, 106: 105-118, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1390268",
            "keyword": [
                "pbtk",
                "physiologically-based pharmacokinetic model",
                "in vitro in vivo extrapolation",
                "ToxCast",
                "PBPK-reverse dosimetry",
                "r package",
                "httk",
                "high throughput toxicokinetics",
                "ExpoCast",
                "exposure"
            ],
            "contactPoint": {
                "fn": "John Wambaugh",
                "hasEmail": "mailto:wambaugh.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://cran.r-project.org/web/packages/httk/index.html",
                    "accessURL": "https://cran.r-project.org/web/packages/httk/index.html"
                }
            ],
            "modified": "2017-03-03",
            "references": [
                "https://doi.org/10.1016/j.envint.2017.06.004",
                "https://www.sciencedirect.com/science/article/pii/S0160412017301204?via%3Dihub",
                "https://ars.els-cdn.com/content/image/1-s2.0-S0160412017301204-mmc1.xlsx",
                "https://ars.els-cdn.com/content/image/1-s2.0-S0160412017301204-mmc2.docx"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Datasets in Gene Expression Omnibus used in the study ORD-019001: Compensatory changes in CYP expression in three different toxicology mouse models: CAR-null, Cyp3a-null, and Cyp2b9/10/13-null mice.",
            "description": "Accession numbers of microarray data sets used in the analysis. \n\nThis dataset is associated with the following publication:\nKumar, R., L. Mota, E. Litoff, J. Rooney, T. Boswell, E. Courter, C. Henderson, J. Hernandez, C. Corton, D. Moore, and W. Baldwin. Compensatory changes in CYP expression in three different toxicology mouse models: CAR-null, Cyp3a-null, and Cyp2b9/10/13-null mice.   PLoS ONE. Public Library of Science, San Francisco, CA, USA, 12(3): 1-24, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1389078",
            "keyword": [
                "microarray accession numbers",
                "microarray",
                "constitutive activated receptor (CAR)",
                "Cyp2b",
                "Cyp3a"
            ],
            "contactPoint": {
                "fn": "Jon Corton",
                "hasEmail": "mailto:corton.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data submission for A-xOkz.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1389078/Data%20submission%20for%20A-xOkz.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-10-20",
            "references": [
                "https://doi.org/10.1371/journal.pone.0174355"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Judson_Mansouri_Automated_Chemical_Curation_QSAREnvRes_Data",
            "description": "Here we describe the development of an automated  KNIME workflow to curate and correct errors in the structure and identity of chemicals using the publically available PHYSPROP physico-chemical properties and environmental fate datasets. The workflow first assembles structure-identity pairs using up to four provided chemical identifiers, including chemical name, CASRNs, SMILES, and MolBlock. Problems detected  included errors and mismatches in chemical structure formats, identifiers, and various structure validation issues, including hypervalency and stereochemistry descriptions. Subsequently, a machine learning procedure was applied to evaluate the impact of this curation process. The performance of QSAR models built on only the highest quality subset of the original dataset was compared to the larger curated and corrected data set. The latter showed statistically improved predictive performance. The final workflow was used to curate the full list of PHYSPROP datasets, and is being made publically available for further usage and integration by the scientific community. \n\nThis dataset is associated with the following publication:\nMansouri, K., C. Grulke, A. Richard, R. Judson, and A. Williams. (SAR AND QSAR IN ENVIRONMENTAL RESEARCH) An automated curation procedure for addressing chemical errors and inconsistencies in public datasets used in QSAR modeling.   SAR AND QSAR IN ENVIRONMENTAL RESEARCH. Taylor & Francis, Inc., Philadelphia, PA, USA, 27(11): 911-937, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1394621",
            "keyword": [
                "DSSTox",
                "Data curation",
                "QSAR modeling",
                "physicochemical properties",
                "Open Data",
                "ACToR"
            ],
            "contactPoint": {
                "fn": "Richard Judson",
                "hasEmail": "mailto:judson.richard@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/Sustainable_Chemistry_Data/Chemistry_Dashboard/PHYSPROP_Analysis/",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/Sustainable_Chemistry_Data/Chemistry_Dashboard/PHYSPROP_Analysis/"
                }
            ],
            "modified": "2017-04-13",
            "references": [
                "https://doi.org/10.1080/1062936x.2016.1253611"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Datasets used in ORD-018902: Bisphenol A alternatives can effectively substitute for estradiol ",
            "description": "Gene Expression Omnibus numbers only. \n\nThis dataset is associated with the following publication:\nMesnage, R., A. Phedonos, M. Arno, S. Balu, C. Corton, and M. Antoniou. Transcriptome profiling reveals bisphenol A alternatives activate estrogen receptor alpha in human breast cancer cells.   TOXICOLOGICAL SCIENCES. Society of Toxicology,    158(2): 431-443, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1376229",
            "keyword": [
                "bisphenol A alternatives",
                "endocrine disruption",
                "MCF-7 cell line",
                "human breast cancer",
                "estrogen receptor"
            ],
            "contactPoint": {
                "fn": "Jon Corton",
                "hasEmail": "mailto:corton.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data submission for A-6wwx.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376229/Data%20submission%20for%20A-6wwx.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-01",
            "references": [
                "https://doi.org/10.1093/toxsci/kfx101"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "IATA-Bayesian Network Model for Skin Sensitization Data",
            "description": "Since the publication of the Adverse Outcome Pathway (AOP) for skin sensitization, there have been many efforts to develop systematic approaches to integrate the information generated from different key events for decision making. The types of information characterizing key events in an AOP can be generated from in silico, in chemico, in vitro or in vivo approaches. Integration of this information and interpretation for decision making are known as integrated approaches to testing and assessment or IATA. One such IATA that has been developed was published by Jaworska et al (2013) which describes a Bayesian network model known as ITS-2. The current work evaluated the performance of ITS-2 using a stratified cross validation approach.  We also characterized the impact of refinements to the network by replacing the most significant component, the output from a commercial expert system TIMES-SS with structural alert information readily generated from the freely available OECD QSAR Toolbox. Lack of any structural alert flags or TIMES-SS predictions, yielded a sensitization potential prediction of 79% +3%/-4%. If the TIMES-SS prediction was replaced by an indicator for the presence of a structural alert, the network predictivity increased to 84% +2%/-4%, which was only slightly less than found for the original network (89% &plusmn;2%). The local applicability domain of the original ITS-2 network was also evaluated using reaction mechanistic domains to better understand what types of chemicals ITS-2 was able to make the best predictions for &ndash; i.e. a local validity domain analysis.  We ultimately found that the original network was successful at predicting which chemicals would be sensitizers, but not at predicting their relative potency. \n\nThis dataset is associated with the following publication:\nFitzpatrick, J., and G. Patlewicz. (SAR AND QSAR IN ENVIRONMENTAL RESEARCH) Application of IATA - A case study in evaluating the global and local performance of a Bayesian Network model for Skin Sensitization.   SAR AND QSAR IN ENVIRONMENTAL RESEARCH. Taylor & Francis, Inc., Philadelphia, PA, USA, 28(4): 297-310, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1395040",
            "keyword": [
                "skin sensitization",
                "IATA",
                "qsar",
                "ITS",
                "Bayesian network model",
                "DSSTox"
            ],
            "contactPoint": {
                "fn": "Ann Richard",
                "hasEmail": "mailto:richard.ann@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/PatlewiczGrace/IATA_and_Bayesian_Network_Model_for_Skin_Sensitization/",
                    "accessURL": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/PatlewiczGrace/IATA_and_Bayesian_Network_Model_for_Skin_Sensitization/"
                }
            ],
            "modified": "2017-08-07",
            "references": [
                "https://doi.org/10.1080/1062936x.2017.1311941"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Identifying Prevalent Chemical Mixtures in the US Population EHP Data",
            "description": "Frequent itemset mining (FIM), a technique used for finding patterns in consumer purchasing behavior, can be applied to data from large-scale biomonitoring studies to identify combinations of chemicals that frequently co-occur in people. As a proof of concept, we applied FIM to biomonitoring data from the National Health and Nutrition Examination Survey. In this way, we identified 90 chemical combinations consisting of relatively few chemicals that occur in at least 30% of the US population, as well as 3 super-combinations consisting of relatively many chemicals that occur in a small but non-negligible proportion of the US population. Thus, we have demonstrated a technique for narrowing a large number of possible chemical combinations down to a much smaller collection of prevalent chemical combinations. \n\nThis dataset is associated with the following publication:\nKapraun, D.F., J.F. Wambaugh, R. Tornero-Velez, and R.W. Setzer. (ENVIRONMENTAL HEALTH PERSPECTIVES) Identifying Prevalent Chemical Mixtures in the US Population.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 125(8): 1-16, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1395052",
            "keyword": [
                "chemical mixtures",
                "frequent itemset mining (FIM)",
                "NHANES",
                "biomonitoring",
                "ExpoCast",
                "exposure"
            ],
            "contactPoint": {
                "fn": "John Wambaugh",
                "hasEmail": "mailto:wambaugh.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://ehp.niehs.nih.gov/EHP1265/#tab3",
                    "accessURL": "https://ehp.niehs.nih.gov/EHP1265/#tab3"
                }
            ],
            "modified": "2017-08-24",
            "references": [
                "https://doi.org/10.1289/ehp1265"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Datasets in Gene Expression Omnibus used in the study ORD-020382: Evaluation of estrogen receptor alpha activation by glyphosate-based herbicide constituents ",
            "description": "GEO accession number of the microarray study. \n\nThis dataset is associated with the following publication:\nMesnage, R., A. Phedonos, M. Biserni, M. Arno, S. Balu, C. Corton, R. Ugarte, and M. Antoniou. Evaluation of estrogen receptor alpha activation by glyphosate-based herbicide constituents.   FOOD AND CHEMICAL TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 108: 30-42, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1376228",
            "keyword": [
                "glyphosate",
                "estrogen receptor",
                "breast cancer",
                "MCF-7 cells"
            ],
            "contactPoint": {
                "fn": "Jon Corton",
                "hasEmail": "mailto:corton.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data submission for A-pk17.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376228/Data%20submission%20for%20A-pk17.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-11-01",
            "references": [
                "https://doi.org/10.1016/j.fct.2017.07.025"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "PPAR\u03b1-independent transcriptional targets of perfluoroalkyl acids revealed by transcript profiling",
            "description": "Microarray datasets used in the analysis. \n\nThis dataset is associated with the following publication:\nRosen, M., K. Das, J. Rooney, B. Abbott, C. Lau, and C. Corton. PPAR\u03b1-independent transcriptional targets of perfluoroalkyl acids revealed by transcript profiling.   TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 387: 95-107, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1376226",
            "keyword": [
                "Gene Expression Omnibus Accession Numbers",
                "perfluorinated chemicals",
                "microarray",
                "liver cancer",
                "steatosis",
                "constitutive activated receptor (CAR)",
                "peroxisome proliferator-activated receptor gamma",
                "peroxisome proliferator-activated receptor alpha",
                "estrogen receptor",
                "STAT5b",
                "PFOA",
                "PFOS",
                "PFNA",
                "PFHxS"
            ],
            "contactPoint": {
                "fn": "Jon Corton",
                "hasEmail": "mailto:corton.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data submission for A-zkhs.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376226/Data%20submission%20for%20A-zkhs.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-10-13",
            "references": [
                "https://doi.org/10.1016/j.tox.2017.05.013"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Precipitation and stream water stable isotope data from the Marys River, Oregon in water year 2015.",
            "description": "Water stable isotope data collected from a range of streams throughout the Marys River basin in water year 2015, and precipitation data collected within the basin at a range of elevations. \n\nThis dataset is associated with the following publication:\nNickolas, L., C. Segura, and J.R. Brooks. The influence of lithology on surface water sources.   Hydrological Processes. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 31(10): 1913-1925, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1396010",
            "keyword": [
                "Marys River",
                "Oregon",
                "Corvallis",
                "precipitation",
                "streamflow",
                "lithology",
                "water resources",
                "river flow",
                "stable isotopes",
                "water supply",
                "geology",
                "climate change"
            ],
            "contactPoint": {
                "fn": "Jacqueline Brooks",
                "hasEmail": "mailto:brooks.reneej@epa.gov"
            },
            "distribution": [
                {
                    "title": "Stable Isotope Stream data from Marys River Basin - OR WY2015.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1396010/Stable%20Isotope%20Stream%20data%20from%20Marys%20River%20Basin%20-%20OR%20WY2015.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Stable Isotope Precipitation data from Marys River Basin - OR WY2015.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1396010/Stable%20Isotope%20Precipitation%20data%20from%20Marys%20River%20Basin%20-%20OR%20WY2015.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-12",
            "references": [
                "https://doi.org/10.1002/hyp.11156"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Sorption of cesium onto the mineral phases and cement ",
            "description": "Numerical data corresponding to manuscript figures. \n\nThis dataset is associated with the following publication:\nKaminski, M., C. Mertz, J. Jerden, M. Kalensky, N. Kivenas , and M. Magnuson. Sorption of cesium onto the mineral phases and cement of concrete and desorption into simple salt solutions.   JOURNAL OF ENVIRONMENTAL RADIOACTIVITY. Elsevier Science Ltd, New York, NY, USA,  165-171, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1390161",
            "keyword": [
                "radiological urban decontamination",
                "cesium",
                "Concrete",
                "cement",
                "RDD",
                "gross decontamination",
                "indoor/outdoor decontamination",
                "IWATERS",
                "nuclear power plant",
                "NPP",
                "IND",
                "nuclear"
            ],
            "contactPoint": {
                "fn": "Matthew Magnuson",
                "hasEmail": "mailto:magnuson.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cs aggregate concrete_Data-hmh5_SDMP_20170301.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390161/Cs%20aggregate%20concrete_Data-hmh5_SDMP_20170301.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-02-24",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2016.07.077"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "County-Level Human Well-Being Index and Domain Scores (2000-2010) plus EQI data set (2000-2005)",
            "description": "The HWBI_Draft_1 is an internal map service being prepared for public release (early FY18). This map services contains mean county-level HWBI, domain, indicators and service scores related to research efforts completed in 2014. The EQI map service is a publically accessible map services that contains average county-level results for 2000-2005. \n\nThis dataset is associated with the following publication:\nHarwell, L., L. Smith, and K. Summers. Modified HWBI Model(s) Linking Service Flows to Well-Being Endpoints: Accounting for Environmental Quality. U.S. Environmental Protection Agency, Washington, DC, USA, 2017.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1395339",
            "keyword": [
                "HWBI",
                "EQI",
                "indicators",
                "composite index"
            ],
            "contactPoint": {
                "fn": "Linda Harwell",
                "hasEmail": "mailto:harwell.linda@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gispub.epa.gov/arcgis/rest/services/ORD/HumanWellBeingIndex/MapServer",
                    "accessURL": "https://gispub.epa.gov/arcgis/rest/services/ORD/HumanWellBeingIndex/MapServer"
                },
                {
                    "title": "https://gispub.epa.gov/arcgis/rest/services/ORD/EnvironmentalQualityIndex/MapServer",
                    "accessURL": "https://gispub.epa.gov/arcgis/rest/services/ORD/EnvironmentalQualityIndex/MapServer"
                }
            ],
            "modified": "2017-09-26",
            "references": [
                "https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100ST29.txt"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The Acute Toxicity of Major Ions to Ceriodaphnia dubia. II. Empirical Relationships in Binary Salt Mixtures",
            "description": "This dataset provides concentration-response data and associated general chemistry conditions for 29 experiments consisting of 209 tests regarding the acute toxicity of binary mixtures of major ions to Ceriodaphnia dubia; it also provides LC50 estimates and the estimated ion mixtures at the LC50 for each toxicity test. \n\nThis dataset is associated with the following publication:\nErickson, R., D. Mount, T. Highland, R. Hockett, D. Hoff, C. Jenson, T. Norberg-King, and K. Peterson. The acute toxicity of major ion salts to Ceriodaphnia dubia.  II.  Empirical relationships in binary salt mixtures.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 36(6): 1525-1537, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1395341",
            "keyword": [
                "Ceriodaphnia dubia",
                "Acute Toxicity",
                "Binary Salt Mixtures",
                "Major Ion Toxicity",
                "Freshwater"
            ],
            "contactPoint": {
                "fn": "Russell Erickson",
                "hasEmail": "mailto:erickson.russell@epa.gov"
            },
            "distribution": [
                {
                    "title": "MEDIonToxPaper2_Dataset.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395341/MEDIonToxPaper2_Dataset.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-09-28",
            "references": [
                "https://doi.org/10.1002/etc.3669"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1395341/documents/MEDIonToxPaper2_DataDictionary.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "qPCR data for calanoids in Lake Harsha",
            "description": "raw data for qPCR assays",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1396166",
            "keyword": [
                "qPCR",
                "rt-qpcr",
                "copepods"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [
                {
                    "title": "SantodomingoJorge_A-vdp4_database _20160918 qPCR for calanoids in Lake Harsha.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1396166/SantodomingoJorge_A-vdp4_database%20_20160918%20qPCR%20for%20calanoids%20in%20Lake%20Harsha.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-01",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data contributed by EPA/ORD/NERL/CED researchers to the manuscript \"Advanced Error Diagnostics of the CMAQ and CHIMERE modeling systems within the AQMEII3 Model Evaluation Framework\" ",
            "description": "This dataset contains the data contributed by EPA/ORD/NERL/CED researchers to the manuscript \"Advanced Error Diagnostics of the CMAQ and CHIMERE modeling systems within the AQMEII3 Model Evaluation Framework\" led by Dr. Efisio Solazzo of the European Commission's Joint Research Center. \n\nThis dataset is associated with the following publication:\nSolazzo, E., C. Hogrefe, A. Colette, M. Garcia-Vivanco, and S. Galmarini. Advanced error diagnostics of the CMAQ and Chimere modelling systems within the AQMEII3 model evaluation framework.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 17: 10435-10465, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1390127",
            "keyword": [
                "air quality model evaluation",
                "spectral decomposition",
                "error apportionment",
                "ozone diurnal cycle",
                "error persistence"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "data_SolazzoEtAl_Sensitivities.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390127/data_SolazzoEtAl_Sensitivities.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-01-31",
            "references": [
                "https://doi.org/10.5194/acp-17-10435-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1390127/documents/HogrefeChristian_A-sbd0_DataDescription.zip",
            "describedByType": "application/zip",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Assessing background levels of specific conductivity using weight of evidence 508 compliant",
            "description": "Data contains sampling station locations with physical and chemical data.\nData: stations 508.xlsx (Ohio dataset), env.bio70 508.xlsx (WV biological station dataset). \n\nThis dataset is associated with the following publication:\nCormier, S., L. Zheng, G. Suter, and C. Flaherty. Assessing background levels of specific conductivity using weight of evidence.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 628-629: 1637-1649, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1402418",
            "keyword": [
                "Ohio",
                "West Virginia",
                "chemistry",
                "conductivity",
                "background",
                "regional",
                "water quality",
                "applicability",
                "stream",
                "weight of evidence"
            ],
            "contactPoint": {
                "fn": "Susan Cormier",
                "hasEmail": "mailto:cormier.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data for Background WoE 508.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1402418/Data%20for%20Background%20WoE%20508.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-10-24",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.02.017",
                "https://pasteur.epa.gov/uploads/10.23719/1402418/documents/DataDictionaryCond_DataFileColumnMetadata_20161221.xlsx"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Effects of Na and Ca on particle size; Effect of filtering on UV absorbance",
            "description": "Effects of Na and Ca on particle size; Effect of filtering on UV absorbance. \n\nThis dataset is associated with the following publication:\nBouchard, D., C. Knightes, X. Chang, and B. Avant. Simulating Multiwalled Carbon Nanotube Transport in Surface Water Systems Using the Water Quality Analysis Simulation Program (WASP).   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(19): 11174\u201311184, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1393469",
            "keyword": [
                "carbon nanotubes",
                "MWCNTs",
                "nanomaterials",
                "wasp8",
                "water quality modeling"
            ],
            "contactPoint": {
                "fn": "Dermont Bouchard",
                "hasEmail": "mailto:bouchard.dermont@epa.gov"
            },
            "distribution": [
                {
                    "title": "A-hhmz_filterUVeffects.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393469/A-hhmz_filterUVeffects.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "A-hhmz_NaCa.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393469/A-hhmz_NaCa.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-14",
            "references": [
                "https://doi.org/10.1021/acs.est.7b01477"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data Dictionary for \"Comparison of soil sampling and analytical methods for asbestos at the Sumas Mountain Asbestos Site\u2014Working towards a toolbox for better assessment\", Version 1 (8/28/2017); by D.A. Vallero (ORD-NERL) and J. Wroble (Region 10).",
            "description": "Definition of terms used in manuscript's technical descriptions, tables and figure. \n\nThis dataset is associated with the following publication:\nWroble, J., T. Frederick, A. Frame, and D. Vallero. Comparison of soil sampling and analytical methods for asbestos at the Sumas Mountain Asbestos Site\u2014Working towards a toolbox for better assessment.   PLoS ONE. Public Library of Science, San Francisco, CA, USA, 12(7): e0180210, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1376845",
            "keyword": [
                "activity based sampling (ABS)",
                "ASTM D 7521",
                "CARB 435",
                "decision unit",
                "EPA 200.2",
                "EPA 200.7",
                "FBAS/ISO 10312",
                "asbestos",
                "sediment",
                "naturally occurring asbestos",
                "transmission electronic microscopy (TEM)"
            ],
            "contactPoint": {
                "fn": "Daniel Vallero",
                "hasEmail": "mailto:vallero.daniel@epa.gov"
            },
            "distribution": [
                {
                    "title": "data dictionary_ValleroDaniel_A-02vb_SDMP_20170822.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376845/data%20dictionary_ValleroDaniel_A-02vb_SDMP_20170822.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-08-28",
            "references": [
                "https://doi.org/10.1371/journal.pone.0180210"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1376845/documents/data%20dictionary_ValleroDaniel_A-02vb_SDMP_20170822.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Air and Soil Data Files from Sumas Study",
            "description": "The data are summarized in the manuscript, but users may wish to apply them from these files. \n\nThis dataset is associated with the following publication:\nWroble, J., T. Frederick, A. Frame, and D. Vallero. Comparison of soil sampling and analytical methods for asbestos at the Sumas Mountain Asbestos Site\u2014Working towards a toolbox for better assessment.   PLoS ONE. Public Library of Science, San Francisco, CA, USA, 12(7): e0180210, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1404696",
            "keyword": [
                "naturally occurring asbestos",
                "contaminated soil",
                "asbestos in air",
                "sediment",
                "transmission electronic microscopy (TEM)",
                "asbestos"
            ],
            "contactPoint": {
                "fn": "Daniel Vallero",
                "hasEmail": "mailto:vallero.daniel@epa.gov"
            },
            "distribution": [
                {
                    "title": "AirDataSumas.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1404696/AirDataSumas.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "SoilMetalsDataSumas.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1404696/SoilMetalsDataSumas.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2017-10-18",
            "references": [
                "https://doi.org/10.1371/journal.pone.0180210"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Production, emissions and economic as well as historical marketing data for the pulp and paper industries in the United States",
            "description": "The pulp & paper sector database contains the entire population of integrated and non-integrated pulp and paper mills (approx. 663 mills) and their products in the U.S. Ion this database, all paper products in the modeling framework are grouped into eight major categories: 1) containerboard, 2) boxboard and other board, 3) packaging and industrial paper, 4) corrugating medium, 5) newsprint, 6) tissue, 7) coated printing and writing paper, and 8) uncoated printing and writing paper. The inputs data contain industry-specific data, market-specific data, and optimization parameters. Data outputs include optimized mitigation options and optimized economic parameters of products. The input data that are specific to the pulp and paper industry characterize the following aspects of individual facilities: unit-level production for each category of products, capacity, production cost (material, operations, and maintenance costs) (RISI 2011), capital cost, fuel types and cost, information about emissions sources (boilers, recovery furnaces, and lime kilns), mitigation technologies (emission controls), energy efficiency measures, and fuel emission intensities. The data related to mitigation technologies provide information regarding applicable air pollution control technologies, their costs, and their emission control characteristics. Similarly, data related to measures intended to increase energy efficiency provide information regarding applicable energy efficiency measures, their costs, and their characteristics. The market data consist of historical and projected nationwide commodity consumption, discount rates, cost of electricity, escalation rates, economic life of technologies, and import and export quantities and prices. \n\nThis dataset is associated with the following publication:\nBhander , G., and W. Jozewicz. Universal industrial sectors integrated solutions module\r\nfor the pulp and paper industry.   Nordic Pulp & Paper Research Journal. Mid Sweden University, Sundsvall,  SWEDEN, 32(3): 375-385, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1390779",
            "keyword": [
                "historical & projected data",
                "mitigation technologies",
                "market-specific data",
                "industry-specific data",
                "pulp and paper sector",
                "emissions analysis",
                "modeling",
                "economic analysis",
                "mitigation options and cost",
                "environmental analysis",
                "multi-pollutant assessment"
            ],
            "contactPoint": {
                "fn": "Gurbakhash Bhander",
                "hasEmail": "mailto:bhander.gurbakhash@epa.gov"
            },
            "distribution": [
                {
                    "title": "UISIS-PNP Model Dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390779/UISIS-PNP%20Model%20Dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "UISIS-PNP Model Outputs Example.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390779/UISIS-PNP%20Model%20Outputs%20Example.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-05-22",
            "references": [
                "https://doi.org/10.3183/npprj-2017-32-03-p375-385"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Effects of energy system changes on CO2 projections for the United States_data tables with data dictionary",
            "description": "Dataset that corresponds to paper titled Effects of recent energy system changes on CO2 projections for the United States. \n\nThis dataset is associated with the following publication:\nLenox, C., and D. Loughlin. Effects of recent energy system changes on CO2 projections for the United States.   CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY. Springer-Verlag, New York, NY, USA, 19(9): 2277-2290, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1394400",
            "keyword": [
                "energy",
                "systems analyses",
                "modeling",
                "Greenhouse gas",
                "air quality",
                "MARKAL"
            ],
            "contactPoint": {
                "fn": "Carol Lenox",
                "hasEmail": "mailto:lenox.carol@epa.gov"
            },
            "distribution": [
                {
                    "title": "LenoxLoughlin_paper_Effects of energy system changes_data tables with data dictionary_FINAL.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394400/LenoxLoughlin_paper_Effects%20of%20energy%20system%20changes_data%20tables%20with%20data%20dictionary_FINAL.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-08",
            "references": [
                "https://doi.org/10.1007/s10098-017-1417-y"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Near-Port Air Quality Assessment Utilizing a Mobile Monitoring Approach",
            "description": "Near-Port Air Quality Assessment Utilizing a Mobile Monitoring Approach. \n\nThis dataset is associated with the following publication:\nSteffens, J., S. Kimbrough, R. Baldauf, V. Isakov, R. Brown, A. Powell, and P. Deshmukh. Near-Port Air Quality Assessment Utilizing a Mobile Monitoring Approach.   Atmospheric Pollution Research. Turkish National Committee for Air Pollution Research and Control, Izmir,  TURKEY, 8(6): 1023-1030, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1390082",
            "keyword": [
                "mobile monitoring",
                "air quality",
                "ports",
                "near source"
            ],
            "contactPoint": {
                "fn": "Evelyn Kimbrough",
                "hasEmail": "mailto:kimbrough.sue@epa.gov"
            },
            "distribution": [
                {
                    "title": "KimbroughEvelyn_A-5qg0_Dataset_20160624.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390082/KimbroughEvelyn_A-5qg0_Dataset_20160624.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-29",
            "references": [
                "https://doi.org/10.1016/j.apr.2017.04.003"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Barrierless Reactions with Loose Transition States Govern the Yields and Lifetimes of Organic Nitrates Derived from Isoprene",
            "description": "The attached extensive computational chemistry dataset was succinctly presented by Piletic et al. (Journal of Physical Chemistry A, 2017, DOI: 10.1021/acs.jpca.7b08229) and involves detailed electronic structure (density functional theory - DFT) and kinetic calculation (master equation formalism) outputs for the reactions of isoprene peroxy radical isomers with NOx.  The first three tabs describe the potential energy surfaces (PESs) of the beta and delta hydroxy-peroxy isoprene isomers reacting with NO to produce NO2, HONO and organic nitrates.  Microcanonical rate constants and organic nitrate yield data are presented in the fourth and fifth tabs.  The PESs for the reactions of the E and Z delta hydroxy-peroxy isoprene isomers is given in the sixth tab while the seventh tab shows the PES data for the reaction of the hydroxyl radical with several organic nitrates. \n\nThis dataset is associated with the following publication:\nPiletic, I., E. Edney, and L. Bartolotti. Barrierless Reactions with Loose Transition States Govern the Yields and Lifetimes of Organic Nitrates Derived from Isoprene.   JOURNAL OF PHYSICAL CHEMISTRY A. American Chemical Society, Washington, DC, USA, 121(43): 8306-8321, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1400392",
            "keyword": [
                "isoprene",
                "organic nitrate",
                "HONO",
                "Chemical mechanisms",
                "air quality",
                "NOx",
                "pm2.5",
                "ozone concentrations",
                "CMAQ",
                "computational chemistry",
                "atmospheric chemistry"
            ],
            "contactPoint": {
                "fn": "Ivan Piletic",
                "hasEmail": "mailto:piletic.ivan@epa.gov"
            },
            "distribution": [
                {
                    "title": "IsopreneOrganicNitrateManuscript_JPCA_2017_ScienceHub_Dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1400392/IsopreneOrganicNitrateManuscript_JPCA_2017_ScienceHub_Dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-16",
            "references": [
                "https://doi.org/10.1021/acs.jpca.7b08229"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1400392/documents/COMPCHEMDataDictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Macrophyte Community Response to Nitrogen Loading and Thermal Stressors in Rapidly Flushed Mesocosm Systems",
            "description": "Data represent response variables from a series of mesocosm experiments to assess how estuarine macrophyte communities respond to nitrogen loading under two different thermal regimes. \n\nThis dataset is associated with the following publication:\nKaldy, J., C. Brown, W. Nelson, and M. Frazier. Macrophyte Community Response to Nitrogen Loading and Thermal Stressors in Rapidly Flushed Mesocosm Systems.   JOURNAL OF EXPERIMENTAL MARINE BIOLOGY AND ECOLOGY. Elsevier Science Ltd, New York, NY, USA, 497: 107-119, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1399579",
            "keyword": [
                "eutrophication",
                "seagrass",
                "macroalgae",
                "nutrients",
                "temperature",
                "Zostera marina",
                "Zostera japonica",
                "nutrient pollution index",
                "wasting disease"
            ],
            "contactPoint": {
                "fn": "James Kaldy",
                "hasEmail": "mailto:kaldy.jim@epa.gov"
            },
            "distribution": [
                {
                    "title": "Kaldy et al_Macrophyte Response_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1399579/Kaldy%20et%20al_Macrophyte%20Response_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-01",
            "references": [
                "https://doi.org/10.1016/j.jembe.2017.09.022"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Digitized Onondaga Lake Dissolved Oxygen Concentrations and Model Simulated Values using Bayesian Monte Carlo Methods   ",
            "description": "The dataset is lake dissolved oxygen concentrations obtained form plots published by Gelda et al. (1996) and lake reaeration model simulated values using Bayesian Monte Carlo methods (Chaudhary and Hantush, 2017). The data also includes measured (Gelda et al., 1996 and references therein) versus estimated liquid film transfer coefficient values (KL) by Chaudhary and Hantush (2017). \n\nThis dataset is associated with the following publication:\nChaudhary, A., and M. Hantush. Bayesian Monte Carlo and Maximum Likelihood Approach for Uncertainty Estimation and Risk Management:  Application to Lake Oxygen Recovery Model.  Mark van Loosdrecht  WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 108: 301-311, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1405325",
            "keyword": [
                "Liquid film transfer coefficient",
                "Observed dissolved oxygen concentration",
                "Simulated dissolved oxygen concentration",
                "95% Confidence interval",
                "Bayesian statistics",
                "Monte Carlo method",
                "model calibration",
                "Uncertainty Estimation",
                "Markov Chain Monte Carlo",
                "Water Quality Management",
                "TMDL",
                "Margin of safety"
            ],
            "contactPoint": {
                "fn": "Mohamed Hantush",
                "hasEmail": "mailto:hantush.mohamed@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHub_Lake reaeration paper_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1405325/ScienceHub_Lake%20reaeration%20paper_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-29",
            "references": [
                "https://doi.org/10.1016/j.watres.2016.11.012"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Association rule mining data for census tract chemical exposure analysis",
            "description": "Chemical concentration, exposure, and health risk data for U.S. census tracts from National Scale Air Toxics Assessment (NATA). \n\nThis dataset is associated with the following publication:\nHuang, H., R. Tornero-Velez, and T. Barzyk. Associations between socio-demographic characteristics and chemical concentrations contributing to cumulative exposures in the United States.   Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London,  UK, 27(6): 544-550, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390151",
            "keyword": [
                "multiple stressors",
                "Rule Mining",
                "Cumulative Risks",
                "Combined Effects",
                "Environmental Justice"
            ],
            "contactPoint": {
                "fn": "Timothy Barzyk",
                "hasEmail": "mailto:barzyk.timothy@epa.gov"
            },
            "distribution": [
                {
                    "title": "ARM Dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390151/ARM%20Dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-07-20",
            "references": [
                "https://doi.org/10.1038/jes.2017.15"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1390151/documents/Data%20dictionary%20for%20ARM%20dataset.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CMAQ predicted concentration files",
            "description": "model predicted concentrations. \n\nThis dataset is associated with the following publication:\nMu\u00f1iz-Unamunzaga, M., R. Borge, G. Sarwar, B. Gantt, D. de la Paz, C. Cuevas, and A. Saiz-Lopez. The influence of ocean halogen and sulfur emissions in the air quality of a coastal megacity: The case of Los Angeles.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 610(611): 1536-1545, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1390152",
            "keyword": [
                "air quality",
                "Marine natural emissions",
                "halogens",
                "DMS",
                "CMAQ",
                "Los Angeles",
                "urban air quality"
            ],
            "contactPoint": {
                "fn": "Golam Sarwar",
                "hasEmail": "mailto:sarwar.golam@epa.gov"
            },
            "distribution": [
                {
                    "title": "COMBINE_CONC_SELECT_A_AVG.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390152/COMBINE_CONC_SELECT_A_AVG.tar",
                    "mediaType": "application/x-tar"
                },
                {
                    "title": "COMBINE_CONC_SELECT_B_AVG.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390152/COMBINE_CONC_SELECT_B_AVG.tar",
                    "mediaType": "application/x-tar"
                }
            ],
            "modified": "2016-10-07",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2017.06.098"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1390152/documents/SrawarGolaml_A-q57q_Data_Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for MSM example application for MSM manuscript",
            "description": "Input data used by the MSM and HSPF for QMRA application to the Manitowoc Basin. \n\nThis dataset is associated with the following publication:\nWhelan, G., K. Kim, R. Parmar, G. Laniak, K. Wolfe, M. Galvin, M. Molina, Y. Pachepsky, P. Duda, R. Zepp, L. Prieto, J. Kinzelman, G.T. Kleinheinz, and M. Bouchard. Capturing microbial sources distributed in a mixed-use watershed within an integrated environmental modeling workflow.   ENVIRONMENTAL MODELLING AND SOFTWARE. Elsevier Science Ltd, New York, NY, USA, 99: 126-146, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1376851",
            "keyword": [
                "Integrated environmental modeling",
                "QMRA",
                "Risk Assessment",
                "pathogens",
                "manure",
                "watershed modeling"
            ],
            "contactPoint": {
                "fn": "Gene Whelan",
                "hasEmail": "mailto:whelan.gene@epa.gov"
            },
            "distribution": [
                {
                    "title": "Calibration Files_061617.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376851/Calibration%20Files_061617.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "RDB_files_062017.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376851/RDB_files_062017.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-06-13",
            "references": [
                "https://doi.org/10.1016/j.envsoft.2017.08.002"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1376851/documents/Whelan%20QMRA%20Primer_Rev6.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Evaluation of air pollutant emissions projections from the GCAM-USA integrated assessment model",
            "description": "This dataset contains 2010 emissions of nitrogen oxides, sulfur dioxide, and fine particulate matter by sector and state as modeled using the GCAM-USA integrated assessment model, in comparison to the 2011 National Emissions Inventory (NEI).  In addition, the dataset includes 2025 projections from both GCAM-USA and the NEI.\r\nThe dataset includes data underlying the figures and tables in the following journal article:\r\nWenjing Shi et al. (2017), Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA.  Applied Energy, in review. \n\nThis dataset is associated with the following publication:\nShi, W., Y. Ou, S. Smith, C. Ledna, C. Nolte, and D. Loughlin. Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA..   Applied Energy. Elsevier B.V., Amsterdam,  NETHERLANDS, 208: 511-521, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1377869",
            "keyword": [
                "emissions",
                "air quality",
                "GCAM-USA",
                "integrated assessment modeling"
            ],
            "contactPoint": {
                "fn": "Christopher Nolte",
                "hasEmail": "mailto:nolte.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Shi et al. dataset.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377869/Shi%20et%20al.%20dataset.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-08-31",
            "references": [
                "https://doi.org/10.1016/j.apenergy.2017.09.122"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales",
            "description": "Hemispheric scale simulations with CMAQ and the Weather Research and Forecasting model are performed for multiple years. Model capabilities for a range of applications including episodic long-range pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution-climate interactions are evaluated through detailed comparison with available surface, aloft, and remotely sensed observations. \n\nThis dataset is associated with the following publication:\nMathur, R., J. Xing, R. Gilliam, G. Sarwar, C. Hogrefe, J. Pleim, G. Pouliot, S. Roselle, T. Spero, D. Wong, and J. Young. Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 17: 12449-12474, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1378084",
            "keyword": [
                "Hemispheric CMAQ",
                "background pollution",
                "long-range transport",
                "WRF"
            ],
            "contactPoint": {
                "fn": "Rohit Mathur",
                "hasEmail": "mailto:mathur.rohit@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure1_tracer_netcdf.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378084/Figure1_tracer_netcdf.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Figure8_LAY1_CONC_netcdf.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378084/Figure8_LAY1_CONC_netcdf.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Figure2_FullLayerHt_ZF_35_44L.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378084/Figure2_FullLayerHt_ZF_35_44L.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "Figure3a_35_44L_zero_NA_TrinidadHead.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378084/Figure3a_35_44L_zero_NA_TrinidadHead.txt",
                    "mediaType": "text/plain"
                },
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                    "title": "Figure3b_35_44L_zero_NA_Boulder.txt",
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                {
                    "title": "Figure9a_Bias_Diff_SE_states_jul29-aug3.xlsx",
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                },
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                {
                    "title": "Figure16b_Europe_AOD_SWR_JJAmonthly.txt",
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                },
                {
                    "title": "Figure16c_EUS_AOD_SWR_JJAmonthly.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378084/Figure16c_EUS_AOD_SWR_JJAmonthly.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "Data_Dictionary_HemisphericCMAQ_manuscript.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378084/Data_Dictionary_HemisphericCMAQ_manuscript.docx",
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                {
                    "title": "Data_Dictionary_HemisphericCMAQ_manuscript_Final.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378084/Data_Dictionary_HemisphericCMAQ_manuscript_Final.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-01-20",
            "references": [
                "https://doi.org/10.5194/acp-17-12449-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1378084/documents/Data_Dictionary_HemisphericCMAQ_manuscript.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cockle Field Caging Experiment Data (2014)",
            "description": "To determine whether differences in cockle density or qualitative burial depth observed during the 2014 field survey were affected by green macroalgal (GMA) mats, we conducted a field caging experiment whereby cockles were subjected to the presence or absence of simulated GMA mats for 12 weeks (July-September 2014).  This dataset contains all data collected during that field experiment. \n\nThis dataset is associated with the following publication:\nLewis, N., and T. DeWitt. Effect of Green Macroalgal Blooms on the Behavior, Growth, and Survival of Cockles (Clinocardium nuttallii) in Pacific NW Estuaries.   MARINE ECOLOGY PROGRESS SERIES. Inter-Research, Luhe,  GERMANY, 582: 105-120, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390140",
            "keyword": [
                "green macroalgae",
                "ulva spp.",
                "ecosystem services",
                "behavior",
                "burial",
                "eutrophication",
                "nutrient enrichment",
                "cockle",
                "gull",
                "Oregon"
            ],
            "contactPoint": {
                "fn": "Theodore Dewitt",
                "hasEmail": "mailto:dewitt.ted@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cockle_FieldExptData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390140/Cockle_FieldExptData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-24",
            "references": [
                "https://doi.org/10.3354/meps12328"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cockle/Green Macroalgae Field Survey Data (2014)",
            "description": "To quantify any spatial or temporal variability in cockle densities with respect to in situ GMA biomass in Yaquina Bay, OR, we conducted field surveys during consecutive daytime low tides (<0.46 m MLLW) in both June and August 2014, which provided a comparison between early and late summer.  This dataset contains all data collected during those field surveys. \n\nThis dataset is associated with the following publication:\nLewis, N., and T. DeWitt. Effect of Green Macroalgal Blooms on the Behavior, Growth, and Survival of Cockles (Clinocardium nuttallii) in Pacific NW Estuaries.   MARINE ECOLOGY PROGRESS SERIES. Inter-Research, Luhe,  GERMANY, 582: 105-120, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390154",
            "keyword": [
                "green macroalgae",
                "ulva spp.",
                "ecosystem services",
                "behavior",
                "burial",
                "eutrophication",
                "nutrient enrichment",
                "cockle",
                "gull",
                "Oregon"
            ],
            "contactPoint": {
                "fn": "Theodore Dewitt",
                "hasEmail": "mailto:dewitt.ted@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cockle_FieldSurveyData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390154/Cockle_FieldSurveyData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-27",
            "references": [
                "https://doi.org/10.3354/meps12328"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cockle Temperature Exposure Lab Experiment (2016)",
            "description": "We carried out a lab experiment in which we exposed cockles to a range of air temperatures to simulate the physiological rigors of exposure to sunlight and air at the sediment surface during daytime low tides.  Cockles were subjected to twelve different temperature (6, 14, 21, 30, 34, 38 \u00b1 1.0 \u00b0C) x time (2, 4 hrs) treatments within temperature-controlled chambers, representing the temperature and exposure durations regularly observed on Yaquina Bay mid-intertidal flats during daytime low tides in the summer.  This dataset contains all data collected during that lab experiment. \n\nThis dataset is associated with the following publication:\nLewis, N., and T. DeWitt. Effect of Green Macroalgal Blooms on the Behavior, Growth, and Survival of Cockles (Clinocardium nuttallii) in Pacific NW Estuaries.   MARINE ECOLOGY PROGRESS SERIES. Inter-Research, Luhe,  GERMANY, 582: 105-120, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390155",
            "keyword": [
                "green macroalgae",
                "ulva spp.",
                "ecosystem services",
                "behavior",
                "burial",
                "eutrophication",
                "nutrient enrichment",
                "cockle",
                "gull",
                "Oregon"
            ],
            "contactPoint": {
                "fn": "Theodore Dewitt",
                "hasEmail": "mailto:dewitt.ted@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cockle_LabTemp_ExptData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390155/Cockle_LabTemp_ExptData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-27",
            "references": [
                "https://doi.org/10.3354/meps12328"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Gull Foraging Field Survey Data (2015)",
            "description": "We conducted a predation study to determine whether emergence from the sediment affected cockle survival or physiological condition.  We performed a field survey of the gull population from May-August 2015 in the same low-mid intertidal range of Idaho Flat that other field experiments were conducted.  Surveyed gulls were observed in order to determine diet composition.  This dataset contains all data collected during that field survey. \n\nThis dataset is associated with the following publication:\nLewis, N., and T. DeWitt. Effect of Green Macroalgal Blooms on the Behavior, Growth, and Survival of Cockles (Clinocardium nuttallii) in Pacific NW Estuaries.   MARINE ECOLOGY PROGRESS SERIES. Inter-Research, Luhe,  GERMANY, 582: 105-120, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390156",
            "keyword": [
                "green macroalgae",
                "ulva spp.",
                "ecosystem services",
                "behavior",
                "burial",
                "eutrophication",
                "nutrient enrichment",
                "cockle",
                "gull",
                "Oregon"
            ],
            "contactPoint": {
                "fn": "Theodore Dewitt",
                "hasEmail": "mailto:dewitt.ted@epa.gov"
            },
            "distribution": [
                {
                    "title": "Gull_FieldSurveyData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390156/Gull_FieldSurveyData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-27",
            "references": [
                "https://doi.org/10.3354/meps12328"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cockle Emergence Lab Experiment (2017)",
            "description": "To identify the factors of green macroalgae (GMA) accumulation that cause cockles to rapidly emerge from the sediment, we conducted a series of laboratory experiments to isolate the effects of anoxia, surficial pressure/barrier, GMA presence, and the interaction of GMA presence and a surficial pressure/barrier on the emergence behavior of buried cockles.  We quantified the emergence response of cockles in each of these five treatments with six replicates (emergent proportion of cockles tank-1) per treatment (n = 30 tanks).  After the start of each trial, subjects were examined at 0.5, 1, 2, 4, 6, and 8 hrs for changes in burial depth; those that were partially or completely exposed at the sediment surface were considered to have exhibited an emergence response. \n\nThis dataset is associated with the following publication:\nLewis, N., and T. DeWitt. Effect of Green Macroalgal Blooms on the Behavior, Growth, and Survival of Cockles (Clinocardium nuttallii) in Pacific NW Estuaries.   MARINE ECOLOGY PROGRESS SERIES. Inter-Research, Luhe,  GERMANY, 582: 105-120, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390157",
            "keyword": [
                "green macroalgae",
                "ulva spp.",
                "ecosystem services",
                "behavior",
                "burial",
                "eutrophication",
                "nutrient enrichment",
                "cockle",
                "gull",
                "Oregon"
            ],
            "contactPoint": {
                "fn": "Theodore Dewitt",
                "hasEmail": "mailto:dewitt.ted@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cockle_LabExptData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390157/Cockle_LabExptData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-05-15",
            "references": [
                "https://doi.org/10.3354/meps12328"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Doc Title:  Adult Hippocampal Neurogenesis is Impaired by Transient Developmental Thyroid Hormone Disruption",
            "description": "Severe thyroid hormone (TH) deprivation during development impairs neurogenesis throughout the brain. The hippocampus also maintains a capacity for neurogenesis throughout life which is reduced in adult-onset hypothyroidism. This study examined hippocampal volume in the neonate and adult hippocampal neurogenesis after developmental and adult-onset TH insufficiency. Pregnant rat dams were administered 0, 3, or 10 ppm of propylthiouracil (PTU) via drinking water from gestational day (GD) 6 until weaning. PTU at the high dose reduced body, brain, hippocampal weights on postnatal day (PN) 14, 21 and 78. Sub-regional analysis revealed decrements in hippocampal volumes at 10 but not 3 ppm PTU on PN23. In Experiment 2, one pair of adult male offspring of 0 and 3ppm-teated dams was placed on 3 ppm PTU from PN60, while a 2nd pair remained on control water. Adult neurogenesis was assessed by bromodeoxyuridine (BrdU, 50mg/kg, ip, 2X daily, X5 days) starting on PN90. Brains from animals perfused 1 and 28 days later were processed for immunohistochemistry. Although no volume changes were seen in neonates at 3ppm, thinning of the granule cell layer emerged in adulthood. Developmental TH insufficiency reduced BrdU+ve cells at 1-day with no further reduction at 28-days post-BrdU, indicative of a selective effect on cell proliferation. This was supported by fewer cells staining for the proliferative marker, Ki67. Adult only PTU did not impair neurogenesis or exacerbate effects seen with developmental exposure. A reduced capacity for neurogenesis may contribute to cognitive deficits evident in adults following moderate degrees of developmental TH insufficiency. \n\nThis dataset is associated with the following publication:\nGilbert, M., J. Goodman, J. Gomez, A. Johnstone, and R. Ramos. Adult Hippocampal Neurogenesis is Impaired by Transient and Moderate Developmental Thyroid Hormone Disruption.   TOXICOLOGICAL SCIENCES. Society of Toxicology,     9-21, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1390086",
            "keyword": [
                "hippocampus",
                "neurogenesis",
                "developmental neurotoxicity",
                "thyroid hormone insufficiency",
                "chemical safety for sustainablity",
                "thyroid",
                "brain"
            ],
            "contactPoint": {
                "fn": "Mary Gilbert",
                "hasEmail": "mailto:gilbert.mary@epa.gov"
            },
            "distribution": [
                {
                    "title": "Sceince Hub Data Summaries.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390086/Sceince%20Hub%20Data%20Summaries.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-06",
            "references": [
                "https://doi.org/10.1016/j.neuro.2016.12.009"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "ACTIVE VERSUS SEDENTARY LIFESTYLE FROM WEANING TO ADULTHOOD AND SUSCEPTIBILITY TO OZONE IN RATS",
            "description": "The prevalence of a sedentary (SED) life style combined with calorically rich diets has spurred the rise in childhood obesity which, in turn, translates to adverse health effects in adulthood. Obesity and lack of active (ACT) lifestyle may increase susceptibility to air pollutants. We housed 22 day-old female Long-Evans rats in a cage without (SED) or with a running wheel (ACT). After 10 weeks the rats ran 310 \u00b1 16.3 km (SEM).  Responses of SED and ACT rats to whole-body O3 (0, 0.25, 0.5, or 1.0 ppm; 5 hr/day for 2 days) was assessed. Glucose tolerance (GTT) was performed following the first day of O3. ACT rats had less body fat and an improved glucose tolerance (GTT).  Ventilatory function (plethysmography) of SED and ACT groups was similarly impaired by O3. Bronchoalveolar lavage fluid (BALF) was collected after the second O3 exposure. SED and ACT rats were hyperglycemic following 1.0 ppm O3.  GTT was impaired by O3 in both groups; however, ACT rats exhibited improved recovery to 0.25 and 1.0 ppm O3. BALF cell neutrophils and total cells were similarly increased in ACT and SED groups exposed to 1.0 ppm O3. O3-induced increase in eosinophils was exacerbated in SED rats. Chronic exercise from post-weaning to adulthood improved some of the metabolic and pulmonary responses to O3 (GTT and eosinophils) but several other parameters were unaffected. The reduction in O3-induced rise in BALF eosinophils in ACT rats suggests a possible link between a SED lifestyle and incidence of asthma-related symptoms from O3. \u2003. \n\nThis dataset is associated with the following publication:\nGordon, C., P. Phillips, A. Ledbetter, S. Snow, M. Schladweiler, A. Johnstone, and U. Kodavanti. ACTIVE VS. SEDENTARY LIFESTYLE FROM WEANING TO ADULTHOOD AND SUSCEPTIBILITY TO OZONE IN RATS.   INHALATION TOXICOLOGY. Informa Healthcare USA, New York, NY, USA,  L100-L109, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390099",
            "keyword": [
                "Exercise",
                "obesity",
                "Ozone",
                "Childhood",
                "Children's Environmental Health"
            ],
            "contactPoint": {
                "fn": "Christopher Gordon",
                "hasEmail": "mailto:gordon.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "GordonChristopher - E329 Data for MS.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390099/GordonChristopher%20-%20E329%20Data%20for%20MS.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-10-25",
            "references": [
                "https://doi.org/10.1152/ajplung.00415.2016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A DEVICE THAT ALLOWS RODENTS TO BEHAVIORALLY THERMOREGULATE WHEN HOUSED IN VIVARIUMS  - DATA",
            "description": "Laboratories and vivariums are maintained at ambient temperatures (Ta) of 20-24 \u2070C and it is widely accepted that mice maintained under these conditions are cold stressed. When mice are inactive and sleeping in the daytime, their zone of thermoneutrality associated with a basal metabolic rate is 30-32 \u2070C. If given a choice, mice will use thermoregulatory behavior to seek out thermoneutral temperatures during the daytime. The cold stress of a vivarium can be problematic to researchers requiring an animal model that is not stressed metabolically. However, it may not be practical or economically feasible to maintain an animal vivarium at thermoneutral temperatures. One problem with raising the Ta of a vivarium is that personnel wearing protective equipment will be subject to considerable heat stress. In this paper, we present plans for the construction and operation of a device that allows mice to utilize a refuge with a heated floor maintained at an approximate thermoneutral temperatures (30-32 \u2070C). The device is made of inexpensive, readily available materials and utilizes a disposable hand warmer (HotHands\u00ae) as a heat source. One hand warmer provides a thermoneutral environment for approximately 12 hours. This device is easily adapted to a standard mouse or rat cage and requires brief maintenance each day to change the heating pad.  With this device in a standard cage, mice can select an environment associated with thermoneutral conditions during the daytime when inactive and sleeping. At night, the mice are more active, have a higher metabolic rate, and prefer cooler Ta\u2019s. Egress from the warmed plate allows mice to seek cooler Ta\u2019s at night. \n\nThis dataset is associated with the following publication:\nGordon, C., E. Puckett, E. Repasky, and A. Johnstone. A DEVICE THAT ALLOWS RODENTS TO BEHAVIORALLY THERMOREGULATE WHEN HOUSED IN VIVARIUMS.   COMPARATIVE MEDICINE. American Association for Laboratory Animal Science, Memphis, TN, USA,  173-176, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1390102",
            "keyword": [
                "cold-stress",
                "mouse",
                "behavioral thermoregulation",
                "thermoneutral"
            ],
            "contactPoint": {
                "fn": "Christopher Gordon",
                "hasEmail": "mailto:gordon.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "GordonChristopher_Thermal Floor_ACE_121_As-sf86_Data Set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390102/GordonChristopher_Thermal%20Floor_ACE_121_As-sf86_Data%20Set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-11-08",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Impaired swim bladder inflation in early-life stage fathead minnows exposed to a deiodinase inhibitor, iopanoic acid",
            "description": "The present study investigated whether inhibition of deiodinase, the enzyme which converts thyroxine (T4) to the more biologically-active form, 3,5,3'-triiodothyronine (T3), would impact inflation of the posterior and/or anterior chamber of the swim bladder, processes previously demonstrated to be thyroid-hormone regulated.  Two experiments were conducted using a model deiodinase inhibitor, iopanoic acid (IOP). In the first study, fathead minnow (Pimephales promelas) embryos were exposed to 0.6, 1.9, or 6.0 mg IOP/L or control water in a flow-through system until reaching 6 days post-fertilization (dpf) at which time posterior swim bladder inflation was assessed.  To examine effects on anterior swim bladder inflation, a second study was conducted with 6 dpf larvae exposed to the same IOP concentrations until reaching 21 dpf.  Fish from both studies were sampled for T4/T3 measurements, gene transcription analyses, and thyroid histopathology.  In the embryo study, incidence and length of inflated posterior swim bladders were significantly reduced in the 6.0 mg/L treatment at 6 dpf.  Incidence of inflation and length of anterior swim bladder in larval fish were significantly reduced in all IOP treatments at 14 dpf, but inflation recovered by 18 dpf.  Throughout the larval study, whole body T4 concentrations were significantly increased and T3 concentrations were significantly decreased in all IOP treatments.  Consistent with hypothesized compensatory responses, significant up-regulation of deiodinase-2 mRNA was observed in the larval study, and down-regulation of thyroperoxidase mRNA was observed in all IOP treatments in both studies.  Taken together, these results support the hypothesized adverse outcome pathways linking inhibition of deiodinase activity to impaired swim bladder inflation. \n\nThis dataset is associated with the following publication:\nCavallin, J., G. Ankley, B. Blackwell, C. Blanksma, K. Fay, K. Jensen, M. Kahl, D. Knapen, P. Kosian, S. Poole, E. Randolph, A. Schroeder, L. Vergauwen, and D. Villeneuve. Impaired swim bladder inflation in early-life stage fathead minnows exposed to a deiodinase inhibitor, iopanoic acid (article).   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 36(11): 2942-2952, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1390115",
            "keyword": [
                "thyroid",
                "fish early lifestage",
                "adverse outcome pathway",
                "ecotoxicology",
                "endocrine disruption",
                "screening and prioritization",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cavallin et al. IOP.Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390115/Cavallin%20et%20al.%20IOP.Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-02-08",
            "references": [
                "https://doi.org/10.1002/etc.3855"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Quantitative Adverse Outcome Pathway for Neurodevelopmental Effects of Thyroid Peroxidase-Induced Thyroid Hormone Synthesis Inhibition",
            "description": "Adequate levels of thyroid hormones (TH) are needed for proper brain development, deficiencies may lead to adverse neurological outcomes in humans and animal models. Environmental chemicals have been linked to TH disruption, yet the relationship between developmental exposures and decline in serum TH resulting in neurodevelopmental impairment is poorly understood. The present study developed a quantitative adverse outcome pathway (qAOP) where serum thyroxin (T4) reduction following inhibition of thyroperoxidase in the thyroid gland are described and related to deficits in fetal brain TH and the development of a brain malformation, subcortical band heterotopia. Pregnant dams were exposed to 6-propylthiouracil (PTU  0, 0.1, 0.5, 1, 2, or 3 ppm) from gestational day 6-20, increasing PTU concentrations in maternal thyroid gland and serum as well as in fetal serum. Dams exposed to 0.5 ppm PTU and higher exhibited dose-dependent decreases in thyroidal T4. Serum T4 levels in the dam were significantly decreased with exposure to 2 and 3 ppm PTU. In the fetus, T4 decrements were first observed at a lower dose of 0.5 ppm PTU. Based on these data, fetal brain T4 levels were estimated from published literature sources, and quantitatively linked to increases in the size of the heterotopia present in the brains of offspring. These data show the potential of in vivo assessments and computational descriptions of biological responses to predict the development of this structural brain malformation and use of qAOP approach to evaluate brain deficits that may result from exposure to other TH disruptors. \n\nThis dataset is associated with the following publication:\nHassan, I., H. El-Masri, P. Kosian, J. Ford, S. Degitz, and M. Gilbert. Neurodevelopment and Thyroid Hormone Synthesis Inhibition in the Rat: Quantitative Understanding Within the Adverse Outcome Pathway Framework.   TOXICOLOGICAL SCIENCES. Society of Toxicology,     57-73, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390120",
            "keyword": [
                "developmental hypothyroidism",
                "Thyroperoxidase",
                "AOPs",
                "brain development",
                "thyroid hormone"
            ],
            "contactPoint": {
                "fn": "Mary Gilbert",
                "hasEmail": "mailto:gilbert.mary@epa.gov"
            },
            "distribution": [
                {
                    "title": "GilbertMary_qAOP_A-zcs9_data set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390120/GilbertMary_qAOP_A-zcs9_data%20set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-23",
            "references": [
                "https://doi.org/10.1093/toxsci/kfx163"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Occurrence and in vitro bioactivity of estrogen, androgen, and glucocorticoid compounds in a nationwide screen of United States stream waters",
            "description": "In vitro bioactivity concentrations and chemical concentrations of estrogens, androgens, and glucocorticoids from a nationwide screen of United States stream water samples.  In vitro bioassays include T47D-Kbluc, MDA-kb2, and a CV-1 cell line transduced with human glucocorticoid receptor. \n\nThis dataset is associated with the following publication:\nConley, J., N. Evans, M. Cardon, L. Rosenblum, L. Iwanowicz, P. Hartig, K. Schenck, P. Bradley, and V. Wilson. Occurrence and in vitro bioactivity of estrogen, androgen, and glucocorticoid compounds in a nationwide screen of United States stream waters.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA,  4781-4791, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1390128",
            "keyword": [
                "estrogen",
                "androgen",
                "glucocorticoid",
                "effect based analysis",
                "in vitro biomonitoring",
                "surface water",
                "bioassay",
                "water quality",
                "multiple stressors",
                "in vitro screening",
                "endocrine disruption"
            ],
            "contactPoint": {
                "fn": "Justin Conley",
                "hasEmail": "mailto:conley.justin@epa.gov"
            },
            "distribution": [
                {
                    "title": "ConleyJustin_A-qz6m_Dataset_20170309.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390128/ConleyJustin_A-qz6m_Dataset_20170309.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-03-09",
            "references": [
                "https://doi.org/10.1021/acs.est.6b06515"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1390128/documents/ConleyJustin_A-qz6m_Dataset_Dictionary_20170309.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for human cell spheroid model of embryonic tissue fusion in vitro.",
            "description": "Epithelial-mesenchymal interactions drive embryonic fusion events during development and upon perturbation can result in birth defects. Cleft palate and neural tube defects can result from genetic defects or environmental exposures during development, yet very little is known about the effect of chemical exposures on fusion defects in humans because of the lack of relevant and robust human in vitro assays of developmental fusion behavior. Given the etiology and prevalence of cleft palate and the relatively simple architecture and composition of the embryonic palate, we sought to develop a three-dimensional culture system that could be used to study fusion behavior in vitro using human cells. We engineered human Wharton\u2019s Jelly stromal cell (HWJSC) spheroids of defined size and established that 7 days of culture in osteogenesis differentiation medium was sufficient to promote an osteogenic phenotype consistent with embryonic palatal mesenchyme. HWJSC spheroids supported the attachment of human epidermal keratinocyte progenitor cells on the outer spheroid surface likely through deposition of collagens I and IV, fibronectin, and laminin, and co-cultured spheroids exhibited fusion behavior that was dependent on epidermal growth factor signaling and fibroblast growth factor signaling in agreement with palate fusion literature. The method described here may broadly apply to the generation of three-dimensional epithelial-mesenchymal co-cultures to study developmental fusion events in a format that is amenable to predictive toxicology applications. \n\nThis dataset is associated with the following publication:\nBelair, D., C. Wolf, C. Wood, H. Ren, R. Grindstaff, W. Padgett, A. Swank, D. MacMillan, A. Fisher, W. Winnik, and B. Abbott. Engineering human cell spheroids to model embryonic tissue fusion in vitro..   PLoS ONE. Public Library of Science, San Francisco, CA, USA,  N/A, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1378475",
            "keyword": [
                "2D-DIGE",
                "alkaline phosphatase",
                "qRT-PCR",
                "RNASeq",
                "confocal microscopy",
                "Morphogenetic fusion",
                "palate fusion",
                "stromal cells",
                "epithelial cells",
                "cell spheroids",
                "osteogenesis"
            ],
            "contactPoint": {
                "fn": "Barbara Abbott",
                "hasEmail": "mailto:abbott.barbara@epa.gov"
            },
            "distribution": [
                {
                    "title": "04202017 Main Text & Suppl Figures Data (3).xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378475/04202017%20Main%20Text%20%26%20Suppl%20Figures%20Data%20%283%29.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-06",
            "references": [
                "https://doi.org/10.1371/journal.pone.0184155"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Oregon Tidal Wetland vegetation and edaphic data 2010 - 2012",
            "description": "Data includes edaphic and vegetation field data from four Oregon tidal wetlands. National Wetlands Inventory (NWI) classification: low marsh, high marsh, and palustrine tidal marsh are included for each of the sites as a means of comparing parameters between the NWI classes and actual field data. Vegetation data include number and types of plant assemblages, non-native plant cover, and species richness. Edaphic data include pore water salinity,  sediment carbon and nitrogen content, grain size and marsh surface elevation. \n\nThis dataset is associated with the following publication:\nJanousek, C.N., and C. Folger. Does National Wetland Inventory class consistently identify vegetation and edaphic differences in Oregon tidal wetlands?.   Wetlands Ecology and Management. Springer Science and Business Media B.V;Formerly Kluwer Academic Publishers B.V.,   GERMANY, 26(3): 315-329, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1405224",
            "keyword": [
                "emergent marsh",
                "ecosystem indicators",
                "National Wetlands Inventory",
                "plant composition",
                "sediment carbon",
                "wetland classification"
            ],
            "contactPoint": {
                "fn": "Christina Folger",
                "hasEmail": "mailto:folger.christina@epa.gov"
            },
            "distribution": [
                {
                    "title": "Folger-Janousek_A-4f4z_DataOR Tidal Marshes.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1405224/Folger-Janousek_A-4f4z_DataOR%20Tidal%20Marshes.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2011-08-31",
            "references": [
                "https://doi.org/10.1007/s11273-017-9575-6"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cardiopulmonary changes in humans with coronary artery disease associated with exposure to ambient concentrations of ozone.",
            "description": "The dataset contains a list of cardiac and vascular biomarkers that were obtained on each day a participant visited the EPA Human Studies Facility.  It also contains ozone concentrations on those days, which are publicly available on the EPA AirNow website. This dataset is not publicly accessible because: The dataset pertains to human research. It can be accessed through the following means: Requests to access data should be sent to Robert Devlin at devlin.robert@epa.gov. Format: The metadata are in the form of spreadsheets with health endpoints listed in columns and each human participant listed as a row.\r\nSimilar spreadsheets contain exposure information in columns and participants in rows. \n\nThis dataset is associated with the following publication:\nMirowsky, J., M. Carraway, R. Dhingra, H. Tong, L. Neas, D. Diaz-Sanchez, W. Cascio, M. Case, J. Crooks, E. Hauser, E. Dowdy, W. Krause, and R. Devlin. Ozone exposure is associated with acute changes in inflammation, fibrinolysis, and endothelial cell function in coronary artery disease patients.   ENVIRONMENTAL HEALTH. Academic Press Incorporated, Orlando, FL, USA, 16: 126, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1390160",
            "keyword": [
                "ozone concentrations",
                "heart disease",
                "air pollution",
                "cardiovascular",
                "epidemiology"
            ],
            "contactPoint": {
                "fn": "Robert Devlin",
                "hasEmail": "mailto:devlin.robert@epa.gov"
            },
            "distribution": [],
            "modified": "2017-05-01",
            "references": [
                "https://doi.org/10.1186/s12940-017-0335-0"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Measuring and modeling surface sorption dynamics of organophosphate flame retardants on impervious surfaces",
            "description": "The data presented in this data file is a product of a journal publication. The dataset contains measured and model predicted OPFRs gas-phase and surface-phase concentrations in small and micro chambers. \n\nThis dataset is associated with the following publication:\nLiang, Y., X. Liu, and M. Allen. Measuring and Modeling Surface Sorption Dynamics of  Organophosphate Flame Retardants in Chambers.   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 193: 754-762, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1373881",
            "keyword": [
                "Surface sorption",
                "SVOCs",
                "fate and transport model",
                "Organophosphate flame retardants (OPFRs)",
                "Chamber testing",
                "Sink effect",
                "Surface adsorption",
                "Langmuir isotherm",
                "Freundlich isotherm"
            ],
            "contactPoint": {
                "fn": "Xiaoyu Liu",
                "hasEmail": "mailto:liu.xiaoyu@epa.gov"
            },
            "distribution": [
                {
                    "title": "LiuXiaoyu_A-wdcf_Data Tables&Dictionary-20170804.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1373881/LiuXiaoyu_A-wdcf_Data%20Tables%26Dictionary-20170804.xlsx",
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                }
            ],
            "modified": "2017-08-04",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2017.11.080"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Porous nitrogen-enriched carbonaceous material from marine waste: chitosan-derived layered CNX catalyst for aerial oxidation of 5-hydroxymethylfurfural (HMF) to 2,5-furandicarboxylic acid",
            "description": "Chitosan-derived, porous and layered nitrogen-enriched carbonaceous CNx catalyst (PLCNx) has been synthesized from marine waste and its use demonstrated in a metal-free heterogeneous selective oxidation of 5-hydroxymethyl-furfural (HMF) to 2,5-furandicarboxylic acid (FDCA) using aerial oxygen under mild reaction conditions. \n\nThis dataset is associated with the following publication:\nVarma, R., M. Nadagouda, and S. Verma. Porous nitrogen-enriched carbonaceous material from marine waste: chitosan-derived layered CNX catalyst for aerial oxidation of 5-hydroxymethylfurfural (HMF) to 2,5-furandicarboxylic acid.   Scientific Reports. Nature Publishing Group, London,  UK, 7(13596): 1-6, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1389572",
            "keyword": [
                "Porous nitrogen-enriched carbonaceous material",
                "chitosan-derived layered CNX catalyst",
                "Aerial oxidation",
                "5-hydroxymethylfurfural (HMF)",
                "furandicarboxylic acid",
                "marine waste"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "Supporting information.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1389572/Supporting%20information.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2017-08-10",
            "references": [
                "https://doi.org/10.1038/s41598-017-14016-5",
                "https://pasteur.epa.gov/uploads/10.23719/1389572/documents/Supporting%20information.pdf"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1389572/documents/Supporting%20information.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Experimental data obtained by the characterization and leaching of industrially lead contaminated soil projected to the stored in a repository.",
            "description": "The data set contains the elemental composition, pH, and surface area, TOC, IC and bulk density of the soils to be deposited in a repository. Additionally, contains the leaching results of the TCLP, SPLP, and a Controlled Acidity Leaching Protocol and the results of the sequential extraction performed with such soils. \n\nThis dataset is associated with the following publication:\nPinto, P., and S. Al-Abed. Assessing Metal Mobilization from Industrially Lead-Contaminated Soils Located at an Urban Site.  W. Berry Lyons, Christopher B. Gardner, and David T. Long  APPLIED GEOCHEMISTRY. Elsevier Science Ltd, New York, NY, USA, 83: 31-40, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407596",
            "keyword": [
                "lead",
                "arsenic",
                "industrial soil",
                "soil remediation",
                "metal leaching"
            ],
            "contactPoint": {
                "fn": "Souhail Al-Abed",
                "hasEmail": "mailto:al-abed.souhail@epa.gov"
            },
            "distribution": [
                {
                    "title": "meta deta set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407596/meta%20deta%20set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-05-09",
            "references": [
                "https://doi.org/10.1016/j.apgeochem.2017.01.025"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1407596/documents/data%20dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Human BDCM Mulit-Route PBPK Model",
            "description": "This data set contains the code for the BDCM human multi-route model written in the programming language acsl.  The final published manuscript is provided since it contains all the model parameters and data (from published literature). \n\nThis dataset is associated with the following publication:\nKenyon , E., T.L. Leavens, C. Eklund , and R. Pegram. Development and Application of a Human PBPK Model for Bromodichloromethane (BDCM) to Investigate Impacts of Multi-Route Exposure.   JOURNAL OF APPLIED TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 36(9): 1095-1111, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407542",
            "keyword": [
                "acslx",
                "model code",
                "disinfection byproducts",
                "physiologically-based pharmacokinetic model",
                "pbpk",
                "bromodichloromethane",
                "multi-route"
            ],
            "contactPoint": {
                "fn": "Elaina Kenyon",
                "hasEmail": "mailto:kenyon.elaina@epa.gov"
            },
            "distribution": [
                {
                    "title": "BDCMPBPKMs.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407542/BDCMPBPKMs.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "BDCM_inhCSL.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407542/BDCM_inhCSL.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "LocalSensitivityAnalysis_BDCMpbpk.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407542/LocalSensitivityAnalysis_BDCMpbpk.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "GlobalSensitivityAnalysis_BDCMpbpk.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407542/GlobalSensitivityAnalysis_BDCMpbpk.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "VmaxKm_HanesWolfPlot_bdcm.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407542/VmaxKm_HanesWolfPlot_bdcm.pdf",
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                }
            ],
            "modified": "2015-12-01",
            "references": [
                "https://doi.org/10.1002/jat.3269"
            ],
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                }
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            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Summary of the Development the US Environmental Protection Agency\u2019s Medaka Extended One Generation Reproduction Test (MEOGRT) Using Data from Nine Multigenerational Medaka Tests",
            "description": "In response to various legislative mandates the United States Environmental Protection Agency (USEPA) formed its Endocrine Disruptor Screening Program (EDSP), which in turn, implemented a tiered testing strategy to determine the potential of pesticides, commercial chemicals, and environmental contaminants to disrupt the endocrine system.  The first tier of tests is intended to detect the potential for endocrine disruption mediated through estrogen, androgen or thyroid pathways, while the second tier is intended to further characterize the effects on these pathways and to establish a dose-response relationship for adverse effects.   One of these Tier 2 tests, the Medaka Extended One Generation Reproduction Test (MEOGRT) was developed by the USEPA for the EDSP and, in collaboration with the Japanese Ministry of the Environment, for the Organisation for Economic Co-operation and Development\u2019s (OECD) Guidelines for the Testing of Chemicals.  The MEOGRT protocol was iteratively modified based upon knowledge gained after successfully completing nine tests with variations in test protocols.  The dataset  both the final MEOGRT protocol that has been published by the USEPA and the OECD, the iterations of the protocol that provided valuable insights into nuances of the protocol.  The various tests include exposure to 17\u03b2-estradiol, 4-t-octylphenol, o,p\u2019- dichlorodiphenyltrichloroethane, 4-chloro-3-methylphenol, tamoxifen, 17\u03b2-trenbolone, vinclozolin, and prochloraz. \n\nThis dataset is associated with the following publication:\nFlynn, K., D. Lothenbach, F. Whiteman, D. Hammermeister, L. Touart, J. Swintek, N.  Tatarazako, Y. Onishi, and R. Johnson. Summary of the development the US Environmental Protection Agency\u2019s Medaka Extended One Generation Reproduction Test (MEOGRT) using data from 9 multigenerational medaka tests.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 36(12): 3387-3403, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1374722",
            "keyword": [
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                "endocrine disruption",
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                "aquatic toxicity"
            ],
            "contactPoint": {
                "fn": "Kevin Flynn",
                "hasEmail": "mailto:flynn.kevin@epa.gov"
            },
            "distribution": [
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            ],
            "modified": "2015-05-20",
            "references": [
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                    "name": "U.S. Environmental Protection Agency",
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                        "name": "U.S. Government"
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                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
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        {
            "title": "Wehmas et al. 94-04 Toxicol Sci: Datasets for manuscript",
            "description": "Dataset includes overview text document (accepted version of manuscript) and tables, figures, and supplementary materials. Supplementary tables provide summary data underlying figures, as noted in the text. \n\nThis dataset is associated with the following publication:\nWehmas, L., A. Deangelo, S. Hester, B. Chorley, G. Carswell, G. Olson, M. George, J. Carter, S. Eldridge, A. Fisher, B. Vallanat, and C. Wood. Metabolic Disruption Early in Life is Associated With Latent Carcinogenic Activity of Dichloroacetic Acid in Mice.   TOXICOLOGICAL SCIENCES. Society of Toxicology,    159(2): 354-365, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1372476",
            "keyword": [
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                "Metabolism",
                "early-life exposure",
                "liver",
                "dichloroacetic acid"
            ],
            "contactPoint": {
                "fn": "Charles Wood",
                "hasEmail": "mailto:wood.charles@epa.gov"
            },
            "distribution": [
                {
                    "title": "Wehmas et al. 94-04 Toxicol Sci_Main Text_resub cw5 clean.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372476/Wehmas%20et%20al.%2094-04%20Toxicol%20Sci_Main%20Text_resub%20cw5%20clean.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Wehmas et al. 94-04 Toxicol Sci Figures 1-5.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372476/Wehmas%20et%20al.%2094-04%20Toxicol%20Sci%20Figures%201-5.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Wehmas et al. 94-04 Toxicol Sci_Table 1_v6.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372476/Wehmas%20et%20al.%2094-04%20Toxicol%20Sci_Table%201_v6.pdf",
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                {
                    "title": "Wehmas et al. 94-04 Toxicol Sci_Supplementary Figures 1-4.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372476/Wehmas%20et%20al.%2094-04%20Toxicol%20Sci_Supplementary%20Figures%201-4.pdf",
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                    "title": "Wehmas et al. 94-04 Toxicol Sci_Supplementary Table S2_v4.pdf",
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                    "title": "Wehmas et al. 94-04 Toxicol Sci_Supplementary Table S3_v5.pdf",
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                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372476/Wehmas%20et%20al.%2094-04%20Toxicol%20Sci_Supplementary%20Table%20S6_v6.pdf",
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                    "title": "Wehmas et al. 94-04 Toxicol Sci_Supplementary Table S11_v2.xlsx",
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                    "title": "Wehmas et al. 94-04 Toxicol Sci_Supplementary Table S12_v2.xlsx",
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                    "title": "Wehmas et al. 94-04 Toxicol Sci_Supplementary Table S13_v2.xlsx",
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                    "title": "Wehmas et al. 94-04 Toxicol Sci_Supplementary Table S14_v2.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372476/Wehmas%20et%20al.%2094-04%20Toxicol%20Sci_Supplementary%20Table%20S14_v2.xlsx",
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                },
                {
                    "title": "Wehmas et al. 94-04 Toxicol Sci_Supplementary Table S15_v6.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372476/Wehmas%20et%20al.%2094-04%20Toxicol%20Sci_Supplementary%20Table%20S15_v6.xlsx",
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                {
                    "title": "Wehmas et al. 94-04 Toxicol Sci_Supplementary Table S16_v3.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372476/Wehmas%20et%20al.%2094-04%20Toxicol%20Sci_Supplementary%20Table%20S16_v3.xlsx",
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                }
            ],
            "modified": "2017-06-22",
            "references": [
                "https://doi.org/10.1093/toxsci/kfx146"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
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                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Enterovirus species and serotype distributions in monthly municipal wastewater samples",
            "description": "This dataset contains the enterovirus genome copies measured per liter of sample and read counts obtained from amplicon sequencing of the VP1 and VP4 genes. \n\nThis dataset is associated with the following publication:\nBrinkman , N., S. Fout , and S. Keely. Retrospective Surveillance of Wastewater To Examine Seasonal Dynamics of Enterovirus Infections.   mSphere. American Society for Microbiology, Washington, DC, USA, 2(3): e00099-17, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1377810",
            "keyword": [
                "enteric virus",
                "enterovirus",
                "high throughput sequencing",
                "wastewater surveillance"
            ],
            "contactPoint": {
                "fn": "Nichole Brinkman",
                "hasEmail": "mailto:brinkman.nichole@epa.gov"
            },
            "distribution": [
                {
                    "title": "BrinkmanNichole_A-73nf_dataset_20180818.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377810/BrinkmanNichole_A-73nf_dataset_20180818.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-12-28",
            "references": [
                "https://doi.org/10.1128/msphere.00099-17"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The Acute Toxicity of Major Ion Salts to Ceriodaphnia dubia. III. Mathematical models for mixture toxicity",
            "description": "This dataset concerns the development of models for describing the acute toxicity of major ions to Ceriodaphnia dubia using data from single salt tests and binary mixture tests described in two other datasets under this research effort.  It provides the data used in model development in the associated journal article.  It also provides concentration-response data and associated general chemistry conditions for 3 experiments consisting of 14 toxicity tests on more complex mixtures of major ions based on data regarding elevated major ions in effluents and receiving waters, which was used for testing the models. . \n\nThis dataset is associated with the following publication:\nErickson, R., D. Mount, T. Highland, R. Hockett, D. Hoff, T. Norberg-King, and K.  Peterson. The acute toxicity of major ion salts to Ceriodaphnia dubia: III.  Mathematical models for mixture toxicity.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA,  1-13, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1393907",
            "keyword": [
                "Ceriodaphnia dubia",
                "Acute Toxicity",
                "modeling",
                "Complex Mixtures",
                "Major Ion Toxicity",
                "Freshwater"
            ],
            "contactPoint": {
                "fn": "Russell Erickson",
                "hasEmail": "mailto:erickson.russell@epa.gov"
            },
            "distribution": [
                {
                    "title": "MEDIonToxPaper3_Dataset.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393907/MEDIonToxPaper3_Dataset.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-06-14",
            "references": [
                "https://doi.org/10.1002/etc.3953"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1393907/documents/MEDIonToxPaper3_DataDictionary.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Newton SSANTA Dr Water using POU filters dataset",
            "description": "This dataset contains information about all the features extracted from the raw data files, the formulas that were assigned to some of these features, and the candidate compounds that correspond to those formulas.  Data sources, bioactivity, exposure estimates, functional uses, and predicted and observed retention times are available for all candidate compounds. \n\nThis dataset is associated with the following publication:\nNewton, S., R. McMahen, J. Sobus, K. Mansouri, A. Williams, A. McEachran, and M. Strynar. Suspect Screening and Non-Targeted Analysis of Drinking Water Using Point-Of-Use Filters.   ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 234: 297-306, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1390166",
            "keyword": [
                "molecular feature",
                "database match",
                "candidate compounds",
                "suspect screening",
                "drinking water",
                "non-targeted analysis",
                "per and polyfluorinated",
                "time of flight mass spectrometry"
            ],
            "contactPoint": {
                "fn": "Mark Strynar",
                "hasEmail": "mailto:strynar.mark@epa.gov"
            },
            "distribution": [
                {
                    "title": "Newton Brita Dr Water Data 6-8-17.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390166/Newton%20Brita%20Dr%20Water%20Data%206-8-17.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-08",
            "references": [
                "https://doi.org/10.1016/j.envpol.2017.11.033"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Drinking Water Earthquake Resilience Paper Data",
            "description": "Data for the 9 figures contained in the paper, A SOFTWARE FRAMEWORK FOR ASSESSING THE RESILIENCE OF DRINKING WATER SYSTEMS TO DISASTERS WITH AN EXAMPLE EARTHQUAKE CASE STUDY. \n\nThis dataset is associated with the following publication:\nKlise, K., M. Bynum, D. Moriarty, and R. Murray. A SOFTWARE FRAMEWORK FOR ASSESSING THE RESILIENCE OF DRINKING WATER SYSTEMS TO DISASTERS WITH AN EXAMPLE EARTHQUAKE CASE STUDY.   ENVIRONMENTAL MODELLING & SOFTWARE. Elsevier Science, New York, NY,   95: 420-431, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1379519",
            "keyword": [
                "water security",
                "resilience",
                "modeling",
                "earthquake",
                "disasters",
                "EPANET",
                "systems modeling",
                "drinking water",
                "hydraulics",
                "water quality"
            ],
            "contactPoint": {
                "fn": "Regan Murray",
                "hasEmail": "mailto:murray.regan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Resilience_paper_data_051217.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379519/Resilience_paper_data_051217.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-05-12",
            "references": [
                "https://doi.org/10.1016/j.envsoft.2017.06.022"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Small Footprint Solar/Wind-powered CASTNET System Dataset",
            "description": "In this Research Effort \u201cSmall Footprint Solar/Wind-Powered CASTNET System\u201d there are two data sets. One data set contains  atmospheric  concentration measurements,  at the standard CASTNET site at Cowetta, NC (COW005)  and the special CASTNET  site at Screwdriver Knob, Cowetta, NC (COW137);  the other data set contains test data used to evaluate the small footprint monitoring systems  operating  conditions/limits.  The measurement parameters for the atmospheric concentrations are: Site ID,   Year, Dates , SO2 ug/m3, SO4= ug/m3, HNO3 ug/m3, NO3- ug/m3, NH4+ ug/m3, Total NO3- ug/m3,  Ca++ ug/m3,  K+ ug/m3, Mg++ ug/m3, Na+ ug/m3, Cl- ug/m3.  The test data set contains the Site ID, the Date and Time,  Battery Voltage (Volts), Flow Rate (lpn), Temp (C), Solar Output (watts), and Wind Output (watts). \n\nThis dataset is associated with the following publication:\nBaumgardner, R., C. Rogers, M. Puchalski, J. Walker, T. Lavery, and K. Mishole. Small Footprint Solar/Wind Powered CASTNET System. U.S. Environmental Protection Agency, Washington, DC, USA, 2017.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1374717",
            "keyword": [
                "The measurement parameters for the atmospheric concentrations are: Site ID",
                "Year",
                "Dates",
                "SO2 ug/m3",
                "SO4= ug/m3",
                "HNO3 ug/m3",
                "NO3- ug/m3",
                "NH4+ ug/m3",
                "Total NO3- ug/m3",
                "Ca++ ug/m3",
                "K+ ug/m3",
                "Mg++ ug/m3",
                "Na+ ug/m3",
                "Cl- ug/m3.  The test data set contains the Site ID",
                "the Date and Time",
                "Battery Voltage (Volts)",
                "Flow Rate (lpn)",
                "Temp (C)",
                "Solar Output (watts)",
                "and Wind Output (watts)",
                "Solar/Wind Powered",
                "Sulfur Polluants",
                "Nitrogen Pollutants",
                "Secondary Standard",
                "Acidic Deposition"
            ],
            "contactPoint": {
                "fn": "Ralph Baumgardner",
                "hasEmail": "mailto:baumgardner.ralph@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://java.epa.gov/castnet/clearsession.do",
                    "accessURL": "https://java.epa.gov/castnet/clearsession.do"
                }
            ],
            "modified": "2017-08-02",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1374717/documents/Data%20Dictionary-%20Small%20Footprint%20%20Solar-Wind-Powered%20CASTNET%20System.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "YSI multimeter data",
            "description": "A YSI Model 556 multi-parameter instrument was utilized to collect traceable temperature compensated specific conductivity (SC) readings to scale each Onset in-river sonde using manufacturer provided HOBOware\u00ae Conductivity Assistant software. The YSI instrument was calibrated each morning using YSI-3161 1000 \u03bcS cm\u22121 standard solution, checked again each night, and checked weekly using YSI-3165 100,000 \u03bcS cm\u22121 standard solution.\r\nDaily calibration check precision (n = 42) was 98 \u00b1 2% (mean \u00b1 standard deviation), and the weekly high range linearity check precision (n = 9) was 95 \u00b1 4%. \n\nThis dataset is associated with the following publication:\nLandis , M., A. Kamal, K. Kovalcik , C. Croghan , G. Norris , and A. Bergdale. The Impact of Commercially Treated Oil and Gas Produced Water Discharges on Bromide Concentrations and Modeled Brominated Trihalomethane Disinfection Byproducts at two Downstream Municipal Drinking Water Plants in the Upper Allegheny River, Pennsylvania, USA.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 542(2016): 505-520, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1364384",
            "keyword": [
                "Specific Conductivity",
                "Source Attribution"
            ],
            "contactPoint": {
                "fn": "Matthew Landis",
                "hasEmail": "mailto:landis.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "YSI_multimeter_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1364384/YSI_multimeter_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-20",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "U.S. Geological Survey: Surface-Water Historical Instantaneous Data for the Nation: Build Time Series",
            "description": "The USGS historical data base contains historical surface water discharge volume data for all 16,658 surface water sites that have current conditions. \n\nThis dataset is associated with the following publication:\nLandis , M., A. Kamal, K. Kovalcik , C. Croghan , G. Norris , and A. Bergdale. The Impact of Commercially Treated Oil and Gas Produced Water Discharges on Bromide Concentrations and Modeled Brominated Trihalomethane Disinfection Byproducts at two Downstream Municipal Drinking Water Plants in the Upper Allegheny River, Pennsylvania, USA.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 542(2016): 505-520, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1364360",
            "keyword": [
                "Specific Conductivity",
                "Source Attribution"
            ],
            "contactPoint": {
                "fn": "Matthew Landis",
                "hasEmail": "mailto:landis.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://waterdata.usgs.gov/nwis/uv/?referred_module=sw",
                    "accessURL": "https://waterdata.usgs.gov/nwis/uv/?referred_module=sw"
                }
            ],
            "modified": "2016-09-21",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "ISCO Grab Sample Ion Chromatography Analytical Data",
            "description": "ISCO grab samples were collected from river, wastewater treatment plant discharge, and public drinking water intakes.  Samples were analyzed for major ions (ppb) using a dual Dionex Model ICS2000 Ion Chromatography System, and Specific Conductivity (\u03bcS/cm) using Mettler Toledo Model S47-K meter equipped with an InLab\u00ae731 probe. \n\nThis dataset is associated with the following publication:\nLandis , M., A. Kamal, K. Kovalcik , C. Croghan , G. Norris , and A. Bergdale. The Impact of Commercially Treated Oil and Gas Produced Water Discharges on Bromide Concentrations and Modeled Brominated Trihalomethane Disinfection Byproducts at two Downstream Municipal Drinking Water Plants in the Upper Allegheny River, Pennsylvania, USA.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 542(2016): 505-520, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1364381",
            "keyword": [
                "Major Ions",
                "Specific Conductivity",
                "Source Attribution"
            ],
            "contactPoint": {
                "fn": "Matthew Landis",
                "hasEmail": "mailto:landis.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "ISCO_grab_sample_IC_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1364381/ISCO_grab_sample_IC_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-20",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Onset in-river conductivity sonde data",
            "description": "Onset HOBO Model U24-01 in-river sondes were deployed to measure water temperature and electrical conductivity at each of the ISCO sampling sites at 5 min intervals. \n\nThis dataset is associated with the following publication:\nLandis , M., A. Kamal, K. Kovalcik , C. Croghan , G. Norris , and A. Bergdale. The Impact of Commercially Treated Oil and Gas Produced Water Discharges on Bromide Concentrations and Modeled Brominated Trihalomethane Disinfection Byproducts at two Downstream Municipal Drinking Water Plants in the Upper Allegheny River, Pennsylvania, USA.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 542(2016): 505-520, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1364383",
            "keyword": [
                "Specific Conductivity",
                "Source Attribution"
            ],
            "contactPoint": {
                "fn": "Matthew Landis",
                "hasEmail": "mailto:landis.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "river_sonde_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1364383/river_sonde_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-20",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Size-Selective Sampling Performance of Six Low-Volume \u201cTotal\u201d Suspended Particulate (TSP) Inlets",
            "description": "Results from the comprehensive wind tunnel evaluation of six low-volume aerosol inlets are presented as a function of wind speed and aerodynamic particle diameter. \n\nThis dataset is associated with the following publication:\nVanderpool, R., J. Krug, S. Kaushik, J. Gilberry, A. Dart, and C. Witherspoon. Size-selective sampling performance of six low-volume \u201ctotal\u201d suspended particulate (TSP) inlets.   AEROSOL SCIENCE AND TECHNOLOGY. Taylor & Francis, Inc., Philadelphia, PA, USA, 52(1): 98-113, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1376892",
            "keyword": [
                "Aerosol",
                "particulate",
                "inlet",
                "low-volume",
                "size-selective",
                "samplers",
                "inlets",
                "particulates"
            ],
            "contactPoint": {
                "fn": "Robert Vanderpool",
                "hasEmail": "mailto:vanderpool.robert@epa.gov"
            },
            "distribution": [
                {
                    "title": "Low-Volume_Inlets_ScienceHub_Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376892/Low-Volume_Inlets_ScienceHub_Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-15",
            "references": [
                "https://doi.org/10.1080/02786826.2017.1386766"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Citizen Science in the Ironbound Community",
            "description": "Time stamp data of non-identified locations within the Ironbound community.  A normalization data table is provided that defines established regression between sensors pod units 1-4 and State of New Jersey reference monitoring data performed during a collocation event.  In addition, a table is provided that defines the 90th percentile of air quality measures following data normalization. \n\nThis dataset is associated with the following publication:\nKaufman, A., R. Williams, T. Barzyk, M. Greenberg, M. OShea, P. Sheridan, A. Hoang, C. Ash, A. Teitz, M. Mustafa, and S. Garvey. A Citizen Science and Government Collaboration: Developing Tools to Facilitate Community Air Monitoring.   ENVIRONMENTAL JUSTICE. Mary Ann Liebert, Inc., New Rochelle, NY, USA, 10(2): 1-11, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407516",
            "keyword": [
                "citizen science",
                "low cost air quality sensors",
                "citizen science air monitor",
                "nitrogen dioxide",
                "Fine Particulate Matter",
                "air sensors toolbox"
            ],
            "contactPoint": {
                "fn": "Ronald Williams",
                "hasEmail": "mailto:williams.ronald@epa.gov"
            },
            "distribution": [
                {
                    "title": "U1_L9_3-18_3-25.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/U1_L9_3-18_3-25.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "U4_L20_6-16_7-14.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/U4_L20_6-16_7-14.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "U4_L4_2-12_2-27.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/U4_L4_2-12_2-27.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "U3_L19_6-25_7-14.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/U3_L19_6-25_7-14.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "U3_L16_4-24_5-11.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/U3_L16_4-24_5-11.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "U3_L11_3-18_3-25.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/U3_L11_3-18_3-25.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "U3_L7_3-3_3-16.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/U3_L7_3-3_3-16.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "U3_L3_2-12_2-24.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/U3_L3_2-12_2-24.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "U2_L15_4-21_5-11.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/U2_L15_4-21_5-11.xlsx",
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                },
                {
                    "title": "U2_L6_2-28_3-16.xlsx",
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                {
                    "title": "U2_L2_2-12_2-27.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/U2_L2_2-12_2-27.xlsx",
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                },
                {
                    "title": "U1_L17_6-25_7-10.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/U1_L17_6-25_7-10.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "U1_L14_4-21_5-12.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/U1_L14_4-21_5-12.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "U1_L5_3-3_3-16.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/U1_L5_3-3_3-16.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "U1_L1_2-12_2-27.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/U1_L1_2-12_2-27.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "NormalizationTableUsedinSupportofmanuscriptOutput.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/NormalizationTableUsedinSupportofmanuscriptOutput.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Location Avg and 90th.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407516/Location%20Avg%20and%2090th.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-20",
            "references": [
                "https://doi.org/10.1089/env.2016.0044"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
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            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Performance Evaluation of the United Nations Environment Programme Air Quality Unit",
            "description": "The Reference data represents reference monitoring data associated with EPA-operated air monitoring equipment located at its AIRS test site in the Research Triangle Park, NC campus.  The UN sensor pod data represents data collected simultaneously (collocated) as the Reference data and then subsequently used in a comparison of the agreement between sensor pod and reference monitors. Original time intervals of the various data collections are preserved in the two data sets. \n\nThis dataset is associated with the following publication:\nWilliams, R., T. Conner, A. Clements, V. Foltescu, V. Nthusi, J. Jabbour, D. Nash, J. Rice, A. Kaufman, A. Rourk, and M. Srivastava. Performance Evaluation of the United Nations Environment Programme Air Quality Monitoring Unit. U.S. Environmental Protection Agency, Washington, DC, USA, 2017.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407558",
            "keyword": [
                "reference",
                "Sensor pod",
                "time interval",
                "sensor",
                "united nations",
                "particulate matter",
                "nitrogen dioxide",
                "sulfur dioxide"
            ],
            "contactPoint": {
                "fn": "Ronald Williams",
                "hasEmail": "mailto:williams.ronald@epa.gov"
            },
            "distribution": [
                {
                    "title": "Reference_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407558/Reference_data.xlsx",
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                },
                {
                    "title": "UN Pod_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407558/UN%20Pod_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-09",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
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            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Toxicity Assessment for EPA's Hydraulic Fracturing Study",
            "description": "This dataset contains data used to develop multiple manuscripts on the toxicity of chemicals associated with the hydraulic fracturing industry. These manuscripts were developed as part of EPA's larger study on the potential for hydraulic fracturing to impact drinking water resources. For each manuscript, we have provided a separate Excel file containing all of the data used to develop that manuscript. The full list of chemicals and toxicity values used in the development of these manuscripts can also be found online in the draft database for EPA's hydraulic fracturing study (URL provided as part of the dataset). \n\nThis dataset is associated with the following publications:\nYost , E., J. Stanek , R. Dewoskin , and L. Burgoon. Overview of Chronic Oral Toxicity Values for Chemicals Present in Hydraulic Fracturing Fluids, Flowback and Produced Waters.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50: 4788-4797, (2016).\nYost , E., J. Stanek , R. Dewoskin , and L. Burgon. Estimating the Potential Toxicity of Chemicals Associated with Hydraulic Fracturing Operations Using Quantitative Structure Activity Relationship Modeling.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(14): 7732-7742, (2016).\nYost, E., J. Stanek, and L. Burgoon. A Decision Analysis Framework for Estimating the Potential Hazards for Drinking Water Resources of Chemicals Used in Hydraulic Fracturing Fluids.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 574: 1544-1558, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1390101",
            "keyword": [
                "hydraulic fracturing",
                "drinking water",
                "toxicity",
                "hazard evaluation",
                "qsar"
            ],
            "contactPoint": {
                "fn": "Erin Yost",
                "hasEmail": "mailto:yost.erin@epa.gov"
            },
            "distribution": [
                {
                    "title": "Chronic_Oral_Toxicity_Values_for_Chemicals_in_HF_Fluids_Flowback_and_Produced_Water.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390101/Chronic_Oral_Toxicity_Values_for_Chemicals_in_HF_Fluids_Flowback_and_Produced_Water.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://cfpub.epa.gov/ncea/hfstudy/recordisplay.cfm?deid=308341",
                    "accessURL": "https://cfpub.epa.gov/ncea/hfstudy/recordisplay.cfm?deid=308341"
                },
                {
                    "title": "Potential_Toxicity_of_Chemicals_Associated_with_HF_Using_QSAR_Modeling.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390101/Potential_Toxicity_of_Chemicals_Associated_with_HF_Using_QSAR_Modeling.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "MCDA_for_Est_Potential_Haz_of_Chems_Used_in_HF_Fluids.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390101/MCDA_for_Est_Potential_Haz_of_Chems_Used_in_HF_Fluids.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-06-04",
            "references": [
                "http://pubs.acs.org/doi/abs/10.1021/acs.est.5b05327",
                "https://doi.org/10.1016/j.scitotenv.2016.08.167"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Kaushal et al. 2017 (Applied Geochemistry) Human-accelerated weathering increases salinization, major ions, and alkalinization in fresh water across land use",
            "description": "\u2022Base cations increased in drinking water over \u223c50 years coinciding with urbanization.\n\u2022DIC, cations, Si, SO42- and pH in streams increased with impervious surface cover.\n\u2022Road salts and weathering of impervious surfaces were major sources of ions.\n\u2022Base cations and pH contributed to alkalinization from headwaters to coastal waters.\n\u2022Increased ions impact drinking water, infrastructure, and coastal alkalinization. \n\nThis dataset is associated with the following publication:\nKaushal, S., S. Duan, T. Doody, S. Haq, R. Smith, T. Newcomer Johnson, K. Delany Newcomb, J. Gorman, N. Bowman, P. Mayer, K.L. Wood, K.T. Belt, and W.P. Sack. Human-accelerated weathering increases salinization, major ions, and alkalinization in fresh water across land use.   APPLIED GEOCHEMISTRY. Elsevier Science Ltd, New York, NY, USA, 83: 121-135, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1404721",
            "keyword": [
                "salinization",
                "weathering",
                "alkalinization",
                "base cations",
                "drinking water",
                "impervious surface cover",
                "road salt",
                "infrastructure",
                "land use"
            ],
            "contactPoint": {
                "fn": "Tamara Newcomer Johnson",
                "hasEmail": "mailto:newcomer-johnson.tammy@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.sciencedirect.com/science/article/pii/S0883292717301282",
                    "accessURL": "https://www.sciencedirect.com/science/article/pii/S0883292717301282"
                }
            ],
            "modified": "2016-07-15",
            "references": [
                "https://doi.org/10.1016/j.apgeochem.2017.02.006"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Tetrabromobisphenol A In vitro Dermal Absopriton Data",
            "description": "In vitro dermal absorption data of tetrabromobisphenol A using human cadaver and rat skin. \n\nThis dataset is associated with the following publication:\nKnudsen, G., M. Hughes , K.L. McIntosh, J.M. Sanders, and L.S. Birnbaum. Estimation of Tetrabromobisphenol A (TBBPA)percutaneous uptake in humans using the parallelogram method..   TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 289(2): 323-329, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1390108",
            "keyword": [
                "brominated flame retardant",
                "skin",
                "absorption",
                "in vitro"
            ],
            "contactPoint": {
                "fn": "Michael Hughes",
                "hasEmail": "mailto:hughes.michaelf@epa.gov"
            },
            "distribution": [
                {
                    "title": "TBBPA Dermal In vitro Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390108/TBBPA%20Dermal%20In%20vitro%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-08-27",
            "references": [
                "https://doi.org/10.1016/j.taap.2015.09.012"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Differential genomic effects on signaling pathways by two different CeO2 nanoparticles in HepG2 cells   ",
            "description": "Differential genomic effects on signaling pathways by two different CeO2 nanoparticles in HepG2 cells. \n\nThis dataset is associated with the following publication:\nThai , S., K. Wallace , C. Jones , H. Ren , B. Castellon, J. Crooks , E.A. Grulke, and K. Kitchin. Differential genomic effects on signaling pathways by two different CeO2 nanoparticles in HepG2 cells.   Journal of Nanoscience and Nanotechnology. American Scientific Publishers, VALENCIA, CA, USA, 15(12): 9925-37, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390126",
            "keyword": [
                "Nanoparticle",
                "nanomaterial",
                "nano CeO2",
                "mRNA profiling",
                "signaling pathways",
                "Warburg effect"
            ],
            "contactPoint": {
                "fn": "Kirk Kitchin",
                "hasEmail": "mailto:kitchin.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "filtered_data_fc_qvalues.LAA-high_vs_Control.p0.05.1.5x_QN.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390126/filtered_data_fc_qvalues.LAA-high_vs_Control.p0.05.1.5x_QN.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "filtered_data_fc_qvalues.LAA-low_vs_Control.p0.05.1.5x_QN.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390126/filtered_data_fc_qvalues.LAA-low_vs_Control.p0.05.1.5x_QN.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "filtered_data_fc_qvalues.LAA-mid_vs_Control.p0.05.1.5x_QN.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390126/filtered_data_fc_qvalues.LAA-mid_vs_Control.p0.05.1.5x_QN.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "filtered_data_fc_qvalues.MNA-high_vs_Control.p0.05.1.5x_QN.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390126/filtered_data_fc_qvalues.MNA-high_vs_Control.p0.05.1.5x_QN.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "filtered_data_fc_qvalues.MNA-low_vs_Control.p0.05.1.5x_QN.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390126/filtered_data_fc_qvalues.MNA-low_vs_Control.p0.05.1.5x_QN.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "filtered_data_fc_qvalues.MNA-mid_vs_Control.p0.05.1.5x_QN.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390126/filtered_data_fc_qvalues.MNA-mid_vs_Control.p0.05.1.5x_QN.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-09-28",
            "references": [
                "https://doi.org/10.1166/jnn.2015.11631"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A study of temporal effects of the model anti-androgen flutamide on components of the hypothalamic-pituitary-gonadal axis in adult fathead minnows",
            "description": "The aim of this study was to investigate temporal changes in the hypothalamic-pituitary-gonadal axis of fathead minnow treated with the model androgen receptor (AR) antagonist, flutamide. Reproductively-mature fish were exposed in a flow-through, measured test to either 50 or 500 \u00b5g flutamide/L for 8 d, followed by an 8-d recovery period in clean water. Samples were collected at 1, 2, 4 and 8 days during each phase of the experiment. Flutamide (500 \u00b5g/L) caused significant reductions in relative gonad size of the females on days 8 of the exposure and 1 of the recovery, and reduced expression of secondary sex characteristics in males during the exposure phase of the experiment. Ex vivo gonadal synthesis of testosterone in both sexes (and 17\u03b2-estradiol in females) was reduced in the 500 \u00b5g/L treatment within 2 d of exposure; however, steroid synthesis returned to levels comparable to controls by the end of the exposure portion of the test.  Steroid synthesis in males exposed to 50 \u00b5g flutamide/L was greater than in controls on days 4 and 8 of the exposure. Both the enhanced steroid production in the low treatment males, and return to control levels in the high treatment males and females during chemical exposure are indicative of a compensatory HPG response. One contributor to this response could be increased expression of genes responsible for enzymes involved in steroid synthesis; for example, transcripts for both cytochrome P450 side- chain cleavage and 11\u03b2-hydroxysteroid dehydrogenase were significantly elevated in flutamide-exposed males. Overall, responses of the HPG axis in adult male and female fathead minnows exposed to flutamide were both dynamic and comparatively rapid during exposure and recovery. This has ramifications both for the development of short-term fish assays to detect endocrine-active chemicals, and the derivation of robust adverse outcome pathways for AR antagonists in fish. \n\nThis dataset is associated with the following publication:\nMilsk, R., J. Cavalliin, E. Durhan, M. Kahl, E. Makynen, D. Martinovic-Weigelt, N.  Mueller, A. Schroeder, D. Villeneuve, and G. Ankley. A study of temporal effects of the model anti-androgen flutamide on components of the hypothalamic-pituitary-gonadal axis in adult fathead minnows.   AQUATIC TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 180: 164-172, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1413082",
            "keyword": [
                "Androgen receptor",
                "antagonist",
                "flutamide",
                "adverse outcome pathway",
                "endocrine disruption",
                "fish",
                "reproduction",
                "mode of action (MOA)",
                "fathead minnow"
            ],
            "contactPoint": {
                "fn": "Gerald Ankley",
                "hasEmail": "mailto:ankley.gerald@epa.gov"
            },
            "distribution": [
                {
                    "title": "Flutamide Data Set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413082/Flutamide%20Data%20Set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-28",
            "references": [
                "https://doi.org/10.1016/j.aquatox.2016.09.021"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Association between Natural Resources for OutdoorActivities and Physical Inactivity",
            "description": "it includes available natural resources for outdoor activities, Physical inactivity and households income. \n\nThis dataset is associated with the following publication:\nJiang , Y., Y. Yuan , A. Neale , L. Jackson , and M. Mehaffey. Association between Natural Resources for Outdoor Activities and Physical Inactivity: Results from the Contiguous United States.   International Journal of Environmental Research and Public Health. Molecular Diversity Preservation International, Basel,  SWITZERLAND, 13(8): 1-12, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1373091",
            "keyword": [
                "Protected areas",
                "community health",
                "physical inactivity",
                "diabetes",
                "spatial autocorrelation",
                "spatial lag model",
                "Obsity"
            ],
            "contactPoint": {
                "fn": "Yongping Yuan",
                "hasEmail": "mailto:yuan.yongping@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1373091/Data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-07-27",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Flow intermittence and ecosystem services in rivers of the Anthropocene_Figure 4_Journal of Applied Ecology",
            "description": "Counts of ecosystem service status (provided, altered, and lost/absent) during three hydrological phases (flowing, pool, dry) typically seen in intermittent rivers and ephemeral streams. The ecosystem services follow the Common International Classification of Ecosystem Services (CICES) version 4.3 across three broad categories of services (provisioning, regulating and cultural). Table 1 details these ecosystem services and how these may be altered when transitioned from flowing to pool or dry phases. \n\nThis dataset is associated with the following publication:\nDatry, T., A. Boulton, N. Bonada, K. Fritz, C. Leigh, E. Sauquet, K. Tockner, B. Hugueny, and C. Dahm. Flow intermittence and ecosystem services in rivers of the Anthropocene.   Journal of Applied Ecology. Blackwell Publishing, Malden, MA, USA, 55(1): 353-364, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1374047",
            "keyword": [
                "ecosystem services",
                "ephemeral streams",
                "intermittent rivers",
                "Anthropocene",
                "biodiversity",
                "climate change",
                "conservation",
                "flow management",
                "management",
                "rivers"
            ],
            "contactPoint": {
                "fn": "Ken Fritz",
                "hasEmail": "mailto:fritz.ken@epa.gov"
            },
            "distribution": [
                {
                    "title": "JAE_Figure4.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374047/JAE_Figure4.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-02",
            "references": [
                "https://doi.org/10.1111/1365-2664.12941"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Metabolomic effects of CeO2, SiO2 and CuO metal oxide nanomaterials on HepG2 cells",
            "description": "The data set is a matrix of cellular biochemical (metabolites) in HepG2 cells treated with various metal oxide nanomaterials composed of CeO2, SiO2 and CuO. \n\nThis dataset is associated with the following publication:\nKitchin, K., S. Stirdivant, B. Robinette, B. Castellon, and X. Liang. Metabolomic effects of CeO2, SiO2 and CuO metal oxide nanomaterials on HepG2 cells.   Particle and Fibre Toxicology. BioMed Central Ltd, London,  UK, 14(50): 1-16, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407526",
            "keyword": [
                "nano CeO2",
                "nanomaterial",
                "SiO2",
                "CeO2",
                "CuO",
                "metabolomics",
                "fatty acids",
                "HepG2"
            ],
            "contactPoint": {
                "fn": "Kirk Kitchin",
                "hasEmail": "mailto:kitchin.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Working  Heatmap recolored P and Q criteria for SCIENCE HUB.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407526/Working%20%20Heatmap%20recolored%20P%20and%20Q%20criteria%20for%20SCIENCE%20HUB.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-01-26",
            "references": [
                "https://doi.org/10.1186/s12989-017-0230-4"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Brown et al MEA Developmental Neurotoxicity Screening Manuscript",
            "description": "These data are the individual parameter and well-level data that were support the conclusions in Brown et al. Note: the parameters CVtime and CVnetwork were not used. \n\nThis dataset is associated with the following publication:\nBrown, J., D. Hall, C. Frank, K. Wallace, W. Mundy, and T. Shafer. Editor's highlight: Evaluation of a Microelectrode Array-based Assay for Neural Network Ontogeny using Training Set Chemicals.   TOXICOLOGICAL SCIENCES. Society of Toxicology,    154(1): 126-139, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1412682",
            "keyword": [
                "developmental neurotoxicity",
                "Microelectrode array",
                "In vitro assay",
                "high-throughput in vitro screening assay"
            ],
            "contactPoint": {
                "fn": "Timothy Shafer",
                "hasEmail": "mailto:shafer.tim@epa.gov"
            },
            "distribution": [
                {
                    "title": "Final_Data_Set_SA1_DNT_Paper1 (2)(updated)_CF.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1412682/Final_Data_Set_SA1_DNT_Paper1%20%282%29%28updated%29_CF.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-12-12",
            "references": [
                "https://doi.org/10.1093/toxsci/kfw147"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Simplified two and fifty-one region state-based EEIO model comparison",
            "description": "Supporting data for 2 region and 51 region models assessed in the manuscript \"Exploring the relevance of spatial scale to life cycle inventory results using environmentally-extended input-output models of the United States\". Includes results of the correlation and relative errors analysis, results in kg/$ intensities for the 17 commodities from the 2 region models and the 51 region model,  the 51-region model Make and Use tables, 10 NEI emissions and water withdrawal data aggregated by the 15 BEA sectors, interstate commodity flow data aggregated by BEA sectors between states, BEA national level Make and Use tables for 2012 at sector level, and state GDP data. \n\nThis dataset is associated with the following publication:\nYang, Y., W. Ingwersen, and D. Meyer. Exploring the relevance of spatial scale to life cycle inventory results using environmentally-extended input-output models of the United States.   ENVIRONMENTAL MODELLING & SOFTWARE. Elsevier Science, New York, NY,   99: 52-57, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390147",
            "keyword": [
                "US state life cycle inventory",
                "life cycle assessment",
                "life cycle inventory data",
                "sustainability",
                "input-output data"
            ],
            "contactPoint": {
                "fn": "Wesley Ingwersen",
                "hasEmail": "mailto:ingwersen.wesley@epa.gov"
            },
            "distribution": [
                {
                    "title": "Simplified two and fifty-one region state-based EEIO model comparison.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390147/Simplified%20two%20and%20fifty-one%20region%20state-based%20EEIO%20model%20comparison.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-10-09",
            "references": [
                "https://doi.org/10.1016/j.envsoft.2017.09.017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Modeling Rabbit Responses to Single and Multiple Aerosol Exposures of Bacillus anthracis Spores Data Set",
            "description": "The two excel files contain all of the raw data that was modeled in the R code.  The 6 word documents contain all of the R code that can be used in R to model the raw rabbit data. \n\nThis dataset is associated with the following publication:\nBartrand, T., H. Marks, M. Coleman, D. Donahue, S. Hines, J. Comer, and S. Taft. Modeling Rabbit Responses to Single and Multiple Aerosol Exposures of Bacillus anthracis Spores (HS 4.04.02 - 475).   RISK ANALYSIS. Blackwell Publishing, Malden, MA, USA, 37(5): 943-957, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1375008",
            "keyword": [
                "Bacillus antracis",
                "anthrax",
                "dose response",
                "hazard function",
                "survival analysis",
                "Indoor outdoor decontamination",
                "biological",
                "containment",
                "mitigation",
                "microbial risk assessment",
                "dose respose",
                "Bacillus anthracis"
            ],
            "contactPoint": {
                "fn": "Sarah Taft",
                "hasEmail": "mailto:taft.sarah@epa.gov"
            },
            "distribution": [
                {
                    "title": "PooledDataSet_Mortality.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375008/PooledDataSet_Mortality.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "PooledDataSet_AerosolDose_Updated Units.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375008/PooledDataSet_AerosolDose_Updated%20Units.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "BA_TimeToEvent_AcuteContinuous_Final.doc",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375008/BA_TimeToEvent_AcuteContinuous_Final.doc",
                    "mediaType": "application/msword"
                },
                {
                    "title": "BA_TimeToEvent_BetaModelsContinuous_Final.doc",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375008/BA_TimeToEvent_BetaModelsContinuous_Final.doc",
                    "mediaType": "application/msword"
                },
                {
                    "title": "BA_TimeToEvent_BootstrapPooledContinuous_Final.doc",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375008/BA_TimeToEvent_BootstrapPooledContinuous_Final.doc",
                    "mediaType": "application/msword"
                },
                {
                    "title": "BA_TimeToEvent_MultipleContinuous_Final.doc",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375008/BA_TimeToEvent_MultipleContinuous_Final.doc",
                    "mediaType": "application/msword"
                },
                {
                    "title": "BA_TimeToEvent_PooledANOVAContinuous_Final.doc",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375008/BA_TimeToEvent_PooledANOVAContinuous_Final.doc",
                    "mediaType": "application/msword"
                },
                {
                    "title": "BA_TimeToEvent_PooledContinuous_Final_Commented.doc",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375008/BA_TimeToEvent_PooledContinuous_Final_Commented.doc",
                    "mediaType": "application/msword"
                },
                {
                    "title": "BA_TimeToEvent_PooledContinuousApproxBP_Final.doc",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375008/BA_TimeToEvent_PooledContinuousApproxBP_Final.doc",
                    "mediaType": "application/msword"
                },
                {
                    "title": "BA_TimeToEvent_PooledContinuousLogProbit_Final.doc",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375008/BA_TimeToEvent_PooledContinuousLogProbit_Final.doc",
                    "mediaType": "application/msword"
                }
            ],
            "modified": "2017-01-09",
            "references": [
                "https://doi.org/10.1111/risa.12688"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Buse_Francisella Medium",
            "description": "This dataset contains colony forming unit and qPCR data. \n\nThis dataset is associated with the following publication:\nMorris, B., H. Buse, N. Adcock, and E. Rice. A novel broth medium for enhanced growth of Francisella tularensis.   Letters in Applied Microbiology. Blackwell Publishing, Malden, MA, USA, 64(6): 393-468, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407523",
            "keyword": [
                "Francisella",
                "qPCR",
                "enhanced growth medium",
                "rapid methods",
                "virulence",
                "antibiotics",
                "detection",
                "environmental"
            ],
            "contactPoint": {
                "fn": "Helen Buse",
                "hasEmail": "mailto:buse.helen@epa.gov"
            },
            "distribution": [
                {
                    "title": "Buse_Francisella Medium.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407523/Buse_Francisella%20Medium.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-12-15",
            "references": [
                "https://doi.org/10.1111/lam.12725"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A field-based characterization of conductivity in areas of minimal alteration: a case example in the Cascades of northwestern United States",
            "description": "The data set contains 3 files from three sources (1) state (Washington and Oregon), (2) Combined EPA survey date  from Griffith, (3) data from USGS. \n\nThis dataset is associated with the following publication:\nCormier, S., L. Zheng, G. Hayslip, and C. Flaherty. A field-based characterization of conductivity in areas of minimal alteration: a case example in the Cascades of northwestern United States.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 633: 1657-1666, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1396168",
            "keyword": [
                "Cascades",
                "Washington",
                "Oregon",
                "California",
                "Specific Conductivity",
                "background conductivity",
                "Extirpation",
                "benthic macroinvertebrate"
            ],
            "contactPoint": {
                "fn": "Susan Cormier",
                "hasEmail": "mailto:cormier.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "State EPA combined USGS Cascade.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1396168/State%20EPA%20combined%20USGS%20Cascade.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Data sets Cascade 508 20181007.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1396168/Data%20sets%20Cascade%20508%2020181007.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-11-20",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.02.018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1396168/documents/DataDictionaryCond_DataFileColumnMetadata_20161221.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "NRSA enzyme decomposition model data",
            "description": "Microbial enzyme activities measured at more than 2000 US streams and rivers. These enzyme data were then used to predict organic matter decomposition and microbial respiration, and to predict carbon efflux from US streams and rivers. \n\nThis dataset is associated with the following publication:\nHill, B., C. Elonen, A. Herlihy, T. Jicha, and R. Mitchell. A synoptic survey of microbial respiration, organic matter decomposition,  and carbon efflux in U.S. streams and rivers.   Limnology and Oceanography Bulletin. American Society of Limnology and Oceanography, Lawrence, KS, USA, 62(1): S147-S159, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390153",
            "keyword": [
                "CO2 efflux",
                "decomposition",
                "ecoenzymes",
                "mcirobial respiration",
                "river continuum"
            ],
            "contactPoint": {
                "fn": "Brian Hill",
                "hasEmail": "mailto:hill.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "NRSA_EDM program file.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390153/NRSA_EDM%20program%20file.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "NRSA_EDM.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390153/NRSA_EDM.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-04-28",
            "references": [
                "https://doi.org/10.1002/lno.10583"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1390153/documents/NRSA%20EDM%20Data%20Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "GoldenHeather_A-jhb9",
            "description": "No data are associated with this review/overview article. This dataset is not publicly accessible because: No data are associated with this review/overview paper. It can be accessed through the following means: N/D. Format: No data are associated with this review/overview paper. \n\nThis dataset is associated with the following publication:\nGolden, H., and N. Hoghooghi. Green infrastructure and its catchment-scale effects: an emerging science.   WIREs Water. John Wiley & Sons, Inc., Hoboken, NJ, USA, 5(1): e1254, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1366491",
            "keyword": [
                "Green Infrastructure",
                "watersheds",
                "green infrastrucutre",
                "low impact development",
                "catchments"
            ],
            "contactPoint": {
                "fn": "Heather Golden",
                "hasEmail": "mailto:golden.heather@epa.gov"
            },
            "distribution": [],
            "modified": "2017-06-19",
            "references": [
                "https://doi.org/10.1002/wat2.1254"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Scale Formation under Blended Phosphate Treatment for a Utility with Lead Pipes",
            "description": "Tap water lead profiles from the Del Toral et al (2013) study, grouped in disturbed and undisturbed Pb service line sites. \n\nThis dataset is associated with the following publication:\nWasserstrom, L., S. Miller , S. Triantafyllidou, M. DeSantis, and M. Schock. Scale Formation under Blended Phosphate Treatment for a Utility with Lead Pipes.   Journal AWWA. American Water Works Association, Denver, CO, USA, 109(11): E464-E478, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1390146",
            "keyword": [
                "tap water",
                "lead profile",
                "disturbed lead service line",
                "Blended phosphate",
                "lead corrosion",
                "galvanized pipe",
                "corrosion scale mineralogy/morphology"
            ],
            "contactPoint": {
                "fn": "Simoni Triantafyllidou",
                "hasEmail": "mailto:triantafyllidou.simoni@epa.gov"
            },
            "distribution": [
                {
                    "title": "Fig 11.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390146/Fig%2011.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-05-23",
            "references": [
                "https://doi.org/10.5942/jawwa.2017.109.0121"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Bacterial and archael 16S rRNA sequences and taxonomic summary tables for biofilm samples from the bio-reactors",
            "description": "A biofilm anode acclimated with acetate, acetate+methane, and methane growth media for over three years produced a steady current density of 1.6-2.3 mA/m^2 in a microbial electrochemical cell (MxC) fed with methane as the sole electron donor. Geobacter was the dominant genus for the bacterial domain (93%) in the biofilm anode, while methanogens (Methanocorpusculum labreanum and Methanosaeta concilii) accounted for 82% of the total archaeal clones in the biofilm. A fluorescence in situ hybridization (FISH) image clearly showed a biofilm of bacteria and archaea, supporting a syntrophic interaction between them for performing anaerobic oxidation of methane (AOM) in the biofilm anode. Measured cumulative coulombs correlated linearly to the methane-gas concentration in the range of 10% to 99.97% (R^2 \u2265 0.99) when the measurement was sustained for at least 50 min. Thus, cumulative coulombs over 50 min. could be used to quantify the methane concentration in gas samples. \n\nThis dataset is associated with the following publication:\nGao, Y., H. Ryu, B. Rittmann, A. Hussain, and H. Lee. Quantification of the methane concentration using anaerobic oxidation of methane coupled to extracellular electron transfer.   Bioresource Technology. Elsevier Online, New York, NY, USA, 241: 979-984, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1379482",
            "keyword": [
                "Extracellular electron transfer",
                "Anaerobic oxidation of methane",
                "Reverse methanogenesis",
                "Sensors"
            ],
            "contactPoint": {
                "fn": "Hodon Ryu",
                "hasEmail": "mailto:ryu.hodon@epa.gov"
            },
            "distribution": [
                {
                    "title": "TABLEs_CH4 oxidation MEC test.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379482/TABLEs_CH4%20oxidation%20MEC%20test.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "MEC_CH4 oxidation_bacterial seqs.TXT",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379482/MEC_CH4%20oxidation_bacterial%20seqs.TXT",
                    "mediaType": "text/plain"
                },
                {
                    "title": "MEC_CH4 oxidation_archael seqs.TXT",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379482/MEC_CH4%20oxidation_archael%20seqs.TXT",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2017-09-06",
            "references": [
                "https://doi.org/10.1016/j.biortech.2017.06.053"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Illumina sequencing data for MEC study on high biofilm conductivity in a Geobacter-enriched biofilm",
            "description": "This study systematically assessed intracellular electron transfer (IET) and extracellular electron transfer (EET) kinetics with respect to anode potential (Eanode) in a mixed-culture biofilm anode enriched with Geobacter spp. High biofilm conductivity (0.96\u20131.24 mScm^-1) was maintained during Eanode changes from -0.2 to +0.2 V versus the standard hydrogen electrode (SHE), although the steady-state current density significantly decreased from 2.05 to 0.35 Am^-2 in a microbial electrochemical cell. Substantial increase of the Treponema population was observed in the biofilm anode at Eanode=+0.2 V, which reduced intracellular electron-transfer kinetics associated with the maximum specific substrate-utilization rate by a factor of ten. This result suggests that fast EET kinetics can be maintained under dynamic Eanode conditions in a highly conductive biofilm anode as a result of shift of main EET players in the biofilm anode, although Eanode changes can influence IET kinetics. \n\nThis dataset is associated with the following publication:\nDhar, B., H. Ryu, H. Ren, J. Santodomingo, J. Chae, and H. Lee. High Biofilm Conductivity Maintained Despite Anode Potential Changes in a Geobacter-Enriched Biofilm.   ChemSusChem. Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim,  GERMANY, 9(24): 3485 \u20133491, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1379488",
            "keyword": [
                "Anode potential",
                "biofilm conductivity",
                "electron transfer",
                "Microbial electrochemical cell"
            ],
            "contactPoint": {
                "fn": "Hodon Ryu",
                "hasEmail": "mailto:ryu.hodon@epa.gov"
            },
            "distribution": [
                {
                    "title": "MEC-high biofilm conductivity_Illumina results_tables.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379488/MEC-high%20biofilm%20conductivity_Illumina%20results_tables.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "MEC-high biofilm conductivity-cDNA1_taxonomy.summary.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379488/MEC-high%20biofilm%20conductivity-cDNA1_taxonomy.summary.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "MEC-high biofilm conductivity-cDNA4_taxonomy.summary.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379488/MEC-high%20biofilm%20conductivity-cDNA4_taxonomy.summary.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "MEC-high biofilm conductivity-cDNA1_raw seqs.TXT",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379488/MEC-high%20biofilm%20conductivity-cDNA1_raw%20seqs.TXT",
                    "mediaType": "text/plain"
                },
                {
                    "title": "MEC-high biofilm conductivity-cDNA4_raw seqs.TXT",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379488/MEC-high%20biofilm%20conductivity-cDNA4_raw%20seqs.TXT",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2017-09-06",
            "references": [
                "https://doi.org/10.1002/cssc.201601007"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Room temperature synthesis of biodiesel using sulfonated graphitic carbon nitride",
            "description": "Sulfonation of graphitic carbon nitride (g-CN) affords a polar and strongly acidic catalyst, Sg-CN, which displays unprecedented reactivity and selectivity in biodiesel synthesis and esterification reactions at room temperature. \n\nThis dataset is associated with the following publication:\nVarma, R., R.B.N. Baig, S. Verma, and M. Nadagouda. Room temperature synthesis of biodiesel using sulfonated graphitic carbon nitride.   NATURE. Macmillan Publishers Ltd., London,  UK,  1-6, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1413224",
            "keyword": [
                "biodiesel",
                "sulfonated graphitic carbon nitride",
                "Room temperature"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "Nature Sci. Rep. 6, 39387; doi 10.1038srep39387 (2016)-Room Temperature Biodiesel Synthesis using Sulfonated Graphitic Carbon Nitride.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413224/Nature%20Sci.%20Rep.%206%2C%2039387%3B%20doi%2010.1038srep39387%20%282016%29-Room%20Temperature%20Biodiesel%20Synthesis%20using%20Sulfonated%20Graphitic%20Carbon%20Nitride.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "https://doi.org/10.1038/srep39387",
                    "accessURL": "https://doi.org/10.1038/srep39387"
                }
            ],
            "modified": "2016-12-19",
            "references": [
                "https://doi.org/10.1038/srep39387"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1413224/documents/Nature%20Sci.%20Rep.%206%2C%2039387%3B%20doi%2010.1038srep39387%20%282016%29-Room%20Temperature%20Biodiesel%20Synthesis%20using%20Sulfonated%20Graphitic%20Carbon%20Nitride.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "GIS dataset of candidate terrestrial ecological restoration areas for the United States",
            "description": "A vector GIS dataset of candidate areas for terrestrial ecological restoration based on landscape context.  The dataset was created using NLCD 2011 (www.mrlc.gov) and morphological spatial pattern analysis (MSPA) (http://forest.jrc.ec.europa.eu/download/software/guidos/mspa/).  There are 13 attributes for the polygons in the dataset, including presence and length of roads, candidate area size, size of surround contiguous natural areas, soil productivity, presence and length of road, areas suitable for wetland restoration, and others. \n\nThis dataset is associated with the following publication:\nWickham, J., K. Riiters, P. Vogt, J. Costanza, and A. Neale. An inventory of continental U.S. terrestrial candidate ecological restoration areas based on landscape context.   RESTORATION ECOLOGY. Blackwell Publishing, Malden, MA, USA, 25(6): 894-902, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1375934",
            "keyword": [
                "biodiversity",
                "ecosystem services",
                "Landscape Ecology",
                "NLCD",
                "Road ecology",
                "water quality"
            ],
            "contactPoint": {
                "fn": "James Wickham",
                "hasEmail": "mailto:wickham.james@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/enviroatlas",
                    "accessURL": "https://www.epa.gov/enviroatlas"
                }
            ],
            "modified": "2016-08-24",
            "references": [
                "https://doi.org/10.1111/rec.12522"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1375934/documents/MSPA_brch_ppr_Supplemental.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Levels of pyrethroids/degradates in Ex-R food samples",
            "description": "Levels of pyrethroid insecticides and pyrethroid degradates in Ex-R food samples. This dataset is associated with the following publication:\nMorgan, M., D. MacMillan, D. Zehr, and J. Sobus. Pyrethroid insecticides and their environmental degradates in repeated duplicate-diet solid food samples of 50 adults.   Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London,  UK, 28: 40-45, (2018). NOTE: This dataset has been removed from public access due to revocation. Please refer inquiries regarding this dataset to the listed contact person.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1374550",
            "keyword": [
                "pyrethroid",
                "insecticides",
                "pyrethroid degradates",
                "solid food",
                "diet",
                "adults",
                "degradates"
            ],
            "contactPoint": {
                "fn": "Marsha Morgan",
                "hasEmail": "mailto:morgan.marsha@epa.gov"
            },
            "distribution": [],
            "modified": "2014-09-01",
            "references": null,
            "publisher": {
                "name": "U.S. Environmental Protection Agency",
                "subOrganizationOf": {
                    "name": "U.S. Government"
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Factors Affecting Annual Zostera ",
            "description": "Dataset for figures in text and supplementary materials for a manuscript describing the influence of microtopographic variation and macroalgal cover on morphometrics and survival of the annual form of eelgrass (Zostera marina). \n\nThis dataset is associated with the following publication:\nNelson, W., and G. Sullivan. Effects of microtopographic variation and macroalgal cover on morphometrics and survival of the annual form of eelgrass (Zostera marina).   AQUATIC BOTANY. Elsevier Science Ltd, New York, NY, USA, 145: 37-44, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1375804",
            "keyword": [
                "Annual Zostera marina",
                "annual eelgrass",
                "microtopography",
                "macroalgae impact",
                "seagrass",
                "recruitment"
            ],
            "contactPoint": {
                "fn": "Walter Nelson",
                "hasEmail": "mailto:nelson.walt@epa.gov"
            },
            "distribution": [
                {
                    "title": "Annual Zostera microtopography paper data for SciHub 11_20_17.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375804/Annual%20Zostera%20microtopography%20paper%20data%20for%20SciHub%2011_20_17.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-18",
            "references": [
                "https://doi.org/10.1016/j.aquabot.2017.11.008"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Investigation clogging dynamic of permeable pavement systems using embeded sensors",
            "description": "Permeable pavement is a stormwater control measure commonly selected in both new and retrofit applications. However, there is limited information about the clogging mechanism of these systems that effects the infiltration. A permeable pavement site located at the Seitz Elementary School, on Fort Riley, Kansas was selected for this study. An 80-space parking lot was built behind the school as part of an EPA collaboration with the U.S. Army. The parking lot design includes a permeable interlocking concrete pavement section along the downgradient edge. This study monitored the clogging progress of the pavement section using twelve water content reflectometers and three buried tipping bucket rain gauges. This clogging dynamic investigations was divided into three stages namely pre-clogged, transitional, and clogged. Recorded initial relative water content of all three stages were significantly and negatively correlated to antecedent dry weather periods with stronger correlations during clogged conditions. The peak relative water content correlation with peak rainfall 10-min intensity was significant for the water content reflectometers located on the western edge away from the eastern edge; this correlation was strongest during transition stage. Once clogged, rainfall measurements no longer correlated with the buried tipping bucket rain gauges. Both water content reflectometers and buried tipping bucket rain gauges showed the progress of surface clogging. For every 6mm of rain clogging advanced 1 mm across the surface. The results generally support the hypothesis that the clogging progresses from the upgradient to the downgradient edge. The magnitude of the contributing drainage area and rainfall characteristics are effective factors on rate and progression of clogging. \n\nThis dataset is associated with the following publication:\nRazzaghmanesh, M., and M. Borst. Investigation clogging dynamic of permeable pavement systems using embedded sensors.   JOURNAL OF HYDROLOGY. Elsevier Science Ltd, New York, NY, USA, 557: 887-896, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1372833",
            "keyword": [
                "Green Infrastructure",
                "permeable pavement",
                "clogging",
                "Water content reflectometer",
                "Tipping bucket rain gauge"
            ],
            "contactPoint": {
                "fn": "Michael Borst",
                "hasEmail": "mailto:borst.mike@epa.gov"
            },
            "distribution": [
                {
                    "title": "Clogging dynamic Science hub data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372833/Clogging%20dynamic%20Science%20hub%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-13",
            "references": [
                "https://doi.org/10.1016/j.jhydrol.2018.01.012"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Screening silver nanoparticles for potential neurotoxicity using cortical neurons grown on microelectrode arrays ",
            "description": "the zip files contain outputs from the R-analysis for the nanosilver experiments. \n\nThis dataset is associated with the following publication:\nStrickland, J., W. LeFew, J. Crooks, D. Hall, J. Ortenzio , K. Dreher , and T. Shafer. In vitro screening of silver nanoparticles and ionic silver using neural networks yields differential effects on spontaneous activity and pharmacological responses..   TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 355(11): 1-8, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1413280",
            "keyword": [
                "Nanoparticle",
                "nanosilver",
                "Microelectrode array",
                "neurotoxicity",
                "High throughput screening"
            ],
            "contactPoint": {
                "fn": "Timothy Shafer",
                "hasEmail": "mailto:shafer.tim@epa.gov"
            },
            "distribution": [
                {
                    "title": "MEA_NanoAg.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413280/MEA_NanoAg.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-12-14",
            "references": [
                "https://doi.org/10.1016/j.tox.2016.05.009"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Methodological Details and Full Bibliography",
            "description": "This dataset has several components, The first part describes fully our literature review, providing details not included in the text. The second part provides all the information we used for our literature review, including the weights assigned to each relevant article and the full bibliography. \n\nThis dataset is associated with the following publication:\nDeJesus-Crespo, R., and R. Fulford. Eco-Health Linkages: Assessing the Role of Ecosystem Goods and Services on Human Health Using Causal Criteria Analysis.   International Journal of Public Health. Springer Basel AG, Basel,  SWITZERLAND, 63(1): 81-92, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1376206",
            "keyword": [
                "Literature Review Process",
                "Eco-Evidence Scoring",
                "Full Bibliography",
                "Causal criteria analysis",
                "Ecosystem Goods and Services",
                "human health",
                "Green space"
            ],
            "contactPoint": {
                "fn": "Rebeca De Jesus Crespo",
                "hasEmail": "mailto:dejesus-crespo.rebeca@epa.gov"
            },
            "distribution": [
                {
                    "title": "Eco-Health_DeJesusCrespoFulford_SupplementaryData.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376206/Eco-Health_DeJesusCrespoFulford_SupplementaryData.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-07-01",
            "references": [
                "https://doi.org/10.1007/s00038-017-1020-3"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "St Francis Hydro, Soils data",
            "description": "We collected data 2012-2016 covering spatially-explicit, soil layering, bulk density, drainage rate (2012, 2015) infiltration into rain garden mulch and mineral soil layers; and full water cycle monitoring data. Links for the latter are given in the SDM document. \n\nThis dataset is associated with the following publication:\nShuster, W., R. Darner, L. Schifman, and D. Herrmann. Factors contributing to the hydrologic effectiveness of a rain garden network (Cincinnati OH USA).   Infrastructures. MDPI AG, Basel,  SWITZERLAND, 2(3): 11, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1394116",
            "keyword": [
                "infiltration rate",
                "drainage rate",
                "soil layering",
                "bulk density",
                "wastewater",
                "combined sewer system",
                "hydrologic monitoring",
                "Green Infrastructure",
                "stormwater detention"
            ],
            "contactPoint": {
                "fn": "William Shuster",
                "hasEmail": "mailto:shuster.william@epa.gov"
            },
            "distribution": [
                {
                    "title": "DataWrap_StF.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394116/DataWrap_StF.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-07-18",
            "references": [
                "https://doi.org/10.3390/infrastructures2030011"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Minimal_Set_of_In_Vitro_ER_Agonist_Assays_Selection_RegToxPharm_Data",
            "description": "A dataset for the manuscript which demonstrates that it is possible to achieve levels of performance equivalent to the full 16 assay ER agonist model against both in vitro and in vivo reference chemical sets, using only 4 assays in the simplest \u201csubset\u201d ER agonist model. \n\nThis dataset is associated with the following publication:\nJudson, R., K. Houck, E. Watt, and R. Thomas. (REGULATORY TOXICOLOGY AND PHARMACOLOGY) On Selecting a Minimal Set of In Vitro Assays to Reliably Determine Estrogen Agonist Activity.   REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 91: 39-49, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407002",
            "keyword": [
                "ToxCast",
                "EDSP Models",
                "ACToR"
            ],
            "contactPoint": {
                "fn": "Richard Judson",
                "hasEmail": "mailto:judson.richard@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/Judson/ER_Assay_Select/",
                    "accessURL": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/Judson/ER_Assay_Select/"
                }
            ],
            "modified": "2017-03-01",
            "references": [
                "https://doi.org/10.1016/j.yrtph.2017.09.022"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Datasets in Gene Expression Omnibus used in the study ORD-020969: Genomic effects of androstenedione and sex-specific liver cancer susceptibility in mice ",
            "description": "Datasets in Gene Expression Omnibus used in the study ORD-020969: Genomic effects of androstenedione and sex-specific liver cancer susceptibility in mice. \n\nThis dataset is associated with the following publication:\nRooney, J., N. Ryan, B. Chorley, S. Hester, E. Kenyon, J. Schmid, B. George, M. Hughes, Y. Sey, A. Tennant, D. MacMillan, J. Simmons, C. McQueen, A. Pandiri, C. Wood, and C. Corton. Genomic effects of androstenedione and sex-specific liver cancer susceptibility in mice.   TOXICOLOGICAL SCIENCES. Society of Toxicology,    160(1): 15\u201329, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1376230",
            "keyword": [
                "Gene Expression Omnibus Accession Numbers",
                "Childrens Health",
                "microarray",
                "Androgen receptor",
                "estrogen receptor",
                "glucococorticoid receptor",
                "androstenedione",
                "ethinyl estradiol",
                "prednisone"
            ],
            "contactPoint": {
                "fn": "Jon Corton",
                "hasEmail": "mailto:corton.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data submission for A-3bk7.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376230/Data%20submission%20for%20A-3bk7.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-04",
            "references": [
                "https://doi.org/10.1093/toxsci/kfx153"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Concentrations of Indicator Organisms",
            "description": "It is a compilation of organism concentrations of 16 sampling events conducted between July 2015 and February 2016. It also includes statistical analysis such as mean, standard deviation, etc.  also, probability graphs are included. \n\nThis dataset is associated with the following publication:\nSelvakumar, A., and T. OConnor. Organism Detection in Permeable Pavement Parking Lot Infiltrates at the Edison Environmental Center, NJ.   WATER ENVIRONMENT RESEARCH. Water Environment Federation, Alexandria, VA, USA, 90(1): 21-29, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1390165",
            "keyword": [
                "indicator organisms",
                "porous asphalt",
                "pervious concrete",
                "stormwater runoff"
            ],
            "contactPoint": {
                "fn": "Ariamalar Selvakumar",
                "hasEmail": "mailto:selvakumar.ariamalar@epa.gov"
            },
            "distribution": [
                {
                    "title": "Raw data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390165/Raw%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-05",
            "references": [
                "https://doi.org/10.2175/106143017x14902968254575"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Deposition, critical loads, and exceedances for 1800-2025",
            "description": "This data includes gridded estimates of: (1) decadally averaged total N and S deposition for the conterminous US from 1800-2025, (2) critical loads from the National Critical Loads Database, and (3) exceedances  of critical loads from atmospheric deposition of N and/or S. \n\nThis dataset is associated with the following publication:\nClark, C., J. Phelan, P. Doraiswamy, J. Buckley, J. Cajka, R. Dennis , J. Lynch, C. Nolte, and T. Spero. Atmospheric Deposition and Exceedances of Critical Loads from 1800-2025 for the Coterminous United States.   BULLETIN OF THE ECOLOGICAL SOCIETY OF AMERICA. Ecological Society of America, Ithaca, NY, USA,  978-1002, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407569",
            "keyword": [
                "nitrogen",
                "nitrogen deposition",
                "critical loads",
                "sulfur",
                "acid rain",
                "sulfur deposition",
                "NAAQS",
                "biodiversity",
                "terrestrial ecosystems",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Christopher Clark",
                "hasEmail": "mailto:clark.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "T017_Data_for_EPA.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407569/T017_Data_for_EPA.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-06-28",
            "references": [
                "https://doi.org/10.1002/eap.1703"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1407569/documents/EPA_T017_data_dictionary_062317_CMC.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Oxidative C-H activation of amines using protuberant lychee-like goethite",
            "description": "Goethite with protuberant lychee morphology has been synthesized that accomplishes C-H activation of N-methylanilines to generate \u03b1-aminonitriles; the catalyst takes oxygen from air and uses it as a co-oxidant in the process. \n\nThis dataset is associated with the following publication:\nVerma, S., R.B.N. Baig, R. Varma, and M. Nadagouda. Oxidative C-H activation of amines using protuberant lychee-like goethite.   Nature Communications. Nature Publishing Group, London,  UK, 8: 2024, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1389556",
            "keyword": [
                "Oxidative C-H activation",
                "amines",
                "protuberant lychee-like goethite",
                "\u03b1-aminonitriles"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "Supporting information.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1389556/Supporting%20information.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-06-10",
            "references": [
                "https://doi.org/10.1038/s41598-018-20246-y",
                "https://pasteur.epa.gov/uploads/10.23719/1389556/documents/Supporting%20information.docx"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1389556/documents/Supporting%20information.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Genetic Targets of Acute Toluene Inhalation in Drosophila melanogaster: DGRP activity, overlapping human orthologs, pathway analyses, GWAS results  ",
            "description": "We used the Drosophila Genetics Reference Panel (DGRP), a collection of ~200 homozygous lines of fruit flies whose genomes have been sequenced. We quantified toluene-induced suppression of motor activity in 123 lines of these flies during exposure to toluene, a volatile organic compound known to induce narcosis in mammals via its effects on neuronal ion channels. We then applied genome-wide association analyses on this effect of toluene using the DGRP web portal (http://dgrp2.gnets.ncsu.edu), which identified polymorphisms in candidate genes associated with the variation in response to toluene exposure. We tested ~2 million variants and found 82 polymorphisms located in or near 66 candidate genes that were associated with phenotypic variation for sensitivity to toluene at P < 5 x 10-5, and human orthologs for 52 of these candidate Drosophila genes. None of these orthologs are known to be involved in canonical pathways for mammalian neuronal ion channels, including GABA, glutamate, dopamine, glycine, serotonin, and voltage sensitive calcium channels. \n\nThis dataset is associated with the following publications:\nBushnell, P., W. Ward, T. Morozova, W. Oshiro, M. Lin, R. Judson, S. Hester, J. Mckee, and M. Higuchi. Editor's Highlight: Genetic Targets of Acute Toluene Inhalation in Drosophila melanogaster.   TOXICOLOGICAL SCIENCES. Society of Toxicology,     230-239, (2017).\nTatum-Gibbs, K.R., J. Mckee , M. Higuchi , and P. Bushnell. Effects of Toluene, Acrolein and Vinyl Chloride on Motor Activity of Drosophila Melanogaster.   NEUROTOXICOLOGY AND TERATOLOGY. Elsevier Science Ltd, New York, NY, USA, 47: 114-24, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1419253",
            "keyword": [
                "fruit fly",
                "toluene",
                "motor activity",
                "DGRP",
                "fly genome",
                "volatile organic compound"
            ],
            "contactPoint": {
                "fn": "David Herr",
                "hasEmail": "mailto:herr.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "HerrDavid_A-qnkv_DATA_20171221.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1419253/HerrDavid_A-qnkv_DATA_20171221.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-02-02",
            "references": [
                "https://doi.org/10.1093/toxsci/kfw243"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Suspect Screening and Non-Targeted Analysis of Drinking Water Using Point-Of-Use Filters",
            "description": "This dataset contains information about all the features extracted from the raw data files, the formulas that were assigned to some of these features, and the candidate compounds that correspond to those formulas. Data sources, bioactivity, exposure estimates, functional uses, and predicted and observed retention times are available for all candidate compounds. \n\nThis dataset is associated with the following publication:\nNewton, S., R. McMahen, J. Sobus, K. Mansouri, A. Williams, A. McEachran, and M. Strynar. Suspect Screening and Non-Targeted Analysis of Drinking Water Using Point-Of-Use Filters.   ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 234: 297-306, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1394771",
            "keyword": [
                "drinking water",
                "exposome",
                "suspect screening",
                "non-target analysis",
                "high resolution mass spectrometry"
            ],
            "contactPoint": {
                "fn": "Seth Newton",
                "hasEmail": "mailto:newton.seth@epa.gov"
            },
            "distribution": [
                {
                    "title": "Newton Brita Dr Water Data 6-8-17.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394771/Newton%20Brita%20Dr%20Water%20Data%206-8-17.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-08",
            "references": [
                "https://doi.org/10.1016/j.envpol.2017.11.033"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Adverse outcome pathway",
            "description": "cell culture information with toxicity and proteomic changes. \n\nThis dataset is associated with the following publication:\nVanEmon, J., P. Pan, and F. Van Breukelen. Effects of chlorpyrifos and trichloropyridinol on HEK 293 human embryonic kidney cells.   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 191: 537-547, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407506",
            "keyword": [
                "adverse outcome pathway",
                "apoptosis",
                "CPF",
                "chlorpyrifos",
                "interleukin",
                "TCP",
                "human embryonic kidney cells",
                "biomarker of exposure"
            ],
            "contactPoint": {
                "fn": "Jeanette Van Emon",
                "hasEmail": "mailto:vanemon.jeanette@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure S1 (002).pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407506/Figure%20S1%20%28002%29.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2016-07-12",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2017.10.039"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Manitowoc R UVDOC data 2011",
            "description": "Manitowoc R UVDOC data 2011. \n\nThis dataset is associated with the following publication:\nWilliamson, C., S. Madronich, A. Lal, R. Zepp, R. Lucas, E. Overholt, K. Rose, S.G. Schladow, and J. Lee-Taylor. Altmetric: 165More detail\r\nArticle | OPEN\r\n\r\nClimate change-induced increases in precipitation are reducing the potential for solar ultraviolet radiation to inactivate pathogens in surface waters.   Scientific Reports. Nature Publishing Group, London,  UK, 7: 13033, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407676",
            "keyword": [
                "climate change",
                "Lake Michigan",
                "pathogens",
                "surface waters",
                "waterborne pathogens"
            ],
            "contactPoint": {
                "fn": "Richard Zepp",
                "hasEmail": "mailto:zepp.richard@epa.gov"
            },
            "distribution": [
                {
                    "title": "Manitowoc R UVDOC Data 2011.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407676/Manitowoc%20R%20UVDOC%20Data%202011.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2011-09-02",
            "references": [
                "https://doi.org/10.1038/s41598-017-13392-2"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "EPA Nanorelease Dataset",
            "description": "EPA Nanorelease Dataset. \n\nThis dataset is associated with the following publication:\nWohlleben, W., C. Kingston, J. Carter, E. Sahle-Demessie, S. Vazquez-Campos, B. Acrey, C. Chen, E. Walton, H. Egenolf, P. Muller, and R. Zepp. NanoRelease: Pilot interlaboratory comparison of a weathering protocol applied to resilient and labile polymers with and without embedded carbon nanotubes.   CARBON. Pergamon Press Ltd., New York, NY, USA, 113: 346-360, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407652",
            "keyword": [
                "carbon nanotubes",
                "inter-laboratory comparision",
                "lab prototcol",
                "mwcnt"
            ],
            "contactPoint": {
                "fn": "Richard Zepp",
                "hasEmail": "mailto:zepp.richard@epa.gov"
            },
            "distribution": [
                {
                    "title": "EPA NanoRelease Data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407652/EPA%20NanoRelease%20Data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-09-08",
            "references": [
                "https://doi.org/10.1016/j.carbon.2016.11.011"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "data for aromatase 3D qsar modeling",
            "description": "computational chemistry data (very complex; need to be an expert to understand and use. \n\nThis dataset is associated with the following publication:\nLee, S., and M. Barron. 3D-QSAR Study of Steroidal and Azaheterocyclic Human Aromatase Inhibitors using Quantitative Profile of Protein-Ligand Interactions.   Journal of Cheminformatics. Springer, New York, NY, USA, 10(2): 1-13, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1394789",
            "keyword": [
                "Aromatase inhibitor",
                "adverse outcome pathway",
                "3D-QSAR",
                "steroid",
                "azaheterocycle",
                "hydrophobic contact",
                "nitrogen-heme-iron coordination",
                "dual descriptor"
            ],
            "contactPoint": {
                "fn": "Mace Barron",
                "hasEmail": "mailto:barron.mace@epa.gov"
            },
            "distribution": [
                {
                    "title": "data for Figures 2 3 6 7 Aromatase_steroid_result.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394789/data%20for%20Figures%202%203%206%207%20Aromatase_steroid_result.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "data for Figures 2 3 6 7 Aromatase_steroidAza_result.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394789/data%20for%20Figures%202%203%206%207%20Aromatase_steroidAza_result.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "data for Fig 3 Coordination Descriptors.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394789/data%20for%20Fig%203%20Coordination%20Descriptors.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "supplemental material data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394789/supplemental%20material%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table 2 and 3 data Machine Learning Result.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394789/Table%202%20and%203%20data%20Machine%20Learning%20Result.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-22",
            "references": [
                "https://doi.org/10.1186/s13321-017-0253-8"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Mutagenic atmospheres resulting from the photooxidation of aromatic hydrocarbon and NOx mixtures",
            "description": "Although many volatile organic compounds (VOCs) are regulated to limit air pollution and the consequent health effects, the photooxidation products generally are not. Thus, we examined the mutagenicity in Salmonella TA100 of photochemical atmospheres generated in a steady-state atmospheric simulation chamber by irradiating mixtures of single aromatic VOCs, NOx, and ammonium sulfate seed aerosol in air. The 10 VOCs examined were benzene; toluene; ethylbenzene; o-, m-, and p-xylene; 1,2,4- and 1,3,5-trimethylbenzene; m-cresol; and naphthalene. Salmonella were exposed at the air-agar interface to the generated atmospheres for 1, 2, 4, 8, or 16 h. Dark-control exposures produced non-mutagenic atmospheres, illustrating that the gas-phase precursor VOCs were not mutagenic at the concentrations tested. Under irradiation, all but m-cresol and naphthalene produced mutagenic atmospheres, with potencies ranging from 2.0 (p-xylene) to 10.4 (ethylbenzene) revertants m3 mgC-1 h-1. The mutagenicity was due exclusively to direct-acting late-generation products of the photooxidation reactions. Gas-phase chemical analysis showed that a number of oxidized organic chemical species enhanced during the irradiated exposure experiments correlated (r \u2265 0.81) with the mutagenic potencies of the atmospheres. Molecular formulas assigned to these species indicated that they likely contained peroxy acid, aldehyde, alcohol, and other functionalities. \n\nThis dataset is associated with the following publication:\nRiedel, T., D. DeMarini, S. Warren, E. Corse, J. Offenberg, T. Kleindienst, M. Lewandowski, and J. Zavala. Mutagenic atmospheres resulting from the photooxidation of aromatic hydrocarbon and NOx mixtures.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 178: 164-172, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1417737",
            "keyword": [
                "Mutagenicity",
                "Salmonella TA100",
                "Aromatic compounds",
                "air quality",
                "Secondary Organic Aerosol",
                "air toxics",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Michael Lewandowski",
                "hasEmail": "mailto:lewandowski.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Riedel mutagenicity Figures.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1417737/Riedel%20mutagenicity%20Figures.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-01-24",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2018.01.052"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Eastern Redcedar Seedling Assessment",
            "description": "Eastern redcedar tree seedling growth in response to various soil, nitrogen, and photosynthetic radiation characteristics. \n\nThis dataset is associated with the following publication:\nGanguli, A., D. Engle, P. Mayer , and L. Salo. Influence of resource availability on Juniperus virginiana expansion in a forest\u2013prairie ecotone.   Ecosphere. ESA Journals,    7(8): e01433, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407551",
            "keyword": [
                "cross timbers",
                "eastern redcedar",
                "invasion",
                "seedlings",
                "soil texture",
                "tallgrass prairie",
                "upland oak forest",
                "cross timbers; eastern redcedar; invasion; seedlings; soil texture; tallgrass prairie; upland oak forest;"
            ],
            "contactPoint": {
                "fn": "Paul Mayer",
                "hasEmail": "mailto:mayer.paul@epa.gov"
            },
            "distribution": [
                {
                    "title": "ERC_SeedlingAssessments.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407551/ERC_SeedlingAssessments.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2003-12-31",
            "references": [
                "https://doi.org/10.1002/ecs2.1433"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1407551/documents/ERC_SeedlingAssessments%20data%20dictionary.xls.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Size-selective performance evaluation of candidate aerosol inlets using polydisperse aerosols",
            "description": "Presented are detailed techniques for the generation, collection, and analysis of polydisperse calibration aerosols for wind tunnel evaluation of size-selective aerosol samplers. \n\nThis dataset is associated with the following publication:\nDart, A., J. Krug, C. Witherspoon, J. Gilberry, Q. Malloy, S. Kaushik, and R. Vanderpool. Development of polydisperse aerosol generation and measurement procedures for wind tunnel evaluation of size-selective aerosol samplers.   AEROSOL SCIENCE AND TECHNOLOGY. Taylor & Francis, Inc., Philadelphia, PA, USA, 52(9): 957-970, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1413966",
            "keyword": [
                "Polydisperse",
                "wind tunnel",
                "samplers",
                "particulate",
                "sampling",
                "Aerosol"
            ],
            "contactPoint": {
                "fn": "Robert Vanderpool",
                "hasEmail": "mailto:vanderpool.robert@epa.gov"
            },
            "distribution": [
                {
                    "title": "Polydisperse_Aerosol_ScienceHub_Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413966/Polydisperse_Aerosol_ScienceHub_Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "S1-SOP for Generation of Polydisperse Aerosols.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413966/S1-SOP%20for%20Generation%20of%20Polydisperse%20Aerosols.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "S2-SOP for Collection and Extraction of Polydisperse Aerosols.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413966/S2-SOP%20for%20Collection%20and%20Extraction%20of%20Polydisperse%20Aerosols.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "S3-SOP for Polydisperse Aerosol Size Distribution Determination.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413966/S3-SOP%20for%20Polydisperse%20Aerosol%20Size%20Distribution%20Determination.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2017-12-27",
            "references": [
                "https://doi.org/10.1080/02786826.2018.1469728"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1413966/documents/Polydisperse_Aerosol_ScienceHub_Data.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Barron et al. \"Photoenhanced toxicity of weathered crude oil in sediment and water to larval zebrafish\" submitted to the Bulletin of Environmental Contamination and Toxicology",
            "description": "The dataset contains fish mortality associated with various treatment of oil and dispersants in water accommodated fractions and sediment. The dataset also contains analytical chemistry associated with each experimental treatment. \n\nThis dataset is associated with the following publications:\nBarron, M. Photoenhanced Toxicity of Petroleum to Aquatic Invertebrates and Fish.   ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY. Springer, New York, NY, USA, 73(1): 40-46, (2017).\nBarron, M., J. Kryzwa, C. Lilavois, and S. Raimondo. Photoenhanced toxicity of weathered crude oil in sediment and water to larval zebrafish.   BULLETIN OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY. Springer, New York, NY, USA, 100(1): 49-53, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1393828",
            "keyword": [
                "mortality",
                "oil",
                "zebrafish",
                "phototenhanced toxicity",
                "dispersants"
            ],
            "contactPoint": {
                "fn": "Sandra Raimondo",
                "hasEmail": "mailto:raimondo.sandy@epa.gov"
            },
            "distribution": [
                {
                    "title": "Barron et al phototox data_Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393828/Barron%20et%20al%20phototox%20data_Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-05",
            "references": [
                "https://doi.org/10.1007/s00244-016-0360-y",
                "https://doi.org/10.1007/s00128-017-2228-x"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cali2014data",
            "description": "meteorology from onsite sonic at Woodside and distributions of observed concentrations from GMAP mobile monitoring at Woodside. \n\nThis dataset is associated with the following publication:\nIsakov, V., A. Venkatram, R. Baldauf, P. Deshmukh, and M. Zhang. Evaluation and development of tools to quantify the impacts of roadside vegetation barriers on near-road air quality..   INTERNATIONAL JOURNAL OF ENVIRONMENT AND POLLUTION. Inderscience Enterprises Limited, Geneva,  SWITZERLAND, 62(2): 127-135, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1390110",
            "keyword": [
                "mobile monitoring",
                "Roadways",
                "Barriers",
                "vegetation",
                "Dispersion",
                "Models"
            ],
            "contactPoint": {
                "fn": "Vladilen Isakov",
                "hasEmail": "mailto:isakov.vlad@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cali2014data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390110/Cali2014data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-01-25",
            "references": [
                "https://doi.org/10.1504/ijep.2017.10010370"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figure 4, Cropland Reallocation",
            "description": "This is a netCDF formatted data file.  All data values are reported as grid cell area percent (%).  Since all simulation grid cells are of uniform area.  Reallocation in terms of hectares can be computed as (variable _value*14400).  Data values may be displayed spatially using any number of viewers including VERDI which is open source software that can be downloaded free of charge from http://www.cmascenter.com.\nEach data file contains 29 data layers for each of 30 reallocation variables (crops).  We assume there is no irrigated CRP land area (variable 30).  Each variable value represents the simulation grid cell area that is reallocated from one crop (data layer) to that variable. \n\nThis dataset is associated with the following publication:\nCooter, E., R. Dodder, J. Bash, A. Elobeid, L. Ran, V. Benson, and D. Yuan. Exploring a United States Maize Cellulose Biofuel Scenario Using an Integrated Energy and Agricultural Markets Solution Approach.   Annals of Agricultural & Crop Sciences. Austin Publishing Group, Jersey City, NJ, USA, 2(2): 1031, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1418266",
            "keyword": [
                "integrated multimedia systems modeling",
                "air quality",
                "land quality",
                "water quality",
                "scenarios",
                "national",
                "Mississippi River Basin",
                "Northern Gulf of Mexico",
                "Hypoxia",
                "EPIC",
                "CMAQ",
                "MARKAL"
            ],
            "contactPoint": {
                "fn": "Ellen Cooter",
                "hasEmail": "mailto:cooter.ellen@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure4.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1418266/Figure4.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-01-29",
            "references": [
                "http://austinpublishinggroup.com/agriculture-crop-sciences/fulltext/aacs-v2-id1031.php"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1418266/documents/Cropland%20Reallocation%20metadata.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Effects of an Environmentally-relevant Mixture of Pyrethroid Insecticides on Spontaneous Activity in Primary Cortical Networks on Microelectrode Arrays",
            "description": "This manuscript tests the hypothesis of dose additivity of an environmental mixture of pyrethriod insecticides at the level of network function, in vitro. The results demonstrate that permethrin, deltamethrin, esfenvalerate, cypermethrin and beta-cyfluthrin all change the activity of networks as measured by microelectrode arrays, and that the effects of an environmental-relevant mixture of these 5 compounds can be predicted based on a dose-additivity model.\nThese results are consistent with results from in vivo experiments that examined motor activity. This study supports the Office of Pesticides decision to regulate mixtures of pyrethroids based on dose additivity. \n\nThis dataset is associated with the following publication:\nJohnstone , A., J. Strickland, K. Crofton , C. Gennings, and T. Shafer. Effects of an Environmentally-relevant Mixture of Pyrethroid Insecticides on Spontaneous Activity in Primary Cortical Networks on Microelectrode Arrays.   NEUROTOXICOLOGY. Elsevier B.V., Amsterdam,  NETHERLANDS, 60(16): 234-239, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390091",
            "keyword": [
                "Dose-additivity",
                "Microelectrode array",
                "Mixtures",
                "neurotoxicity",
                "pyrethroids",
                "in vitro"
            ],
            "contactPoint": {
                "fn": "Timothy Shafer",
                "hasEmail": "mailto:shafer.tim@epa.gov"
            },
            "distribution": [
                {
                    "title": "ShaferTimothy_SciHub Dataset for pyrethroid mixture.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390091/ShaferTimothy_SciHub%20Dataset%20for%20pyrethroid%20mixture.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-09-09",
            "references": [
                "https://doi.org/10.1016/j.neuro.2016.05.005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Aerial energetic residue data from JBER C4 testing",
            "description": "Aerially-collected energetic residues from surface detonation of C4. \n\nThis dataset is associated with the following publication:\nWalsh, M., B. Gullett, M. Walsh, M. Bigl, and J. Aurell. Improving post-detonation energetics residues estimations for the Life Cycle Environmental Assessment process for munitions..   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 194: 622-627, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1375324",
            "keyword": [
                "C4",
                "Life Cycle Environmental Assessment",
                "munitions",
                "energetics",
                "detonation residues",
                "combustion products",
                "fine particles",
                "emission factors"
            ],
            "contactPoint": {
                "fn": "Brian Gullett",
                "hasEmail": "mailto:gullett.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data Table Science Hub JBER 06 06 2017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375324/Data%20Table%20Science%20Hub%20JBER%2006%2006%202017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-06",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2017.11.072"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Datasets Supporting Paper Titled, \u201cInfluence of Network Model Detail on the Performance of Designs of Contamination Warning Systems\u201d",
            "description": "This ZIP file contains the four EPANET network models used for one of the two water distribution system (WDS) network models (N1) analyzed in the paper titled: \n\n\u201cThe effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies\u201d.\n\nThe EPANET network models provided here are for the network model named \u201cN1\u201d in this paper. \n\nThis dataset is associated with the following publication:\nJanke , R., and M. Davis. The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies.   Drinking Water Engineering and Science Discussions. Copernicus Gesellschaft mbH, Gottingen,  GERMANY,  1-25, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1390111",
            "keyword": [
                "EPANET network models",
                "TEVA-SPOT ensemble and regret analysis",
                "WATER DISTRIBUTION SYSTEMS; OPTIMIZATION; SIMULATION;",
                "water quality",
                "drinking water distribution systems",
                "community health",
                "public health"
            ],
            "contactPoint": {
                "fn": "Robert Janke",
                "hasEmail": "mailto:janke.robert@epa.gov"
            },
            "distribution": [
                {
                    "title": "A-2ngi_N1_EPANET_Models.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390111/A-2ngi_N1_EPANET_Models.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-10-13",
            "references": [
                "https://doi.org/10.5194/dwes-2017-39"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "EPIC Forest LAI Dataset: LAI estimates generated from the USDA Environmental Policy Impact Climate (EPIC) model (a widely used, field-scale, biogeochemical model) on four forest complexes spanning three physiographic provinces in VA and NC.",
            "description": "This data depicts calculated and validated LAI estimates generated from the USDA Environmental Policy Impact Climate (EPIC) model (a widely used, field-scale, biogeochemical model) on four forest complexes spanning three physiographic\nprovinces in Virginia and North Carolina. Measurements of forest composition (species and number), LAI, tree diameter, basal area, and canopy height were recorded at each site during the 2002 field season. Calibrated EPIC results show stand-level temporally resolved LAI estimates with R2 values ranging from 0.69 to 0.96, and stand maximum height estimates within 20% of observation. \n\nThis dataset is associated with the following publication:\nIiames, J., E. Cooter, D. Schwede, and J. Williams. A Comparison of Simulated and Field-Derived Leaf Area Index (LAI) and Canopy Height Values from Four Forest Complexes in the Southeastern USA.   Forests. MDPI AG, Basel,  SWITZERLAND, 9(1): 26, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1418159",
            "keyword": [
                "LAI",
                "Southeastern USA",
                "EPIC",
                "mixed forest",
                "unmanaged",
                "nitrogen deposition",
                "atmospheric flux"
            ],
            "contactPoint": {
                "fn": "Ellen Cooter",
                "hasEmail": "mailto:cooter.ellen@epa.gov"
            },
            "distribution": [
                {
                    "title": "ExcelData.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1418159/ExcelData.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "forests-09-00026 (1).pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1418159/forests-09-00026%20%281%29.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "https://www.mdpi.com/journal/forests/special_issues/LAI_remotesensing",
                    "accessURL": "https://www.mdpi.com/journal/forests/special_issues/LAI_remotesensing"
                }
            ],
            "modified": "2018-01-26",
            "references": [
                "https://doi.org/10.3390/f9010026"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figures6&7_Tables2&3",
            "description": "This file contains three netCDF formatted files containing simulation model results used to produce Figures 6 and 7 and tables 3 and 4.  These data can be accessed using a variety of open source software tools, e.g., NCDUMP and R as well as graphical display software such as R and VERDI (http://www.cmascenter.org). \n\nThis dataset is associated with the following publication:\nCooter, E., R. Dodder, J. Bash, A. Elobeid, L. Ran, V. Benson, and D. Yuan. Exploring a United States Maize Cellulose Biofuel Scenario Using an Integrated Energy and Agricultural Markets Solution Approach.   Annals of Agricultural & Crop Sciences. Austin Publishing Group, Jersey City, NJ, USA, 2(2): 1031, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1418437",
            "keyword": [
                "integrated multimedia systems modeling",
                "air quality",
                "land quality",
                "water quality",
                "scenarios",
                "national",
                "Mississippi River Basin",
                "Northern Gulf of Mexico",
                "Hypoxia",
                "EPIC",
                "CMAQ",
                "MARKAL"
            ],
            "contactPoint": {
                "fn": "Ellen Cooter",
                "hasEmail": "mailto:cooter.ellen@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figures6&7_Tables2&3.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1418437/Figures6%267_Tables2%263.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-01-29",
            "references": [
                "http://austinpublishinggroup.com/agriculture-crop-sciences/fulltext/aacs-v2-id1031.php"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1418437/documents/EPIC_metadata.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figure 5, Biofuel refinery facility locations",
            "description": "This workbook contains the locations and types of current and anticipated biofuel feedstock processing facilities assumed under the simulated scenarios. \n\nThis dataset is associated with the following publication:\nCooter, E., R. Dodder, J. Bash, A. Elobeid, L. Ran, V. Benson, and D. Yuan. Exploring a United States Maize Cellulose Biofuel Scenario Using an Integrated Energy and Agricultural Markets Solution Approach.   Annals of Agricultural & Crop Sciences. Austin Publishing Group, Jersey City, NJ, USA, 2(2): 1031, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1418436",
            "keyword": [
                "integrated multimedia systems modeling",
                "air quality",
                "land quality",
                "water quality",
                "scenarios",
                "national",
                "Mississippi River Basin",
                "Northern Gulf of Mexico",
                "Hypoxia",
                "EPIC",
                "CMAQ",
                "MARKAL"
            ],
            "contactPoint": {
                "fn": "Ellen Cooter",
                "hasEmail": "mailto:cooter.ellen@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure_5_facility_locations.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1418436/Figure_5_facility_locations.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-01-30",
            "references": [
                "http://austinpublishinggroup.com/agriculture-crop-sciences/fulltext/aacs-v2-id1031.php"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Table 1:  Biofuels simulation scenarios",
            "description": "A spreadsheet containing information used to generate Table 1.  Agricultural Market sector results presented in the spreadsheet were generated elsewhere (non-EPA) and have been published previously.  Their generation is not part of this Science Hub project.  Documentation and Metadata supporting these data are provided in the Table 1 file and in the link provided in the supporting documents section. \n\nThis dataset is associated with the following publication:\nCooter, E., R. Dodder, J. Bash, A. Elobeid, L. Ran, V. Benson, and D. Yuan. Exploring a United States Maize Cellulose Biofuel Scenario Using an Integrated Energy and Agricultural Markets Solution Approach.   Annals of Agricultural & Crop Sciences. Austin Publishing Group, Jersey City, NJ, USA, 2(2): 1031, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1418434",
            "keyword": [
                "integrated multimedia systems modeling",
                "air quality",
                "land quality",
                "water quality",
                "scenarios",
                "national",
                "Mississippi River Basin",
                "Northern Gulf of Mexico",
                "Hypoxia",
                "EPIC",
                "CMAQ",
                "MARKAL"
            ],
            "contactPoint": {
                "fn": "Ellen Cooter",
                "hasEmail": "mailto:cooter.ellen@epa.gov"
            },
            "distribution": [
                {
                    "title": "Table_1.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1418434/Table_1.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-01-30",
            "references": [
                "http://austinpublishinggroup.com/agriculture-crop-sciences/fulltext/aacs-v2-id1031.php",
                "https://www.sciencedirect.com/science/article/pii/S136481521300128X?via%3Dihub"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "MARGA_Chen et al_2016",
            "description": "These data describe the chromatography characteristics of the MARGA instrument software as compared to an alternative, independent technique for chromatogram processing, including an assessment of accuracy, precision and method detection limit. \n\nThis dataset is associated with the following publication:\nChen, X., J. Walker, and C. Geron. Chromatography related performance of the Monitor for Aerosols and Gases in Ambient Air (MARGA): laboratory and field based evaluation.   Atmospheric Measurement Techniques. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 10(3893): 3908, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390105",
            "keyword": [
                "MARGA",
                "online ion chromatography",
                "inorganic PM",
                "nitrogen",
                "sulfur",
                "deposition",
                "bidirectional flux",
                "micrometeorology"
            ],
            "contactPoint": {
                "fn": "John Walker",
                "hasEmail": "mailto:walker.johnt@epa.gov"
            },
            "distribution": [
                {
                    "title": "MARGA_Chen et al_2016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390105/MARGA_Chen%20et%20al_2016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-12-21",
            "references": [
                "https://doi.org/10.5194/amt-10-3893-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Buse_Francisella and free-living amoebae data sets",
            "description": "Co-infection data in the form of colony forming units and amoeba cell counts. \n\nThis dataset is associated with the following publication:\nBuse , H., F. Schaefer, and G. Rice. Enhanced survival but not amplification of Francisella spp. in the presence of free-living amoebae.   Acta Microbiologica et Immunologica Hungarica. Akademiai Kiado, Budapest,  HUNGARY, 64(1): 17-36, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407522",
            "keyword": [
                "legionella",
                "amoeba",
                "Francisella",
                "co-cultures",
                "Acanthamoeba",
                "Vermamoeba",
                "endosymbiont",
                "environmental persistence",
                "host",
                "parasite"
            ],
            "contactPoint": {
                "fn": "Helen Buse",
                "hasEmail": "mailto:buse.helen@epa.gov"
            },
            "distribution": [
                {
                    "title": "Buse_Ft FLA txt data set.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407522/Buse_Ft%20FLA%20txt%20data%20set.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-09-17",
            "references": [
                "https://doi.org/10.1556/030.63.2016.015"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Radford McAlester flight paths",
            "description": "Heights and position of UAS from starting point. \n\nThis dataset is associated with the following publication:\nAurell, J., B. Mitchell, V. Chirayath, J. Jonsson, D. Tabor, and B. Gullett. Field determination of multipollutant, open area combustion source emission factors with a hexacopter unmanned aerial vehicle.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 166(11): 433-440, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1376669",
            "keyword": [
                "emissions",
                "hexacopter",
                "combustion",
                "plume",
                "sensor",
                "sampler",
                "unmanned aerials system"
            ],
            "contactPoint": {
                "fn": "Brian Gullett",
                "hasEmail": "mailto:gullett.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data Table Science Hub UAS Kolibri paper 04 11 2017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376669/Data%20Table%20Science%20Hub%20UAS%20Kolibri%20paper%2004%2011%202017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-11",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2017.07.046"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Regional Marginal Abatement Cost Curves for NOx",
            "description": "Data underlying the figures included in the manuscript \"Marginal abatement cost curve for NOx incorporating controls, renewable electricity, energy efficiency and fuel switching\". Data include national and regional Marginal Abatement Cost Curves. \n\nThis dataset is associated with the following publication:\nLoughlin, D., A. Macpherson, K. Kaufman, and B. Keaveny. Marginal abatement cost curve for NOx incorporating controls, renewable electricity,  energy efficiency and fuel switching.   JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION. Air & Waste Management Association, Pittsburgh, PA, USA, 67(10): 1115-1125, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1371943",
            "keyword": [
                "MACC",
                "NOx",
                "renewable electricity",
                "energy efficiency",
                "fuel switching",
                "natural gas",
                "Energy systems modeling",
                "MARKAL",
                "nested sensitivity analysis",
                "electricity generation",
                "coal",
                "emission projections",
                "scenario analysis",
                "air quality",
                "climate change"
            ],
            "contactPoint": {
                "fn": "Daniel Loughlin",
                "hasEmail": "mailto:loughlin.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "figure_data_MACC_v5_051617.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371943/figure_data_MACC_v5_051617.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-01-31",
            "references": [
                "https://doi.org/10.1080/10962247.2017.1342715"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Estimating Intermittent Individual Spawning Behavior via Disaggregating Group Data ",
            "description": "In order to understand fish biology and reproduction it is important to know the fecundity patterns of individual fish, as frequently established by recording the output of mixed-sex groups of fish in a laboratory setting. However, for understanding individual reproductive health and modeling purposes it is important to estimate individual fecundity from group fecundity. A multi-stage method was developed that disaggregates group level data into estimates for individual-level clutch size and spawning interval distributions. The disaggregation technique was verified by combining data from fathead minnow pairs, and checking that the disaggregation method reproduced the original clutch sizes and spawning intervals. \n\nThis dataset is associated with the following publication:\nNishimura, J., R. Smith, K. Jensen, G. Ankley, and K. Watanabe. Estimating intermittent individual spawning behavior via disaggregating group data.   BULLETIN OF MATHEMATICAL BIOLOGY. Elsevier Science Ltd, New York, NY, USA, 80(3): 687-700, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1393857",
            "keyword": [
                "disaggregation",
                "maximum likelihood",
                "deconvolution",
                "inverse problems",
                "endocrine disruption",
                "fish",
                "reproduction",
                "mode of action (MOA)",
                "fathead minnow"
            ],
            "contactPoint": {
                "fn": "Gerald Ankley",
                "hasEmail": "mailto:ankley.gerald@epa.gov"
            },
            "distribution": [
                {
                    "title": "AnkleyGerald_A-9327_Dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393857/AnkleyGerald_A-9327_Dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-06",
            "references": [
                "https://doi.org/10.1007/s11538-017-0379-x"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Estimating environmental co-benefits of U.S. low-carbon pathways using the GCAM-USA integrated assessment model ",
            "description": "There are many technological pathways that can lead to reduced carbon dioxide (CO2) emissions.  However, these pathways can have substantially different impacts on other environmental endpoints, such as air quality and energy-related water demand. This study uses an integrated assessment model with state-level resolution of the U.S. energy system to compare environmental impacts of alternative low-carbon pathways. One set of pathways emphasizes nuclear energy and carbon capture and storage (NUC/CCS), while another set emphasizes renewable energy (RE). These are compared with pathways in which all technologies are available. Air pollutant emissions, mortality costs attributable to particulate matter less than 2.5 microns in diameter (PM2.5), and energy-related water demands are evaluated for 50% and 80% CO2 reduction targets in the U.S. in 2050. The RE low-carbon pathways require less water withdrawal and consumption than the NUC/CCS pathways because of the large cooling demands of nuclear power and CCS. However, the NUC/CCS low-carbon pathways produce greater health benefits, mainly because the NUC/CCS assumptions result in less primary PM2.5 emissions from residential wood combustion. Environmental co-benefits differ among states because of factors such as existing technology stock, resource availability, and environmental and energy policies. An important finding is that biomass in the building sector can offset some of the health co-benefits of the low-carbon pathways even though it plays only a minor role in reducing CO2 emissions. \nThis dataset consists of source code, input data, and processed outputs for Ou et al. (2018), published in Applied Energy. \n\nThis dataset is associated with the following publication:\nOu, Y., W. Shi, S.J. Smith, C.M. Ledna, J.J. West, C. Nolte, and D. Loughlin. Estimating environmental co-benefits of U.S. low-carbon pathways using an integrated assessment model with state-level resolution.   Applied Energy. Elsevier B.V., Amsterdam,  NETHERLANDS, 216: 482-493, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1418337",
            "keyword": [
                "emissions",
                "air quality",
                "GCAM-USA",
                "integrated assessment modeling"
            ],
            "contactPoint": {
                "fn": "Christopher Nolte",
                "hasEmail": "mailto:nolte.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Ou et al. dataset.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1418337/Ou%20et%20al.%20dataset.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-02-14",
            "references": [
                "https://doi.org/10.1016/j.apenergy.2018.02.122"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Seahorse Manuscript Data Set ",
            "description": "Metadata for figures presented in manuscript reporting bioenergetic effects of exposure to environmentally relevant organic compound in human airway epithelial cells. \n\nThis dataset is associated with the following publication:\nLavrich, K., E. Corteselli, P. Wages, P. Bromberg, S. Simmons, E. Gibbs-Flournoy, and J. Samet. Investigating Mitochondrial Dysfunction in Human Lung Cells Exposed to Redox-Active PM Components.   TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 342: 99-107, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1394616",
            "keyword": [
                "Extracelular flux analyses",
                "Mitochondria",
                "quinones",
                "airway epithelial cells"
            ],
            "contactPoint": {
                "fn": "James Samet",
                "hasEmail": "mailto:samet.james@epa.gov"
            },
            "distribution": [
                {
                    "title": "Seahorse Manuscript Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394616/Seahorse%20Manuscript%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-08",
            "references": [
                "https://doi.org/10.1016/j.taap.2018.01.024"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The reduction of summer sulfate and switch from summer to winter PM2.5 concentration maxima in the U.S.",
            "description": "These four files each contain 24-hour PM2.5 concentrations collected between 2000-2015. \n\nThis dataset is associated with the following publication:\nChan, E., B. Gantt, and S. McDow. The reduction of summer sulfate and switch from summertime to wintertime PM2.5 concentration maxima in the United States.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 175: 25-32, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:062"
            ],
            "identifier": "https://doi.org/10.23719/1390150",
            "keyword": [
                "air quality",
                "Fine Particulate Matter",
                "pm2.5",
                "sulfate",
                "nitrate",
                "organic carbon"
            ],
            "contactPoint": {
                "fn": "Stephen McDow",
                "hasEmail": "mailto:mcdow.stephen@epa.gov"
            },
            "distribution": [
                {
                    "title": "daily_site_level_PM2.5_2000_2015_science_hub.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390150/daily_site_level_PM2.5_2000_2015_science_hub.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "daily_site_level_sulfate_2000_2015_science_hub.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390150/daily_site_level_sulfate_2000_2015_science_hub.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "daily_site_level_nitrate_2000_2015_science_hub.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390150/daily_site_level_nitrate_2000_2015_science_hub.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "daily_site_level_OC_2000_2015_science_hub.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390150/daily_site_level_OC_2000_2015_science_hub.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-05-16",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2017.11.055"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1390150/documents/Data%20Dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Global Mercury Observatory System Land-based Monitoring Data Portal",
            "description": "Global Mercury Observation System On-line Data Portal. This dataset is not publicly accessible because: Data was unable to be uploaded in ScienceHub but can be obtained through contact with the researcher specified below. It can be accessed through the following means: Contacts\r\nFor more information on GMOS and its activities, please contact:\r\n\r\nProgramme Coordinator\r\n\r\nDr. Nicola Pirrone\r\nCNR-Institute of Atmospheric Pollution Research, Rome, Italy\r\nE-mail: pirrone@iia.cnr.it\r\n\r\nPhone: +39.0984.493239, Fax: +39.0984.493215 (at Division of Rende)\r\nPhone: +39.06.90672803 / 2831, Fax: +39.06.90672472 (at the Institute Headquarters in Rome). Format: Monitoring data is generated from Tekran continuous mercury monitoring instruments (hourly) at globally distributed sites. \n\nThis dataset is associated with the following publications:\nCarbone, F., A. Bruno, A. Naccarato, F. De Simone, C. Gencarelli, F. Sprovieri, I.M. Hedgecock, M. Landis, H. Shov, K.A. Pfaffhuber, K.A. Read, L. Martin, H. Angot, A. Dommergue, O. Magand, and N. Pirrone. The Superstatistical Nature and Interoccurrence Time of Atmospheric Mercury Concentration Fluctuations.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 123(2): 764-774, (2018).\nDe Simone, F., P. Artaxo, M. Bencardino, S. Cinnirella, F. Carbone, F. D'Amore, A. Dommergue, X. Bin Feng, C. Gencarelli, I. Hedgecock, M. Landis, F. Sprovieri, N. Suzuki, I. Wangberg, and N. Pirrone. Particulate-phase mercury emissions from biomass burning and impact on resulting deposition: a modelling assessment.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 17: 1881-1899, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license-non-epa-generated.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1419007",
            "keyword": [
                "Probability density function",
                "Tsallis q-statistics",
                "Global atmospheric turbulence"
            ],
            "contactPoint": {
                "fn": "Matthew Landis",
                "hasEmail": "mailto:landis.matthew@epa.gov"
            },
            "distribution": [],
            "modified": "2017-12-31",
            "references": [
                "https://doi.org/10.1002/2017jd027384",
                "https://doi.org/10.5194/acp-17-1881-2017",
                "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6260940",
                "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6070161"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "sample data Red River_2011-2013",
            "description": "OK Fish Kill data from Red River 2011-2013. \n\nThis dataset is associated with the following publication:\nJones-Lepp, T., V. Taguchi, W. Sovocool, D. Betowski, P. DeArmond, B. Schumacher, W. Winnik, R. McMillin, and C. Armstrong. Novel contaminants identified in fish kills in the Red River watershed, 2011\u20132013.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(2): 336-344, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1377033",
            "keyword": [
                "fish kills",
                "mass spectrometry",
                "non-target analysis"
            ],
            "contactPoint": {
                "fn": "Tammy Jones-Lepp",
                "hasEmail": "mailto:jones-lepp.tammy@epa.gov"
            },
            "distribution": [
                {
                    "title": "metals data correlations 081117.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377033/metals%20data%20correlations%20081117.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "sample data Red River Region 6 081817.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377033/sample%20data%20Red%20River%20Region%206%20081817.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-18",
            "references": [
                "https://doi.org/10.1002/etc.3989"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Mutagenicity of Simulated Atmospheres",
            "description": "The data are the number of colonies per Petri plate for all the experiments.  The colonies are mutants and are also called revertants (rev)--because the Salmonella mutagenicity assay is a \"reverse mutation\" assay.  The data show the number of colonies (rev) per Petri plate for each experiment for each hour of exposure (1, 2, 4, 8, or 16 hours). \n\nThis dataset is associated with the following publication:\nZavala-Mendez, J., J. Krug, S. Warren, T. Krantz, C. King, J. Mckee, S. Gavett, M. Lewandowski, W. Lonneman, T. Kleindienst, M. Meier, M. Higuchi, M.I. Gilmour, and D. DeMarini. Evaluation of an Air Quality Health Index for Predicting the Mutagenicity of Simulated Atmospheres.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(5): 3045\u20133053, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1393584",
            "keyword": [
                "Mutagenicity",
                "Salmonella",
                "air pollution",
                "Smog",
                "mutation spectra",
                "Ozone",
                "PM"
            ],
            "contactPoint": {
                "fn": "David Demarini",
                "hasEmail": "mailto:demarini.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science Hub Smog Chamber SA-PM and SA-O3 Data Set.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393584/Science%20Hub%20Smog%20Chamber%20SA-PM%20and%20SA-O3%20Data%20Set.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-04-19",
            "references": [
                "https://doi.org/10.1021/acs.est.8b00613"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Southeast Atmosphere Studies: learning from model-observation syntheses",
            "description": "Observed and modeled data shown in figure 2b-c. \n\nThis dataset is associated with the following publication:\nMao, J., A. Carlton, R. Cohen, W. Brune, S. Brown, G. Wolfe, J. Jimenez, H. Pye, N.L. Ng, L. Xu, V.F. McNeill, K. Tsigaridis, B. McDonald, C. Warneke, A. Guenther, M. Alvarado, J. de Gouw, L. Mickley, E. Liebensperger, R. Mathur, C. Nolte, R. Portmann, N. Unger, M. Tosca, and L. Horowitz. Southeast Atmosphere Studies: learning from model-observation syntheses.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 18: 2615-2651, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407538",
            "keyword": [
                "SOAS",
                "SAS",
                "Southeastern USA",
                "SOA",
                "Ozone",
                "CMAQ",
                "Aerosol"
            ],
            "contactPoint": {
                "fn": "Havala Pye",
                "hasEmail": "mailto:pye.havala@epa.gov"
            },
            "distribution": [
                {
                    "title": "maoetal.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407538/maoetal.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "https://esrl.noaa.gov/csd/groups/csd7/measurements/2013senex/",
                    "accessURL": "https://esrl.noaa.gov/csd/groups/csd7/measurements/2013senex/"
                }
            ],
            "modified": "2017-02-16",
            "references": [
                "https://doi.org/10.5194/acp-18-2615-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Enhancements to AERMOD\u2019s Building Downwash Algorithms based on Wind-Tunnel and Embedded-LES Modeling -BDW-2",
            "description": "This data set is associated with the results found in the journal article: Monbureau et al, 2018. Enjancements to AERMOD's building downwash algorithms based on wind-tunnel and Embedded-LES modeling. Atmospheric Environment, https://doi.org/10.1016/j.atmosenv.2018.02.022. \nThe goal of this study is to improve AERMOD's ability to accurately model important and complex building downwash scenarios by incorporating knowledge gained from a recently completed series of wind tunnel studies and complementary large eddy simulations of flow and dispersion around simple structures for a variety of building dimensions, stack locations, stack heights, and wind angles. This study presents three modifications to the building downwash algorithm in AERMOD that improve the physical basis and internal consistency of the model, and one modification to AERMOD's building pre-processor to better represent elongated buildings in oblique winds. These modifications are demonstrated to improve the ability of AERMOD to model observed ground-level concentrations in the vicinity of a building for the variety of conditions examined in the wind tunnel and numerical studies. \n\nThis dataset is associated with the following publication:\nMonbureau, E., D. Heist, S. Perry, L. Brouwer, H. Foroutan , and W. Tang. Enhancements to AERMOD's building downwash algorithms based on wind-tunnel and Embedded-LES modeling.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 179: 321-330, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1424691",
            "keyword": [
                "dispersion modeling",
                "building downwash",
                "wind tunnel",
                "CFD"
            ],
            "contactPoint": {
                "fn": "David Heist",
                "hasEmail": "mailto:heist.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "HeistDavid_A-v42c_DatafilesBDW-2-20170807.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1424691/HeistDavid_A-v42c_DatafilesBDW-2-20170807.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-03-08",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2018.02.022"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1424691/documents/HeistDavid_A-v42c_DataDictionary-BDW-2_20170807.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Metal concentrations from permeable pavement parking lot in Edison, NJ",
            "description": "The U.S. Environmental Protection Agency constructed a 4000-m2 parking lot in Edison, New Jersey in 2009. The parking lot is surfaced with three permeable pavements [permeable interlocking concrete pavers (PICP), pervious concrete (PC), and porous asphalt (PA)]. Samples of each permeable pavement infiltrate, surface runoff from traditional asphalt (CC), and rainwater (RW) were analyzed in duplicate for 22 metals (including Al, As, Ba, Be, Ca, Cd, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Pb, Sb, Si, Sn, Sr, V, and Zn) in both total and dissolved phases for 6 years (Jan. 2010 - Oct. 2015). \n\nThis dataset is associated with the following publication:\nLiu, J., and M. Borst. Performances of Metal Concentrations from Three Permeable Pavement Infiltrates.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 136: 41-53, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1392578",
            "keyword": [
                "Censored data",
                "stormwater",
                "permeable pavement",
                "metal concentration"
            ],
            "contactPoint": {
                "fn": "Michael Borst",
                "hasEmail": "mailto:borst.mike@epa.gov"
            },
            "distribution": [
                {
                    "title": "EPLM_large.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1392578/EPLM_large.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-30",
            "references": [
                "https://doi.org/10.1016/j.watres.2018.02.050"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "QCL N2O data final MayAugust2016",
            "description": "The dataset consists of daily measurements of N2O, N2O isotopic abundance and site preference, and CO2 flux. Data are presented as a daily averages of 10 second data, obtained over a 46 day period. \n\nThis dataset is associated with the following publication:\nYuan, Y., H. Chen, W. Yuan, D. Williams, J. Walker, and w. Shi. Is biochar-manure co-compost a better solution for soil health improvement and N2O emissions mitigation?.   BIOGEOCHEMISTRY. Springer, New York, NY, USA, 113: 14-25, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1412705",
            "keyword": [
                "biochar",
                "nitrous oxide",
                "isotopomer",
                "quantum cascade laser"
            ],
            "contactPoint": {
                "fn": "David Williams",
                "hasEmail": "mailto:williams.davidj@epa.gov"
            },
            "distribution": [
                {
                    "title": "N2O chamber data.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1412705/N2O%20chamber%20data.txt",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2016-09-30",
            "references": [
                "https://doi.org/10.1016/j.soilbio.2017.05.025"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1412705/documents/data%20dictionary%20N2O%20chamber%20data.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Snohomish Estuary nutrient enhanced coastal acidification pH time series and grab samples",
            "description": "High-resolution (15-minute frequency) monitoring of pH, dissolved oxygen, salinity, temperature, depth, and chlorophyll was conducted from July 15-October 1, 2015 in a shallow, subtidal seagrass bed in Puget Sound, WA, USA.  Grab samples for instrument validation and carbonate chemistry analysis were periodically taken next to the in-situ instrumentation. \n\nThis dataset is associated with the following publication:\nPacella, S., C. Brown, G. Waldbusser, R. Labiosa, and B. Hales. Seagrass habitat metabolism increases short-term extremes and long-term offset of CO2 under future ocean acidification.   PNAS  (PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES). National Academy of Sciences, WASHINGTON, DC, USA, 115(15): 3870-3875, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407616",
            "keyword": [
                "Ocean acidification",
                "coastal acidification",
                "seagrasses",
                "carbonate chemistry"
            ],
            "contactPoint": {
                "fn": "Stephen Pacella",
                "hasEmail": "mailto:pacella.stephen@epa.gov"
            },
            "distribution": [
                {
                    "title": "PNAS_sciencehub_Pacella.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407616/PNAS_sciencehub_Pacella.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-30",
            "references": [
                "https://doi.org/10.1073/pnas.1703445115"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Carbonate chemistry, water quality, coral measurements",
            "description": "Carbonate chemistry parameters (pH, total alkalinity, and pCO2), water quality parameters (Temperature, salinity, Ca, Mg, PO4, NH3 and NO3)  as well as all coral measurements (buoyant weight, tissue surface area, surface area density, calcification rate, tissue growth rate, and percent change in surface area density) taken over the three month exposure. \n\nThis dataset is associated with the following publication:\nEnzor, L., C. Hankins, D. Vivian, W. Fisher, and M. Barron. Calcification continues in Caribbean reef-building corals at high pCO2 levels in a recirculating ocean acidification exposure system.   JOURNAL OF EXPERIMENTAL MARINE BIOLOGY AND ECOLOGY. Elsevier Science Ltd, New York, NY, USA, 499: 9-16, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1411864",
            "keyword": [
                "Recirculating System",
                "Ocean acidification",
                "Caribbean coral",
                "elevated pCO2",
                "calcification"
            ],
            "contactPoint": {
                "fn": "Laura Enzor",
                "hasEmail": "mailto:enzor.laura@epa.gov"
            },
            "distribution": [
                {
                    "title": "Carbonate Chemistry, water quality and coral measurements, 3-15-18.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1411864/Carbonate%20Chemistry%2C%20water%20quality%20and%20coral%20measurements%2C%203-15-18.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-25",
            "references": [
                "https://doi.org/10.1016/j.jembe.2017.12.008"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1411864/documents/Data%20dictionary%2C%203-15-18.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Ecohydrological Index, Native Fish, and Climate Trends and Relationships in the Kansas River Basin_dataset",
            "description": "The dataset is an excel file that contain data for the figures in the manuscript. \n\nThis dataset is associated with the following publication:\nSinnathamby, S., K. Douglas-Mankin, M. Muche, S. Hutchison, and A. Anandhi. Ecohydrological index, native fish, and climate trends and relationships in the Kansas River basin.   ECOHYDROLOGY. Wiley Interscience, Malden, MA, USA, 11(1): e1909, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390136",
            "keyword": [
                "Hydrologic indices",
                "Trend analysis",
                "Ecohydrology",
                "Hydrologic change impacts",
                "Plains Minnow",
                "Common Shiner"
            ],
            "contactPoint": {
                "fn": "Muluken Muche",
                "hasEmail": "mailto:muche.muluken@epa.gov"
            },
            "distribution": [
                {
                    "title": "MucheMuluken_Ecohydrology_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390136/MucheMuluken_Ecohydrology_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-01",
            "references": [
                "https://doi.org/10.1002/eco.1909"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1390136/documents/MucheMuluken_Ecohydrology_Data_Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "People and Water \u2013 IWI-HWBI",
            "description": "The dataset contains the coverages used in the analysis including such things as shp files. \n\nThis dataset is associated with the following publication:\nScown, M., J. Flotemersch, T. Spanbauer, T. Eason, A. Garmestani, and B. Chaffin. People and water: Exploring the social-ecological condition of watersheds of the United States.   Elementa: Science of the Anthropocene. University of California Press (UC Press), Oakland, CA, USA, 5(64): 1-12, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407589",
            "keyword": [
                "ecosystem services",
                "human well-being",
                "social-ecological systems",
                "sustainability",
                "watersheds",
                "governance"
            ],
            "contactPoint": {
                "fn": "Joseph Flotemersch",
                "hasEmail": "mailto:flotemersch.joseph@epa.gov"
            },
            "distribution": [
                {
                    "title": "People and Water \u2013 IWI-HWBI Data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407589/People%20and%20Water%20%E2%80%93%20IWI-HWBI%20Data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-09-30",
            "references": [
                "https://doi.org/10.1525/elementa.189"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Emissions from Prescribed Burning of Agricultural Fields in the Pacific Northwest",
            "description": "PM2.5, volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), and polychlorinated dibenzodioxins/dibenzofurans (PCDDs/PCDFs), and continuous measurements of black carbon (BC), particle mass by size, CO, CO2, CH4, and aerosol characteristics. \n\nThis dataset is associated with the following publication:\nHolder, A., B. Gullett, S. Urbanski, R. Elleman, S. O'Neil, D. Tabor, B. Mitchell, and K. Baker. Emissions from Prescribed Burning of Agricultural Fields in the Pacific Northwest.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 166: 22-33, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390145",
            "keyword": [
                "agricultural burning",
                "emission factors",
                "wheat",
                "bluegrass",
                "particulate matter",
                "organics"
            ],
            "contactPoint": {
                "fn": "Brian Gullett",
                "hasEmail": "mailto:gullett.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data Table Science Hub WA ID 01 26 2017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390145/Data%20Table%20Science%20Hub%20WA%20ID%2001%2026%202017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-01-27",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2017.06.043"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Predicting_Systemic_Toxicity_Effects_ArchTox_2017_Data",
            "description": "In an effort to address a major challenge in chemical safety assessment, alternative approaches for characterizing systemic effect levels, a predictive model was developed. Systemic effect levels were curated from ToxRefDB, HESS-DB and COSMOS-DB from numerous study types totaling 4382 in vivo studies for 1201 chemicals. Observed systemic effects in mammalian models are a complex function of chemical dynamics, kinetics, and inter- and intra-individual variability. In order to address the complexity problem, systemic effect levels were modeled at the study-level by leveraging study covariates (e.g., study type, strain, administration route) in addition to multiple descriptor sets, including chemical (ToxPrint, PaDEL, and Physchem), biological (ToxCast), and kinetic descriptors. Using Random Forest modeling with cross-validation and external validation procedures, study-level covariates alone accounted for approximately 20% of the variance reducing the root mean squared error (RMSE) from 0.96 log10 mg/kg/day to 0.85 log10 mg/kg/day, providing a baseline performance metric (lower expectation of model performance). A consensus model developed using a combination of study-level covariates, chemical, biological, and kinetic descriptors explained a total of 38% of the variance with an RMSE of 0.76 log10 mg/kg/day. A benchmark model (upper expectation of model performance) was also developed with an RMSE of 0.5 log10 mg/kg/day by incorporating study-level covariates and the mean effect level per chemical. To achieve a representative chemical-level prediction, the minimum study-level predicted and observed effect level per chemical were compared reducing the RMSE from 1.1 to 0.8 log10 mg/kg/day. Although biological descriptors did not improve model performance, the final model was enriched for biological descriptors that indicated xenobiotic metabolism gene expression, oxidative stress, and cytotoxicity, demonstrating the importance of accounting for kinetics and non-specific bioactivity in predicting systemic effect levels. Herein, we have generated an externally predictive model of systemic effect levels for use as a safety assessment tool and have generated forward predictions for thousands of chemicals. \n\nThis dataset is associated with the following publication:\nTruong, L., G. Ouedraogo, L. Pham, J. Clouzeau, S. Loisel-Joubert, D. Blanchet, H. No\u00e7airi, W. Setzer, R. Judson, C. Grulke, K. Mansouri, and M. Martin. (Archives of Toxicology) Predicting In Vivo Effect Levels for Repeat Dose Systemic Toxicity using Chemical, Biological, Kinetic and Study Covariates.   Archives of Toxicology. Springer, New York, NY, USA, 92(2): 587-600, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407006",
            "keyword": [
                "ToxRefDB",
                "ToxCast",
                "Predictive Toxicity",
                "Systemic Effects",
                "Effect Levels",
                "ACToR"
            ],
            "contactPoint": {
                "fn": "Richard Judson",
                "hasEmail": "mailto:judson.richard@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/MartinMatt/Systemic_Toxicity_Model/",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/MartinMatt/Systemic_Toxicity_Model/"
                }
            ],
            "modified": "2017-03-08",
            "references": [
                "https://doi.org/10.1007/s00204-017-2067-x"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Full Scale Drinking Water System Decontamination at the Water Security Test Bed",
            "description": "The EPA\u2019s Water Security Test Bed (WSTB) facility is a full-scale representation of a drinking water distribution system.  In collaboration with the Idaho National Laboratory (INL), EPA designed the WSTB facility to support full-scale evaluations of water infrastructure decontamination, real-time sensors, mobile water treatment systems, and decontamination of premise plumbing and appliances.  The EPA research focused on decontamination of 1) Bacillus globigii (BG) spores, a non-pathogenic surrogate for Bacillus anthracis and 2) Bakken crude oil.  Flushing and chlorination effectively removed most BG spores from the bulk water but BG spores still remained on the pipe wall coupons. Soluble oil components of Bakken crude oil were removed by flushing although oil components persisted in the dishwasher and refrigerator water dispenser.  Using this full-scale distribution system allows EPA to 1) test contaminants without any human health or ecological risk and 2) inform water systems on effective methodologies responding to possible contamination incidents. \n\nThis dataset is associated with the following publication:\nSzabo, J., J. Hall, S. Reese, J. Goodrich, S. Panguluri, G. Meiners, and H. Ernst. Full Scale Drinking Water System Decontamination at the Water Security Test Bed.   JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA,  E535-E547, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1390162",
            "keyword": [
                "Decontamination",
                "Drinking water distribution system",
                "Bacillus",
                "oil spill",
                "bacterial spores",
                "drinking water"
            ],
            "contactPoint": {
                "fn": "Jeffrey Szabo",
                "hasEmail": "mailto:szabo.jeff@epa.gov"
            },
            "distribution": [
                {
                    "title": "INL data 12052014 ScienceHub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390162/INL%20data%2012052014%20ScienceHub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "INL September 2015 Oil Decon ScienceHub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390162/INL%20September%202015%20Oil%20Decon%20ScienceHub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "INL August 2016 oil - BG test ScienceHub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390162/INL%20August%202016%20oil%20-%20BG%20test%20ScienceHub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-17",
            "references": [
                "https://doi.org/10.5942/jawwa.2017.109.0141"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Aerosol direct effects on ozone - China case study",
            "description": "Model output from the 2-way coupled WRF-CMAQ modeling system applied to China. This dataset is not publicly accessible because: EPA scientists helped with the model set-up and data analysis. The data was created by collaborators at Tsinghua University and is housed there. Since its not EPA generated data, the dataset is not included in ScienceHub. It can be accessed through the following means: The data can be accessed by contacting the corresponding author Prof. Shuxiao Wang (email: shxwang@tsinghua.edu.cn; phone: +86-10-62771466; fax: +86-10-62773650). Format: The data analyzed in this study were created by collaborators at Tsinghua University, China. The data can be accessed by contacting the corresponding author Prof. Shuxiao Wang (email: shxwang@tsinghua.edu.cn; phone: +86-10-62771466; fax: +86-10-62773650). \n\nThis dataset is associated with the following publication:\nXing, J., J. Wang, R. Mathur, S. Wang, G. Sarwar, J. Pleim, C. Hogrefe, Y. Zhang, J. Jiang, D. Wong, and J. Hao. Impacts of aerosol direct effects on tropospheric ozone through changes in atmospheric dynamics and photolysis rates.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 17: 9869-9883, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407541",
            "keyword": [
                "CMAQ",
                "air pollution",
                "aerosol direct radiative effects"
            ],
            "contactPoint": {
                "fn": "Rohit Mathur",
                "hasEmail": "mailto:mathur.rohit@epa.gov"
            },
            "distribution": [],
            "modified": "2017-03-06",
            "references": [
                "https://doi.org/10.5194/acp-17-9869-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data_files_Reyes_EHP_phthalates",
            "description": "The file contains three files in comma separated values (.csv) format. \r\n\u201cReyes_EHP_Phthalates_US_metabolites.csv\u201d contains information about the National Health and Nutrition Examination Survey (NHANES) metabolite code names along with Tolerable Daily Intake (TDI), molecular weight of the parent phthalate, molecular weight of the metabolite, and names and abbreviations of the corresponding metabolites and phthalates. \r\n\r\n\u201cReyes_EHP_Phthalates_US_MCR.csv\u201d contains the following information:\r\n\u2022\tData on the surveyed individuals from the original NHANES data files that includes\r\n\u2022\tIdentifying information for individual;\r\n\u2022\tDemographic information used in defining the creatinine levels and in investigating sub populations based on age, gender, ethnicity;\r\n\u2022\tConcentration of phthalate metabolites and creatinine in urine.\r\n\u2022\tCalculated values for each individual;\r\n\u2022\tDaily intake of each of the six phthalate;\r\n\u2022\tHazard Quotients associated with each phthalate\u2019s daily intake;\r\n\u2022\tValues of Hazard Index and the Maximum Cumulative Ratio.       \r\n\r\n\u201cReyes_EHP_Phthalates_US_MCR_definitions.csv\u201d and the definitions and units of the fields in \u201cReyes_EHP_Phthalates_US_MCR.csv\u201d. \n\nThis dataset is associated with the following publication:\nReyes, J., and P. Price. An analysis of cumulative risks based on biomonitoring data for six phthalates using the Maximum Cumulative Ratio.   ENVIRONMENT INTERNATIONAL. Elsevier B.V., Amsterdam,  NETHERLANDS, 112: 77-84, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407557",
            "keyword": [
                "urine concentrations",
                "calculated doses",
                "hazard quotients",
                "hazard indices",
                "Maximum Cumulative Ratios",
                "Phthalates",
                "cumulative risk assessment",
                "biomonitoring"
            ],
            "contactPoint": {
                "fn": "Paul Price",
                "hasEmail": "mailto:price.pauls@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data_files_Reyes_EHP_phthalates.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407557/Data_files_Reyes_EHP_phthalates.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-05-15",
            "references": [
                "https://doi.org/10.1016/j.envint.2017.12.008"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Compilations of measured and calculated physicochemical property values for PCBs, PBDEs, PCDDs and PAHs",
            "description": "The dataset consists of compilations of measured and calculated physicochemical property values for PCBs, PBDEs, PCDDs and PAHs.  The properties included in this dataset are the octanol-water partition coefficient, melting point, vapor pressure and water solubility.  The measured property values were obtained from a critical review of the scientific literature.  The calculated values were obtained using the following applications: ACD/Percepta, ChemAxon Plugin Calculators, EPI Suite, NICEATM, Online Chemical Modeling Environment (OCHEM), OPERA, SPARC, and Toxicity Estimation Software Tool (T.E.S.T.). \n\nThis dataset is associated with the following publication:\nStevens, C., J. Patel, M. Koopmans, J. Olmstead, S. Hilal, N. Pope, E. Weber, and K. Wolfe. Demonstration of a consensus approach for the calculation of physicochemical properties required for environmental fate assessments.   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 194: 94-106, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1412936",
            "keyword": [
                "PCBs",
                "PBDEs",
                "PCDDs",
                "PAHs",
                "Kow",
                "melting point",
                "vapor pressure",
                "water solubility",
                "physicochemical property",
                "qsar",
                "predictive models",
                "cheminformatics"
            ],
            "contactPoint": {
                "fn": "Caroline Stevens",
                "hasEmail": "mailto:stevens.caroline@epa.gov"
            },
            "distribution": [
                {
                    "title": "PCBsPBDEsPCDDsPAHs_PhysChemProp_LitValues.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1412936/PCBsPBDEsPCDDsPAHs_PhysChemProp_LitValues.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "PCBsPBDEsPCDDsPAHs_PhysChemProp_CalculatedValues.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1412936/PCBsPBDEsPCDDsPAHs_PhysChemProp_CalculatedValues.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-12-13",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2017.11.137"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Tools to Minimize Inter-Laboratory Variability in Vitellogenin Gene Expression Monitoring Programs",
            "description": "All data files are in excel format. Files with names CSU are different mesocosms qPCR data results for vitellogen gene and 18s a house keeping gene. Data files labelled ORD are qPCR data generated by NERL Cincinnati.  Those labeled R5 are qPCR data generated by EPA\u2019s Region 5 lab and RMI_Mass are qPCR data generated by the University of Massachusetts Amherst. \n\nThis dataset is associated with the following publication:\nJastrow , A., D. Gordon , K. Auger, E. Punska, K. Arcaro, K. Keteles , D. Winkleman, D. Lattier , A. Biales , and J. Lazorchak. Tools to minimize interlaboratory variability in vitellogenin gene expression monitoring programs.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 36(11): 3102-3107, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1393387",
            "keyword": [
                "Same as science hub research effort",
                "real-time PCR",
                "fathead minnow",
                "bioassay",
                "estrogen",
                "wastewater",
                "inter-laboratory variability"
            ],
            "contactPoint": {
                "fn": "James Lazorchak",
                "hasEmail": "mailto:lazorchak.jim@epa.gov"
            },
            "distribution": [
                {
                    "title": "Recalculation.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393387/Recalculation.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-01-09",
            "references": [
                "https://doi.org/10.1002/etc.3885"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Zhao et al. (2017) Chem. Geol. v. 474 p.1",
            "description": "The dataset provides information on chromium concentrations extracted from rock samples collected at the Garfield SF site in New Jersey (USA). The data are discussed in Zhao et al. (2017). Chemical Geology, v. 474, p. 1-8. \n\nThis dataset is associated with the following publication:\nZhao, J., T. Al, S. Chapman, B. Parker, K. Mishkin, D. Cutt, and R. Wilkin. Determination of Cr(III) solids formed by reduction of Cr(VI) in a contaminated fractured bedrock aquifer: evidence for natural attenuation of Cr(VI).   CHEMICAL GEOLOGY. Elsevier Science Ltd, New York, NY, USA, 474: 1-8, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1409665",
            "keyword": [
                "groundwater",
                "chromium",
                "arsenic",
                "nickel",
                "iron sulfides",
                "uranium"
            ],
            "contactPoint": {
                "fn": "Richard Wilkin",
                "hasEmail": "mailto:wilkin.rick@epa.gov"
            },
            "distribution": [
                {
                    "title": "Zhao et al. (2017) Chem. Geol. v. 474 p. 1.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1409665/Zhao%20et%20al.%20%282017%29%20Chem.%20Geol.%20v.%20474%20p.%201.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-11-21",
            "references": [
                "https://doi.org/10.1016/j.chemgeo.2017.10.004"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Deiodinase 1 Screening of ToxCast Phase 1 Chemical Library",
            "description": "This excel spreadsheet contains the resultant data for over from inhibition assays with human Deiodinase 1 screened against the ToxCast Phase 1 chemical library and a few additional chemicals.  Over 1800 chemicals were tested in total. It contains the list of chemicals tested and the median, minimum, and maximum inhibition for each chemical screened at 200 \u00b5M.  Chemicals that gave greater than 50% inhibition were screened in concentration response mode, and the median, min, max inhibition at each concentration for those chemicals are included.  Propylthiouracil was used in each plate as a positive control and the concentration-response data for those curves are also included. \n\nThis dataset is associated with the following publication:\nHornung, M., J. Korte, J. Olker, J. Denny, C. Knutsen, P. Hartig, M. Cardon, and S. Degitz. Screening the ToxCast Phase 1 chemical library for inhibition of deiodinase type 1 activity.   TOXICOLOGICAL SCIENCES. Society of Toxicology,    162(2): 570-581, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1376911",
            "keyword": [
                "in vitro",
                "thyroid hormone",
                "Chemical Screening",
                "deiodinase"
            ],
            "contactPoint": {
                "fn": "Michael Hornung",
                "hasEmail": "mailto:hornung.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "20170817_DIO1_Phase1_InHouse.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376911/20170817_DIO1_Phase1_InHouse.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-16",
            "references": [
                "https://doi.org/10.1093/toxsci/kfx279"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A Database of Historical Benthic Invertebrate Biodiversity Spanning 182 Years in Narragansett Bay (Rhode Island and Massachusetts)_Data_ v1",
            "description": "To examine biodiversity trends over time, a master list was compiled of all benthic invertebrate species collected from the Narragansett Bay beginning with Totten\u2019s 1834 descriptions of mollusks, Leidy\u2019s collections in 1855, Verrill and Smith\u2019s surveys beginning in 1871, and studies at Alexander Agassiz\u2019s Newport Marine Zoological Laboratory, 1873\u20131910. The list, spanning 182 years, was compiled from 104 sources and includes invertebrate macrofauna (>0.5 mm) and more limited studies of meiofauna. It currently holds over 1,200 unique taxa from 21 phyla. Information given for each collection record includes: current accepted scientific name, when and where sampled, by whom (with citation), gear used, and full taxonomic hierarchy. \n\nThis dataset is associated with the following publication:\nHale, S., M. Hughes, and H. Buffum. Historical Trends of Benthic Invertebrate Biodiversity Spanning 182 Years in a Southern New England Estuary.   Estuaries and Coasts. Estuarine Research Federation, Port Republic, MD, USA, 41(6): 1525\u20131538, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1429305",
            "keyword": [
                "Marine benthic invertebrates",
                "biodiversity",
                "Taxonomic distinctness",
                "Historical trends",
                "Narragansett Bay"
            ],
            "contactPoint": {
                "fn": "Stephen Hale",
                "hasEmail": "mailto:hale.stephen@epa.gov"
            },
            "distribution": [
                {
                    "title": "HaleStephen_A-j3vh_Data_20180322.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1429305/HaleStephen_A-j3vh_Data_20180322.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-03-22",
            "references": [
                "https://doi.org/10.1007/s12237-018-0378-7",
                "https://pasteur.epa.gov/uploads/10.23719/1429305/documents/HaleStephen_A-j3vh__DataDescriptionReport_20180323.pdf"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Verification, validation, and field testing the USEPA National Stormwater Calculator",
            "description": "We used this dataset to verify and validate functions in the USEPA National Stormwater Calculator, and then applied field data and commonly-available datasets to illustrate calibration techniques and uncertainty evaluation. \n\nThis dataset is associated with the following publication:\nSchifman, L., M. Tryby, J. Berner, and W. Shuster. Managing Uncertainty in Runoff Estimation with the U.S. Environmental Protection Agency National Stormwater Calculator..   JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION. American Water Resources Association, Middleburg, VA, USA, 54(1): 148-159, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1394115",
            "keyword": [
                "infiltration",
                "stormwater management",
                "urban hydrology",
                "Green Infrastructure",
                "low impact development",
                "Urban Planning"
            ],
            "contactPoint": {
                "fn": "William Shuster",
                "hasEmail": "mailto:shuster.william@epa.gov"
            },
            "distribution": [
                {
                    "title": "Schifman_NSWC_ScienceHub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394115/Schifman_NSWC_ScienceHub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-05",
            "references": [
                "https://doi.org/10.1111/1752-1688.12599"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Foy Lake paleodiatom data",
            "description": "Percent abundance of 109 diatom species collected from a Foy Lake (Montana, USA) sediment core that was sampled every \u223c5\u201320 years, yielding a \u223c7 kyr record over 800 time-steps. \n\nThis dataset is associated with the following publication:\nAngeler, D., T. Eason, A. Garmestani, T. Spanbauer, and C. Allen. Assessing cross-scale patterns and the composition of ecological communities of alternative lake regimes.   PLoS ONE. Public Library of Science, San Francisco, CA, USA,  01, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1396045",
            "keyword": [
                "Foy Lake",
                "Montana",
                "diatoms",
                "resilience",
                "leading indicators",
                "governance",
                "environmental change",
                "complex systems",
                "law and policy"
            ],
            "contactPoint": {
                "fn": "Tarsha Eason",
                "hasEmail": "mailto:eason.tarsha@epa.gov"
            },
            "distribution": [
                {
                    "title": "Foy Lake (Paleodiatom data).xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1396045/Foy%20Lake%20%28Paleodiatom%20data%29.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-06-26",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Figures and Tables in \"Impacts of Different Characterizations of Large-Scale Background on Simulated Regional-Scale Ozone Over the Continental U.S.\"",
            "description": "This dataset contains the data used in the Figures and Tables of the manuscript \"Impacts of Different Characterizations of Large-Scale Background on Simulated Regional-Scale Ozone Over the Continental U.S.\". \n\nThis dataset is associated with the following publication:\nHogrefe, C., P. Liu, G. Pouliot, R. Mathur, S. Roselle, J. Flemming, M. Lin, and R. Park. Impacts of different characterizations of large-scale background on simulated regional-scale ozone over the continental United States.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 18: 3839-3864, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1418975",
            "keyword": [
                "Air Quality Model Evaluation International Initiative (AQMEII)",
                "boundary conditions",
                "process analysis",
                "column ozone burdens"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "HogrefeEtAl_Data_Figures_Tables.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1418975/HogrefeEtAl_Data_Figures_Tables.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-01-19",
            "references": [
                "https://doi.org/10.5194/acp-18-3839-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1418975/documents/DataDictionary_HogrefeEtAl_A-dr86.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "raw data collected from Malvern Instrument",
            "description": "These are raw data/image files from the Malvern Zetasizer Instrument. \n\nThis dataset is associated with the following publication:\nBuse, H., J. Hoelle, C. Muhlen, and D. Lytle. Electrophoretic mobility of Legionella pneumophila serogroups 1 to 14.   FEMS MICROBIOLOGY LETTERS. Elsevier Science Ltd, New York, NY, USA,  1, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1419478",
            "keyword": [
                "opportunistic pathogen",
                "Legionella pneumophila",
                "biofilm colonization",
                "drinking water",
                "surface charge"
            ],
            "contactPoint": {
                "fn": "Helen Buse",
                "hasEmail": "mailto:buse.helen@epa.gov"
            },
            "distribution": [
                {
                    "title": "sg1 pH effect on EPM.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1419478/sg1%20pH%20effect%20on%20EPM.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "sg4 pH effect on EPM.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1419478/sg4%20pH%20effect%20on%20EPM.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "EPM.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1419478/EPM.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2018-02-05",
            "references": [
                "https://doi.org/10.1093/femsle/fny067"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Photocatalytic C-H Activation and Oxidative Esterification Using Pd@g-C3N4",
            "description": "Graphitic carbon nitride supported palladium nanoparticles, Pd@g-C3N4, have been synthesized and utilized for the direct oxidative esterification of alcohols using atmospheric oxygen as a co-oxidant via photocatalytic C-H activation. \n\nThis dataset is associated with the following publication:\nVerma, S., R.B.N. Baig, R. Varma, and M. Nadagouda. Photocatalytic CH activation and oxidative esterification using Pd@g-C3N4.   ACS Sustainable Chemistry & Engineering. American Chemical Society, Washington, DC, USA, 309: 248-252, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1389547",
            "keyword": [
                "C-H Activation",
                "Heterogeneous catalysis",
                "Oxidative esterification",
                "Alcohols",
                "Visible light"
            ],
            "contactPoint": {
                "fn": "Rajender Varma",
                "hasEmail": "mailto:varma.rajender@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.sciencedirect.com/science/article/pii/S0920586117304480?via%3Dihub",
                    "accessURL": "https://www.sciencedirect.com/science/article/pii/S0920586117304480?via%3Dihub"
                }
            ],
            "modified": "2017-06-13",
            "references": [
                "https://doi.org/10.1016/j.cattod.2017.06.009",
                "https://pasteur.epa.gov/uploads/10.23719/1389547/documents/CATTOD-D-17-00099_Supporting%20Information.docx"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Revised risk-based indices and proposed new composite watershed health measure and application thereof to the Upper Mississippi River Watershed, Ohio River Basin, and Maumee River Basin  ",
            "description": "The dataset includes names and geographic coordinates of gauge stations where flow and water quality (sediment, nitrogen, phosphorus) are measured in the Upper Mississippi River Watershed, Ohio River Basin, and Maumee River Basins. The data include estimates of risk indices (reliability, resilience, vulnerability) and a composite watershed health measure at gauge the stations, distributional properties of the indices, sensitivity to water quality standards, scale dependency of the indices, and statistical significance of the relationship between composite watershed health measure and land uses (agricultural, forested, and urban). \n\nThis dataset is associated with the following publication:\nGaneshchandra Mallya  , G., M. Hantush, and R. Govindaraju. Composite measures of watershed health from a water quality perspective.   JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 214: 104-124, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1405326",
            "keyword": [
                "Reliability",
                "Resiliance",
                "Vulnerability",
                "Composite Watershed Health",
                "water quality",
                "scaling",
                "sediment",
                "nitrogen",
                "phosphorus",
                "Upper Mississippi River Watershed",
                "Ohio River Basin",
                "Maummee River Basin",
                "Risk Assessment",
                "Water Quality Standard",
                "stream order",
                "resilience",
                "watershed health water quality",
                "stream networks",
                "Trend analysis"
            ],
            "contactPoint": {
                "fn": "Mohamed Hantush",
                "hasEmail": "mailto:hantush.mohamed@epa.gov"
            },
            "distribution": [
                {
                    "title": "EPA_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1405326/EPA_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-24",
            "references": [
                "https://doi.org/10.1016/j.jenvman.2018.02.049"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Construction and Demolition Debris 2014 US Final Disposition Estimates Using the CDDPath Method",
            "description": "Estimates of the final amount and final disposition of materials generated in the Construction and Demolition waste stream measured in total mass of each material. Traditional C&D materials included are concrete, asphalt pavement, asphalt shingles, bricks and clay, metal, wood, and gypsum drywall. Non-traditional materials in this stream include cardboard, organics, carpet, glass, plastic, and fines. The estimates are based on generation amounts described in the EPA SMM Facts and Figures reports. The method used to estimate final disposition is called CDDpath. This dataset is associated with the following publication:\nTownsend, T., W. Ingwersen, B. Niblick, P. Jain, and J. Wally. CDDPath: A method for quantifying the loss and recovery of construction and demolition debris in the United States.   WASTE MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 84: 302-309, (2019). NOTE: This dataset has been removed from public access due to revocation. Please refer inquiries regarding this dataset to the listed contact person.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1431308",
            "keyword": [
                "Concrete",
                "asphalt pavement",
                "Wood",
                "bricks",
                "carpet",
                "asphalt shingles",
                "mixed C&D MRF",
                "metal",
                "drywall",
                "Sustainable materials management",
                "construction and demolition debris",
                "life cycle assessment",
                "end-of-life management"
            ],
            "contactPoint": {
                "fn": "Briana Niblick",
                "hasEmail": "mailto:niblick.briana@epa.gov"
            },
            "distribution": [],
            "modified": "2018-04-05",
            "references": null,
            "publisher": {
                "name": "U.S. Environmental Protection Agency",
                "subOrganizationOf": {
                    "name": "U.S. Government"
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Alderisio_Meri_vs_ES_MS_vs_MSD",
            "description": "Stain Comparison Meri vs. ES. \n\nThis dataset is associated with the following publication:\nAlderiswio, K., L. Villegas, M. Ware, L. McDonald, L. Xiao, and E. Villegas. Differences in staining intensities affect reported occurrences and concentrations of Giardia spp. in surface drinking water sources.   JOURNAL OF APPLIED MICROBIOLOGY. Blackwell Publishing, Malden, MA, USA, 123(6): 1607-1613, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1393896",
            "keyword": [
                "drinking water",
                "protozoa",
                "water quality",
                "Environmental/recreational water",
                "detection",
                "drinking water sources",
                "giardia spp",
                "occurrences and concentrations",
                "staining intensitities"
            ],
            "contactPoint": {
                "fn": "Eric Villegas",
                "hasEmail": "mailto:villegas.eric@epa.gov"
            },
            "distribution": [
                {
                    "title": "Alderisio-Meri_vs_ES_MS_vs_MSD-Scibhub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393896/Alderisio-Meri_vs_ES_MS_vs_MSD-Scibhub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "0017-06-28",
            "references": [
                "https://doi.org/10.1111/jam.13585"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Trends Between Modeled DeFacto Reuse and Analyzed Grab Samples for Contaminants of Emerging Concern at Water Treatment Plants in The USA",
            "description": "This dataset compared the de facto reuse percentage modeled for the 22 surface water sites sampled in Phase II of the drinking water project and the organic chemical data generated as part of the project. \n\nThis dataset is associated with the following publication:\nNguyen , T., P. Westerhoff , E. Furlong, D. Kolpin, A. Batt, H. Mash, K. Schenck, J.S. Boone, J. Rice, and S. Glassmeyer. Modeled De Facto Reuse and Contaminants of Emerging Concern in Drinking Water Source Waters.   JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA, 110(4): E2-E18, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407663",
            "keyword": [
                "DRINCS",
                "de facto reuse",
                "stream order",
                "drinking water",
                "source water",
                "pharmaceuticals",
                "microorganisms",
                "Per- and polyfluoroalkyl substances"
            ],
            "contactPoint": {
                "fn": "Susan Glassmeyer",
                "hasEmail": "mailto:glassmeyer.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Phase II data DRINCS figures and tables.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407663/Phase%20II%20data%20DRINCS%20figures%20and%20tables.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Data dictionary.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407663/Data%20dictionary.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2018-01-09",
            "references": [
                "https://doi.org/10.1002/awwa.1052"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The Photochemical Conversion of Surrogate Emissions for Use in Toxicological Studies:   Role of Particulate- and Gas-Phase Products",
            "description": "The production of photochemical atmospheres under controlled conditions in an irradiation chamber permits the manipulation of parameters that influence the resulting air pollutant chemistry and potential biological effects.  To date no studies have examined how contrasting atmospheres with a similar Air Quality Health Index (AQHI), but with differing ratios of criteria air pollutants, might differentially affect health endpoints.  Here we produced two atmospheres with similar AQHIs based on the final concentrations of ozone, nitrogen dioxide, and particulate matter (PM2.5).  One simulated atmosphere (SA-PM) generated from irradiation of ~23 ppmC gasoline, ~5 ppmC of \u03b1-pinene, 529 ppb NO, and 3 \u00b5g m-3 (NH4)2SO4 as a seed resulted in ~976 \u00b5g m-3 PM2.5, 326 ppb NO2, and 141 ppb O3 (AQHI 97.7).  The other atmosphere (SA-O3) generated from ~8 ppmC gasoline, 5 ppmC isoprene, 874 ppb NO, 2 \u00b5g m-3 (NH4)2SO4 resulted in ~55 \u00b5g m-3 PM2.5, 643 ppb NO2, and 430 ppb O3 (AQHI of 99.8).  Chemical speciation by gas chromatography showed that photo-oxidation degraded the organic precursors and promoted the de novo formation of secondary reaction products such as formaldehyde and acrolein.  Further work in accompanying papers describe toxicological outcomes from the two distinct photochemical atmospheres. \n\nThis dataset is associated with the following publication:\nKrug, J., M. Lewandowski, J. Offenberg, J. Turlington, W. Lonneman, N. Modak, T. Krantz, C. King, S. Gavett, I. Gilmour, D. DeMarini, and T. Kleindienst. Photochemical Conversion of Surrogate Emissions for Use in Toxicological Studies: Role of Particulate- and Gas-Phase Products.   International Journal of Environmental Science and Technology. Springer, Heidelburg,  GERMANY, 52(5): 3037-3044, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407610",
            "keyword": [
                "Smog chamber",
                "gasoline surrogate emissions",
                "air pollution",
                "health effects",
                "air quality",
                "Secondary Organic Aerosol",
                "air toxics",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Michael Lewandowski",
                "hasEmail": "mailto:lewandowski.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Krug_MRC_Figure 2.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407610/Krug_MRC_Figure%202.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Krug_MRC_Figure 3.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407610/Krug_MRC_Figure%203.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-24",
            "references": [
                "https://doi.org/10.1021/acs.est.7b04879"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data from modeling",
            "description": "Simulation output from CMAQ runs for Uinta Basin. \n\nThis dataset is associated with the following publication:\nMatichuk, R., G. Tonnesen, D. Luecken, R. Gilliam, S. Napelenok, K. Baker, D. Schwede, B. Murphy, D. Helmig, S. Lyman, and S. Roselle. Evaluation of the Community Multiscale Air Quality Model for Simulating Winter Ozone Formation in the Uinta Basin..   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 122(24): 13545-13572, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407533",
            "keyword": [
                "CMAQ",
                "Ozone",
                "winter",
                "UBWOS"
            ],
            "contactPoint": {
                "fn": "Deborah Luecken",
                "hasEmail": "mailto:luecken.deborah@epa.gov"
            },
            "distribution": [
                {
                    "title": "2017JD027057-F03.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407533/2017JD027057-F03.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "pcaps4_2_iter3.GROUP_AVG.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407533/pcaps4_2_iter3.GROUP_AVG.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "2017JD027057-F04.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407533/2017JD027057-F04.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "2017JD027057-F05.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407533/2017JD027057-F05.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "2017JD027057-F06.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407533/2017JD027057-F06.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "2017JD027057-F08.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407533/2017JD027057-F08.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "2017JD027057-F09.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407533/2017JD027057-F09.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "2017JD027057-F10.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407533/2017JD027057-F10.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "2017JD027057-F11.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407533/2017JD027057-F11.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "2017JD027057-F12.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407533/2017JD027057-F12.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "2017JD027057-F13.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407533/2017JD027057-F13.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "2017JD027057-F14.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407533/2017JD027057-F14.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "Data_in_ncs_for_Fig1_Fig15_FigS7-S14.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407533/Data_in_ncs_for_Fig1_Fig15_FigS7-S14.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "met.figs.ubos.tar",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407533/met.figs.ubos.tar",
                    "mediaType": "application/x-tar"
                }
            ],
            "modified": "2017-03-01",
            "references": [
                "https://doi.org/10.1002/2017jd027057"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Wastewater viral community",
            "description": "The dataset contains the information used to generate the figures in the manuscript. The data describes the viral loss measured at all steps of sample processing, culminating in a description of the viral community in a wastewater sample. \n\nThis dataset is associated with the following publication:\nBrinkman , N., E. Villegas , J. Garland , and S. Keely. Reducing inherent biases introduced during DNA viral metagenome analyses of municipal wastewater.   PLoS ONE. Public Library of Science, San Francisco, CA, USA, 13(4): e0195350, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1422367",
            "keyword": [
                "wastewater",
                "Bacteriophage",
                "viral metagenomics"
            ],
            "contactPoint": {
                "fn": "Nichole Brinkman",
                "hasEmail": "mailto:brinkman.nichole@epa.gov"
            },
            "distribution": [
                {
                    "title": "BrinkmanNichole_A-qfvf_dataset_20180223.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1422367/BrinkmanNichole_A-qfvf_dataset_20180223.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-02-23",
            "references": [
                "https://doi.org/10.1371/journal.pone.0195350"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "model calibration",
            "description": "The East Fork data and the methods used to calibrated the model are detailed in the attached previously published EPA report ",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1433513",
            "keyword": [
                "best management practices",
                "Total maximum daily load",
                "ArcHydro",
                "probabilistit risk assessment"
            ],
            "contactPoint": {
                "fn": "Herbert Fredrickson",
                "hasEmail": "mailto:fredrickson.herbert@epa.gov"
            },
            "distribution": [
                {
                    "title": "Yeghiazarian etal-2013-EPA600-R13.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1433513/Yeghiazarian%20etal-2013-EPA600-R13.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2013-05-31",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Aaron Journal article datasets",
            "description": "All figures used in the journal article are in netCDF format. \n\nThis dataset is associated with the following publication:\nSims, A., K. Alapaty , and S. Raman. Sensitivities of Summertime Mesoscale Circulations in the Coastal Carolinas to Modifications of the Kain\u2013Fritsch Cumulus Parameterization.   Monthly Weather Review. American Meteorological Society, Boston, MA, USA, 145(11): 4381-4399, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1420061",
            "keyword": [
                "weather prediction",
                "precipitation cloud life cloud cover",
                "deep convection"
            ],
            "contactPoint": {
                "fn": "Kirankumar Alapaty",
                "hasEmail": "mailto:alapaty.kiran@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://climate.ncsu.edu/files/pubs/MWR-D-16-0047.1/",
                    "accessURL": "https://climate.ncsu.edu/files/pubs/MWR-D-16-0047.1/"
                }
            ],
            "modified": "2016-01-05",
            "references": [
                "https://doi.org/10.1175/mwr-d-16-0047.1"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Exploring Synergies between transit investment and dense redevelopment: A scenario analysis in a rapdily developing urban landscape",
            "description": "This dataset is a journal article that describes the use of a system dynamics model to explore the synergies between transit and development strategies as they give rise to outcomes of community concern: environmental impacts, economic development and equity. The dataset includes the publication itself, the publication figures, the input and calibration data, the data dictionary and the model output data for the base scenarios. \n\nThis dataset is associated with the following publication:\nCox, L., A. Bassi, J. Kolling, A. Procter, N. Flanders, N. Tanners, and R. Araujo. Exploring synergies between transit investment and dense redevelopment: A scenario analysis in a rapidly urbanizing landscape.   LANDSCAPE AND URBAN PLANNING. Elsevier Science Ltd, New York, NY, USA, 167: 429-440, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1407615",
            "keyword": [
                "compact development",
                "equity",
                "integrated approaches",
                "sustainability",
                "light rail"
            ],
            "contactPoint": {
                "fn": "Rochelle Araujo",
                "hasEmail": "mailto:araujo.rochelle@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cox_et_al_2017_Exploring synergies between transit.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407615/Cox_et_al_2017_Exploring%20synergies%20between%20transit.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Cox_Figures for Land Use Paper.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407615/Cox_Figures%20for%20Land%20Use%20Paper.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Cox_Land Use Paper RedevelopmentTables.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407615/Cox_Land%20Use%20Paper%20RedevelopmentTables.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "D-O LRP Model_Base Scenario Outputs.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407615/D-O%20LRP%20Model_Base%20Scenario%20Outputs.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "D-O LRP SD Model Documentation Appendix B.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407615/D-O%20LRP%20SD%20Model%20Documentation%20Appendix%20B.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Historical and Projected Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407615/Historical%20and%20Projected%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-23",
            "references": [
                "https://doi.org/10.1016/j.landurbplan.2017.07.021"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Consumer Product Chemical Weight Fractions from Ingredient Lists ",
            "description": "Data and model predictions supporting the manuscript: Isaacs K.K., Phillips K.A., Biryol D., Dionisio K.L., and Price P. Consumer product chemical weight fractions from ingredient lists. Journal of Exposure Science and Environmental Epidemiology (in press as of 8/2017). \n\nThis dataset is associated with the following publication:\nIsaacs, K., K. Phillips, D. Biryol, K. Dionisio, and P. Price. Consumer product chemical weight fractions from ingredient lists.   Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London,  UK, 28: 216-222, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1374397",
            "keyword": [
                "consumer products",
                "Exposure modeling",
                "Chemical Safety for Sustainability",
                "ingredients"
            ],
            "contactPoint": {
                "fn": "Kristin Isaacs",
                "hasEmail": "mailto:isaacs.kristin@epa.gov"
            },
            "distribution": [
                {
                    "title": "All_Datasets.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374397/All_Datasets.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-19",
            "references": [
                "https://doi.org/10.1038/jes.2017.29"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1374397/documents/DataDictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Antiandrogenic effects of prochloraz in Xenopus laevis_data_Haselman et al_version_0_20171122",
            "description": "These data are represented in the tables and graphs in the journal article, Antiandrogenic effects following multiple life stage exposure to the fungicide prochloraz in Xenopus laevis by JT Haselman et al. \n\nThis dataset is associated with the following publication:\nHaselman, J., P. Kosian, J. Korte, A. Olmstead, and S. Degitz. Effects of multiple life stage exposure to the fungicide prochloraz in Xenopus laevis: Manifestations of antiandrogenic and other modes of  toxicity.   AQUATIC TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 199: 240-251, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1409830",
            "keyword": [
                "Prochloraz",
                "endocrine disruption",
                "EDSP",
                "Xenopus laevis",
                "LAGDA"
            ],
            "contactPoint": {
                "fn": "Jonathan Haselman",
                "hasEmail": "mailto:haselman.jon@epa.gov"
            },
            "distribution": [
                {
                    "title": "Haselman_et_al_Prochloraz_data_A63z2.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1409830/Haselman_et_al_Prochloraz_data_A63z2.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-11-22",
            "references": [
                "https://doi.org/10.1016/j.aquatox.2018.03.013"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Boquer\u00f3n Beach, PR immunoprevalence study",
            "description": "The data contained in this worksheet provides the Median Fluorescence Intensity (MFI) readings for the Boquer\u00f3n Beach, Puerto Rico saliva samples collected on Day 1 of the study and used to assess immunoprevalence of the beachgoers to the pathogens in the multiplex immunoassay. \n\nThis dataset is associated with the following publication:\nAugustine, S., K. Simmons, T. Eason, C. Curioso, S. Griffin, T. Wade, A. Dufour, S. Fout, A. Grimm, K. Oshima, E. Sams, M. See, and L. Wymer. Immunoprevalence to Six Waterborne Pathogens in Beachgoers at Boquer\u00f3n Beach, Puerto Rico: Application of a Microsphere-Based Salivary Antibody Multiplex Immunoassay.   Frontiers in Public Health. Frontiers, Lausanne,  SWITZERLAND, 5(84): 1-11, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1390125",
            "keyword": [
                "Puerto Rico",
                "Boqueron Beach",
                "Multiplex",
                "immunoassay",
                "salivary antibody",
                "saliva",
                "exposure",
                "bead-based multiplexing",
                "carboxylated microspheres",
                "bead coupling",
                "coupling confirmation"
            ],
            "contactPoint": {
                "fn": "Swinburne Augustine",
                "hasEmail": "mailto:augustine.swinburne@epa.gov"
            },
            "distribution": [
                {
                    "title": "Boqueron data (Augustine et al. 2017-Frontiers).xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390125/Boqueron%20data%20%28Augustine%20et%20al.%202017-Frontiers%29.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-07-19",
            "references": [
                "https://doi.org/10.3389/fpubh.2017.00084"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The potential role of natural gas power plants with carbon capture and storage as a bridge to a low-carbon future",
            "description": "This dataset represents the data underlying the figures presented in the manuscript \"The potential role of natural gas power plants with carbon capture and storage as a bridge to a low-carbon future.\" The manuscript itself is a parametric analysis examining this technology under various technological and contextual assumptions. \n\nThis dataset is associated with the following publication:\nBabaee, S., and D. Loughlin. Exploring the role of natural gas power plants with carbon capture and storage as a bridge to a low-carbon future.   CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY. Springer-Verlag, New York, NY, USA, 20(2): 379-391, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1371942",
            "keyword": [
                "natural gas",
                "renewable electricity",
                "mitigation options",
                "Energy systems modeling",
                "MARKAL",
                "nested sensitivity analysis",
                "electricity generation",
                "coal",
                "emission projections",
                "scenario analysis",
                "air quality",
                "climate change"
            ],
            "contactPoint": {
                "fn": "Daniel Loughlin",
                "hasEmail": "mailto:loughlin.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "figure_data_NGCC_CCS_v1_07202017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371942/figure_data_NGCC_CCS_v1_07202017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-01-31",
            "references": [
                "https://doi.org/10.1007/s10098-017-1479-x"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "ENANTIOMER-SPECIFIC MEASUREMENTS OF CURRENT-USE PESTICIDES IN AQUATIC SYSTEMS",
            "description": "These data are provided in six data tables. Each data table corresponds to a set of samples obtained from a different organization in California that were analyzed for this study. Metadata is presented as table captions, column headers and/or row information for each set of samples. The metadata for each sample set/table varies but includes some combination of the following: organization providing the samples; units of measure (as appropriate); fipronil enantiomer fraction (EF), bifenthrin EF, cis-permethrin EF; racemic standard EFs for fipronil, bifenthrin, and cis-permethrin analyzed with each set of samples [these data were measured for the study]; sample description including location collected, type of sample, date of sample collection, fipronil, bifenthrin, and cis-permethrin concentrations; pavement treatment information including compounds used for concrete treatment, formulation applied to concrete, number of days since treatment; fish and fish treatment information including dose, number of days since dose, fish mortality status, fish length and weight; percent survival in toxicity tests. Additionally, some data analysis information is provided that indicates whether the EF measured in a given sample is not measured, the compound was not detected, racemic or non-racemic. \n\nThis dataset is associated with the following publication:\nUlrich , E., P. TenBrook , L. McMillan, O. Wang, and W. Lao. Enantiomer\u2010specific measurements of current\u2010use pesticides in aquatic systems.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(1): 99-106, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1374566",
            "keyword": [
                "Chiral current-use pesticide",
                "Enantiomer fraction (EF)",
                "aquatic systems",
                "racemic"
            ],
            "contactPoint": {
                "fn": "Elin Ulrich",
                "hasEmail": "mailto:ulrich.elin@epa.gov"
            },
            "distribution": [
                {
                    "title": "ET&C Suppl Info Enantiomer measurements of pesticides in aquatic systems revised.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374566/ET%26C%20Suppl%20Info%20Enantiomer%20measurements%20of%20pesticides%20in%20aquatic%20systems%20revised.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "https://setac.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fetc.3938&file=etc3938-sup-0001-SuppData-S1.docx",
                    "accessURL": "https://setac.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fetc.3938&file=etc3938-sup-0001-SuppData-S1.docx"
                }
            ],
            "modified": "2017-03-21",
            "references": [
                "https://doi.org/10.1002/etc.3938"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Analysis of emission reduction strategies for power boilers in the US pulp and paper industry",
            "description": "This paper first presents the background information for UISIS-PNP model by discussing different types of boilers installed throughout the pulp and paper sector, the air emissions from these boilers, and the menu of air pollution control technologies applicable to the boilers. The paper then presents examples of air pollution reduction strategies, followed by an analysis of the benefits of emission reduction strategies. These examples are given to illustrate modeling capabilities of the UISIS-PNP model and should not be construed as actual emission reduction strategy considerations by EPA. \n\nThis dataset is associated with the following publication:\nBhander , G., and W. Jozewicz. Analysis of Emissions Reduction Strategies for Power Boilers in the U.S. Pulp and Paper Industry..   Energy and Emission Control Technologies. Dove Medical Press, AUCKLAND,  NEW ZEALAND, 2017(5): 27-37, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1392998",
            "keyword": [
                "Power boilers",
                "pulp and paper production",
                "emission sources",
                "fuel consumption",
                "mitigation options",
                "fuel exchange",
                "emissions controls technologies",
                "emissions reduction"
            ],
            "contactPoint": {
                "fn": "Gurbakhash Bhander",
                "hasEmail": "mailto:bhander.gurbakhash@epa.gov"
            },
            "distribution": [
                {
                    "title": "PnP Sector Boilers Dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1392998/PnP%20Sector%20Boilers%20Dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-04-21",
            "references": [
                "https://doi.org/10.2147/eect.s139648",
                "https://pasteur.epa.gov/uploads/10.23719/1392998/documents/PNP%20BOILERS%20PAPER.pdf"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data and code files for co-occurrence modeling project",
            "description": "Files included are original data inputs on stream fishes (fish_data_OEPA_2012.csv), water chemistry (OEPA_WATER_2012.csv), geographic data (NHD_Plus_StreamCat); modeling files for generating predictions from the original data, including the R code (MVP_R_Final.txt) and Stan code (MV_Probit_Stan_Final.txt); and the model output file containing predictions for all NHDPlus catchments in the East Fork Little Miami River watershed (MVP_EFLMR_cooc_Final). \n\nThis dataset is associated with the following publication:\nMartin, R., E. Waits, and C. Nietch. Empirically-based modeling and mapping to consider the co-occurrence of ecological receptors and stressors.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 613(614): 1228-1239, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407576",
            "keyword": [
                "R code",
                "Stan code",
                "East Fork Little Miami River watershed data",
                "Water chemistry bioassessment data",
                "Fish community bioassessment data",
                "Co-occurrence model",
                "Co-occurrence model predictions",
                "co-occurrence models",
                "Bayesian statistics",
                "ecological risk mapping",
                "ecological exposure assessment"
            ],
            "contactPoint": {
                "fn": "Roy Martin",
                "hasEmail": "mailto:martin.roy@epa.gov"
            },
            "distribution": [
                {
                    "title": "fish_data_OEPA_2012.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407576/fish_data_OEPA_2012.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "OEPA_WATER_2012.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407576/OEPA_WATER_2012.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "NHD_Plus_StreamCat.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407576/NHD_Plus_StreamCat.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "MVP_R_Final.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407576/MVP_R_Final.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "MV_Probit_Stan_Final.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407576/MV_Probit_Stan_Final.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "MVP_EFLMR_cooc_Final.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407576/MVP_EFLMR_cooc_Final.txt",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2017-07-13",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2017.08.301"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1407576/documents/EFLMR_cooc_data_dictionary_Final.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Temperature and driving cycle influence SVOC emissions from (bio-) diesel trucks",
            "description": "The present study examines the effects of fuel (an ultra-low sulfur diesel [ULSD] versus a 20% v/v soy-based biodiesel\u201480% v/v petroleum blend [B20]), temperature, load, vehicle, driving cycle, and active regeneration technology on gas- and particle-phase carbon emissions from light and medium heavy-duty diesel vehicles (L/MHDDV). The study is performed using chassis dynamometer facilities that support low temperature operation (-6.7 \u00b0C versus 21.7 \u00b0C) and heavy loads up to 12,000 kg. Organic and elemental carbon (OC-EC) composition of aerosol particles is determined using a thermal-optical technique. Gas- and particle-phase semivolatile organic compound (SVOC) emissions collected using traditional filter and polyurethane foam (PUF) sampling media are analyzed using advanced gas chromatograpy/mass spectrometry (GC/MS) methods. \n\nThis dataset is associated with the following publication:\nHays, M., W. Preston, B. George, I. George, R. Snow, J. Faircloth, T. Long, R. Baldauf, and J. McDonald. Temperature and driving cycle significantly affect semi-volatile organic compound emissions from diesel trucks.   ENERGY AND FUELS. American Chemical Society, Washington, DC, USA, 31(10): 11034-11042, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1377043",
            "keyword": [
                "PM",
                "organic aerosol",
                "Semivolatile Organic Compounds (SVOCs)",
                "biodiesel",
                "Fine Particulate Matter",
                "Aerosol Optical Properties",
                "biomass burning",
                "Combustion Emissions",
                "polycyclic aromatic hydrocarbons"
            ],
            "contactPoint": {
                "fn": "Michael Hays",
                "hasEmail": "mailto:hays.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377043/Figure%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-16",
            "references": [
                "https://doi.org/10.1021/acs.energyfuels.7b01446"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Emissions characterization from a variety of coals on a pilot-scale facility_v1",
            "description": "The current study not only characterizes emissions from three coals (bituminous, sub-bituminous, and lignite), but also investigates the use of instrumentation for improved measurement and monitoring techniques that provide real-time, continuous emissions data.  Testing was completed using the U.S. EPA\u2019s Multi-Pollutant Control Research Facility, a pilot-scale coal-fired combustor using industry-standard emission control technologies, in Research Triangle Park, North Carolina.  Emissions were calculated based on measurements from the flue gas (pre- and post-electrostatic precipitator), to characterize gaseous species (CO, CO2, O2, NOX, SO2, other acid gases, and several organic HAPs) as well as fine and ultrafine particulate (mass, size distribution, number count, elemental carbon, organic carbon, and black carbon).  Comparisons of traditional EPA methods to those made via Fourier Transfer Infrared (FTIR) Spectroscopy for CO, NOX, and SO2 are also reported. \n\nThis dataset is associated with the following publication:\nYelverton, T., A. Brashear, D. Nash, E. Brown, C. Singer, P. Kariher, and J. Ryan. Comparison of gaseous and particulate emissions from a pilot-scale combustor using three varieties of coal.   FUEL. Elsevier Science BV, Amsterdam,  NETHERLANDS, 215: 572-579, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1371562",
            "keyword": [
                "measurement comparison",
                "coal combustion",
                "biomass",
                "emissions characterization",
                "air qualtiy"
            ],
            "contactPoint": {
                "fn": "Tiffany Yelverton",
                "hasEmail": "mailto:yelverton.tiffany@epa.gov"
            },
            "distribution": [
                {
                    "title": "SH-Fuel 2017 data tables with data dictionary_published.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371562/SH-Fuel%202017%20data%20tables%20with%20data%20dictionary_published.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-30",
            "references": [
                "https://doi.org/10.1016/j.fuel.2017.10.092"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Whiting, Indiana Refinery Canister and Tube VOC Sampling",
            "description": "VOC canister and tube data from Whiting, Indiana. \n\nThis dataset is associated with the following publication:\nMukerjee, S., L. Smith, M. Caudill, K. Oliver, W. Whipple, D. Whitaker, and T. Cousett. Application of passive sorbent tube and canister samplers for volatile organic compounds at refinery fenceline locations in Whiting, Indiana.   JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION. Air & Waste Management Association, Pittsburgh, PA, USA, 68(2): 170-175, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1413474",
            "keyword": [
                "Fenceline Monitoring",
                "Passive Sampling",
                "benzene",
                "epa method 325",
                "refinery",
                "volatile organic compound"
            ],
            "contactPoint": {
                "fn": "Shaibal Mukerjee",
                "hasEmail": "mailto:mukerjee.shaibal@epa.gov"
            },
            "distribution": [
                {
                    "title": "CAN_CRL all dups.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413474/CAN_CRL%20all%20dups.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Whiting IN benzene & toluene method comparison_Motria_direct.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413474/Whiting%20IN%20benzene%20%26%20toluene%20method%20comparison_Motria_direct.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "CRL vs ORD all Perc and styrene_with_DLs.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413474/CRL%20vs%20ORD%20all%20Perc%20and%20styrene_with_DLs.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Whiting_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413474/Whiting_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-10-23",
            "references": [
                "https://doi.org/10.1080/10962247.2017.1400480"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Phytoplankton and cyanobacteria",
            "description": "Phytoplankton and cyanobacteria. \n\nThis dataset is associated with the following publication:\nChen, K., J. Lu, and J. Allen. 12   Community structures of phytoplankton with emphasis of toxic cyanobacteria in an Ohio inland lake during bloom season.   ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH. Ecomed Verlagsgesellschaft AG, Landsberg,  GERMANY, 9(11): 1-29, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407678",
            "keyword": [
                "bloom",
                "lake",
                "phytoplankton",
                "toxic cyanobacteria"
            ],
            "contactPoint": {
                "fn": "Jingrang Lu",
                "hasEmail": "mailto:lu.jingrang@epa.gov"
            },
            "distribution": [
                {
                    "title": "Phytoplankton-Cyanobacteria.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407678/Phytoplankton-Cyanobacteria.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-04-20",
            "references": [
                "https://doi.org/10.4236/jwarp.2017.911083"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Storage Tank Legionella and Community",
            "description": "Storage Tank Legionella and Community. \n\nThis dataset is associated with the following publication:\nQin, K., I. Struewing, J. Santodomingo, D. Lytle, and J. Lu. Opportunistic Pathogens and Microbial Communities and their Associations with Sediment Physical Parameters in Drinking Water Storage Tank Sediments.   PATHOGENS. MDPI AG, Basel,  SWITZERLAND, 6(54): 1-28, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407686",
            "keyword": [
                "corrosion",
                "legionella",
                "microbial community",
                "mineral",
                "opportunistic pathogen",
                "storage tank sediment"
            ],
            "contactPoint": {
                "fn": "Jingrang Lu",
                "hasEmail": "mailto:lu.jingrang@epa.gov"
            },
            "distribution": [
                {
                    "title": "Sediment datasheet 072517.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407686/Sediment%20datasheet%20072517.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-10-10",
            "references": [
                "https://doi.org/10.3390/pathogens6040054"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Characterization of spray disinfectant products advertised to contain colloidal silver",
            "description": "Included in dataset. \n\nThis dataset is associated with the following publication:\nRogers, K., J. Navratilova, A. Stefaniak, L. Bowers, A. Knepp, S. Al-Abed, P. Potter, A. Gitipour, I. Radwan, C. Nelson, and K. Bradham. Characterization of engineered nanoparticles in commercially available spray disinfectant products advertised to contain colloidal silver.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 619620: 1375-1384, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407603",
            "keyword": [
                "characterization",
                "collodial silver",
                "Human Exposure",
                "nanosilver"
            ],
            "contactPoint": {
                "fn": "Kim Rogers",
                "hasEmail": "mailto:rogers.kim@epa.gov"
            },
            "distribution": [
                {
                    "title": "Rogers et al 2017 Science Hub Data.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407603/Rogers%20et%20al%202017%20Science%20Hub%20Data.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2017-08-02",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2017.11.195"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Metabolomic profiling of Green Frogs exposed to Mixed Pesticides",
            "description": "GC/MS data from the metabolomic profiling of green frog livers after exposure to pesticides and their mixtures. \n\nThis dataset is associated with the following publication:\nVan Meter, R., D. Glinski, T. Purucker, and M. Henderson. Influence of exposure to pesticide mixtures on the metabolomic profile in post-metamorphic green frogs (Lithobates clamitans).   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 624: 1348-1359, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1420400",
            "keyword": [
                "amphibian",
                "pesticide",
                "bioconcentration",
                "biomarkers"
            ],
            "contactPoint": {
                "fn": "William Henderson",
                "hasEmail": "mailto:henderson.matt@epa.gov"
            },
            "distribution": [
                {
                    "title": "RJV_Mix Pestcides_GF_for_metaboanalyst.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1420400/RJV_Mix%20Pestcides_GF_for_metaboanalyst.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "RJV_herbicides_GF_for_metaboanalyst.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1420400/RJV_herbicides_GF_for_metaboanalyst.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-06-23",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2017.12.175"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1420400/documents/Henderson_A-tqkg_SDMP_20180214.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "2018_extent_CI_data",
            "description": "Full resolution (300m), weekly MERIS data were obtained over the contiguous United States for 2008 through 2011. Seven day composite images were created by retaining the maximum value detected for each pixel within the time period and then the monthly mean of the maximums was calculated. A spatial mosaic composed of 54 individual scenes was generated for each week resulting in a total of 208 CONUS images from 2008 to 2011. Weekly OLCI data were also retrieved from January 2017 through December 2017. MERIS and OLCI data were processed by the NASA OBPG, using the SeaWiFS Data Analysis System, SRTM static land mask, and a transformation to Albers Equal Area with an area-weighted interpolation to match the projections of the National Hydrography Dataset High Resolution. The SRTM land mask and SeaDAS processing is static in relation to waterbody size and did not account for periods of drought nor flood during the study period. Any water pixel adjacent to the SRTM static land mask was automatically flagged and excluded from analysis to reduce potential for mixed land-water pixels and land adjacency effects. To avoid pixel misclassification due to artifacts such as bridges, catchment facilities, and islands, \u201cvalid\u201d water pixels were determined by examining the ESRI World Imagery Basemap. This manual operator pixel selection process lowered the potential that land pixels were not misclassified as water or vice versa.\nEach 300m satellite pixel in a weekly CONUS map represents a provisional maximum Cyanobacteria Index (CI) value retrieved in the specific time period. The provisional CI was calculated using a spectral shape (SS) algorithm detailed and validated elsewhere. \n\nConventional methods to distinguish between ice and water often fail due to high ice reflectance as well as the possibility of cyanobacterial biomass formation under the ice. Therefore, weekly MERIS data were masked for the presence of ice and snow using Interative Multisensor Snow and Ice Mapping System (IMS) Northern Hemisphere Snow and Ice Analysis data (Version 1, 4km). Daily snow and ice data were obtained from the National Snow and Ice Data Center then cropped to the extent of CONUS. Snow and ice data were temporally binned into maximum weekly time composites to match the MERIS data and then converted from raster to shapefile format. If MERIS or OLCI CI values were within the spatial area of the snow and ice mask, they were removed from further analysis. This dataset is associated with the following publication:\nUrquhart, E., and B. Schaeffer. Envisat MERIS and Sentinel-3 OLCI satellite lake biophysical water quality flag dataset for the contiguous United States.   Data in Brief. Elsevier B.V., Amsterdam,  NETHERLANDS, 28: 104826, (2020). NOTE: This dataset has been removed from public access due to revocation. Please refer inquiries regarding this dataset to the listed contact person.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1423890",
            "keyword": [
                "harmful algal bloom",
                "cyanobacteria",
                "lakes",
                "ecology",
                "satellite",
                "remote sensing",
                "water quality"
            ],
            "contactPoint": {
                "fn": "Blake Schaeffer",
                "hasEmail": "mailto:schaeffer.blake@epa.gov"
            },
            "distribution": [],
            "modified": "2018-03-01",
            "references": null,
            "publisher": {
                "name": "U.S. Environmental Protection Agency",
                "subOrganizationOf": {
                    "name": "U.S. Government"
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Guiyang_PM2.5_speciation_data_DOI_10.1007/s11631-017-0248-1",
            "description": "ED-XRF inorganic speciation of PM2.5 in Guiyang, China. \n\nThis dataset is associated with the following publication:\nLiang, L., N. Liu, M. Landis, X. Xu, X. Feng, Z. Chen, L. Shang, and G. Qiu. Chemical characterization and sources of PM2.5 at 12-h resolution in Guiyang, China.   Acta Geochimica. Springer, Heidelburg,  GERMANY, 37(2): 334-345, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1419639",
            "keyword": [
                "Trace elements",
                "pm2.5",
                "source apportionment"
            ],
            "contactPoint": {
                "fn": "Matthew Landis",
                "hasEmail": "mailto:landis.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data_all_set for AGC.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1419639/Data_all_set%20for%20AGC.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-17",
            "references": [
                "https://doi.org/10.1007/s11631-017-0248-1"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Influence of Coal Ash Leachates and Emergent Macrophytes on Water Quality in Wetland Microcosms",
            "description": "Influence of Coal Ash Leachates and Emergent Macrophytes on Water Quality in Wetland Microcosms. \n\nThis dataset is associated with the following publication:\nOlson, L., J. Misenheimer, C. Nelson, K. Bradham, and C. Richardson. Influences of Coal Ash Leachates and Emergent Macrophytes on Water Quality in Wetland Microcosms.   WATER, AIR AND SOIL POLLUTION:FOCUS. Springer, New York, NY, USA, 228: 344, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1407677",
            "keyword": [
                "coal combustion residues",
                "fly ash",
                "phytoremediation",
                "wetland"
            ],
            "contactPoint": {
                "fn": "Clay Nelson",
                "hasEmail": "mailto:nelson.clay@epa.gov"
            },
            "distribution": [
                {
                    "title": "ESM_1_final.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407677/ESM_1_final.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "ESM_2_final.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407677/ESM_2_final.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2017-01-01",
            "references": [
                "https://doi.org/10.1007/s11270-017-3520-4"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Relating soil geochemical properties to arsenic bioaccessibility ",
            "description": "soil element total concentration, soil pH and arsenic bioaccessibility values. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: The public can access the non personally identifiable data through the journal publisher if they have a subscription or other means to access journal articles from this publisher (Journal of Toxicology and Environmental Health). They can not access the personally identifiable/protected info. Format: These data were generated from EPA Regional samples. \n\nThis dataset is associated with the following publication:\nNelson, C., K. Li, D. Obenour, J. Miller, J. Misenheimer, K. Scheckel, A. Betts, A. Juhasz, D. Thomas, and K. Bradham. Relating soil geochemical properties to arsenic bioaccessibility through hierarchical modeling..   JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH - PART A:  CURRENT ISSUES. Taylor & Francis, Inc., Philadelphia, PA, USA, 81(6): 160-172, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1420304",
            "keyword": [
                "arsenic",
                "Bioaccessibility",
                "soil",
                "properties"
            ],
            "contactPoint": {
                "fn": "Clay Nelson",
                "hasEmail": "mailto:nelson.clay@epa.gov"
            },
            "distribution": [],
            "modified": "2017-11-01",
            "references": [
                "https://doi.org/10.1080/15287394.2018.1423798"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Soil As and Pb Levels and Plant Uptake in Three Gardens in Puerto Rico",
            "description": "Total and bioaccessible arsenic and lead levels and plant uptake in garden plants from Puerto Rico. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: The public can access the non personally identifiable data through the journal (Geosciences) publisher (MDPI).  The journal is open access and does not require a subscription. Format: These data were generated from EPA Regional plant and soil samples. \n\nThis dataset is associated with the following publication:\nMisenheimer, J., C. Nelson, E. Huertas, M. Medina-Vera, A. Prevatte, and K. Bradham. Total and Bioaccessible Soil Arsenic and Lead Levels and Plant Uptake in Three Urban Community Gardens in Puerto Rico.   Geosciences. MDPI AG, Basel,  SWITZERLAND, 8(2): 43, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1433316",
            "keyword": [
                "arsenic",
                "bioaccumulation factor",
                "lead",
                "Risk Assessment",
                "soil",
                "urban garden",
                "plant uptake",
                "urban gardens",
                "Puerto Rico",
                "Bioaccessibility"
            ],
            "contactPoint": {
                "fn": "Clay Nelson",
                "hasEmail": "mailto:nelson.clay@epa.gov"
            },
            "distribution": [],
            "modified": "2017-10-30",
            "references": [
                "https://doi.org/10.3390/geosciences8020043"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Relationship Between Total and Biaccessible Lead on Children's Blood Lead Levles in Urban Residential Philadelphia Soils.",
            "description": "Relationship Between Total and Biaccessible Lead on Children's Blood Lead Levles in Urban Residential Philadelphia Soils. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: These data are from a human study collected under IRB protocol:  Institutional Review Board approval was obtained from both the Centers for Disease Control and Prevention (CDC IRB Approval #6611, \"John T. Lewis Community Childhood Blood Lead Prevalence and Health Housing) and the Philadelphia Department of Public Health (PDPH). As such, it is a violation of Federal Law to publish them. Format: These data are from a Regional study in Philadelphia.  Institutional Review Board approval was obtained from both the Centers for Disease Control and Prevention and the Philadelphia Department of Public Health (PDPH). \n\nThis dataset is associated with the following publication:\nBradham, K., C. Nelson, J. Kelly, A. Pomales, K. Scruto, T. Dignam, J. Misenheimer, K. Li, D. Obenour, and D. Thomas. Relationship Between Total and Bioaccessible Lead on Children\u2019s Blood Lead Levels in Urban Residential Philadelphia Soils.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(17): 10005-10011, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1407685",
            "keyword": [
                "Bioaccessibility",
                "bioavailability",
                "Contamination",
                "lead",
                "soil"
            ],
            "contactPoint": {
                "fn": "Karen Bradham",
                "hasEmail": "mailto:bradham.karen@epa.gov"
            },
            "distribution": [],
            "modified": "2017-08-01",
            "references": [
                "https://doi.org/10.1021/acs.est.7b02058"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Comparison of mouse and swine bioassays for determination of soil arsenic relative bioavailability",
            "description": "Soil samples provided by EPA Regional offices to NERL for methods development based on the agreement that the sample identifiers never be released. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: The public can access the data, which are provided in the publication and presented in tables and figures within the publication. Format: These data were generated from EPA Regional samples.  All of the soil samples were provided by EPA Regional offices to NERL for methods development based on the agreement that the sample identifiers never be released.  There is currently on-going litigation for clean-up of these sites, which requires this information to be protected. \n\nThis dataset is associated with the following publication:\nBradham, K., G. Diamond, A. Juhasz, C. Nelson, and D. Thomas. Comparison of mouse and swine bioassays for determination of soil arsenic relative bioavailability.   APPLIED GEOCHEMISTRY. Elsevier Science Ltd, New York, NY, USA, 88: 221-225, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1420302",
            "keyword": [
                "Contamination",
                "arsenic",
                "bioavailability",
                "rish assessment",
                "soil"
            ],
            "contactPoint": {
                "fn": "Karen Bradham",
                "hasEmail": "mailto:bradham.karen@epa.gov"
            },
            "distribution": [],
            "modified": "2017-03-01",
            "references": [
                "https://doi.org/10.1016/j.apgeochem.2017.05.016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "ceilometer normalized backscatter, mixed layer height derived from the backscatter, and radiosondes (t, p, rh, elevation) in Hierarchical Data Format (HDF)",
            "description": "Ceilometer normalized backscatter, mixed layer height derived from the backscatter, and radiosondes (t, p, rh, elevation) in Hierarchical Data Format (HDF). This dataset is not publicly accessible because: Too large. It can be accessed through the following means: Additional data used in this manuscript is available upon request.  The request should be made via email to James Szykman, at szykman.jim@epa.gov.   The additional data includes ceilometer normalized backscatter, mixed layer height derived from the backscatter, and radiosondes (t, p, rh, elevation) in Hierarchical Data Format (HDF). Format: ceilometer normalized backscatter, mixed layer height derived from the backscatter, and radiosondes (t, p, rh, elevation) in Hierarchical Data Format (HDF). \n\nThis dataset is associated with the following publication:\nKnepp, T., J. Szykman, R. Long, R. Duvall, J. Krug, M. Beaver, K. Cavender, K. Kronmiller, M. Wheeler, R. Delgado, R. Hoff, T. Berkoff, E. Olson, R. Clark, D. Wolfe, D. Van Gilst, and D. Neil. Assessment of mixed-layer height estimation from single-wavelength ceilometer profiles.   Atmospheric Measurement Techniques. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 10: 3963-3983, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1420307",
            "keyword": [
                "ceilometer",
                "boundary layer height",
                "mixing height"
            ],
            "contactPoint": {
                "fn": "James Szykman",
                "hasEmail": "mailto:szykman.jim@epa.gov"
            },
            "distribution": [],
            "modified": "2015-12-31",
            "references": [
                "https://doi.org/10.5194/amt-10-3963-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Greenspace and sudden unexpected death ",
            "description": "The attached dataset comprises 187 records, summarized by 2010 census tract. There are 40 variable fields including percent landcover type from the 2011 30m National Land Cover Dataset, density of greenway trails from Wake County (NC) gov't, and demographic attributes from the 2014 American Community Survey.  Two fields reflect count (during 2013-2015) and rate of sudden death; these fields are blank because these human-health data are protected under IRB agreement through UNC.\n\nThe EPA/ORD point of contact for this analysis is Dr. Laura Jackson (jackson.laura@epa.gov).  If interested in acessing the Wake County sudden death dataset, please contact Dr. Ross Simpson (ross_simpson@med.unc.edu). \n\nThis dataset is associated with the following publication:\nWu, J., K. Rappazzo, R. Simpson, G. Joodi, I. Pursell, P. Mounsey, W. Cascio, and L. Jackson. Exploring links between greenspace and sudden unexpected death: a spatial analysis.   ENVIRONMENT INTERNATIONAL. Elsevier B.V., Amsterdam,  NETHERLANDS, 113: 114-121, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1434304",
            "keyword": [
                "Greenspace",
                "Sudden unexpected death",
                "greenway",
                "forest",
                "Bayesian spatial model",
                "Negative binomial model",
                "Wake County",
                "near-road tree canopy"
            ],
            "contactPoint": {
                "fn": "Jianyong Wu",
                "hasEmail": "mailto:wu.jianyong@epa.gov"
            },
            "distribution": [
                {
                    "title": "greenspace and sudden death data.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434304/greenspace%20and%20sudden%20death%20data.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "greenspace and sudden death data dictonary.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434304/greenspace%20and%20sudden%20death%20data%20dictonary.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2018-04-24",
            "references": [
                "https://doi.org/10.1016/j.envint.2018.01.021"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Use of Bayesian Modeling to Assess Occurrence of Viral Pathogens in Multiple US Drinking Water Systems",
            "description": "Drinking water treatment plants rely on purification of contaminated source waters to provide communities with potable water.  One group of possible contaminants are enteric viruses.  Measurement of viral quantities in environmental water systems are often performed using polymerase chain reaction (PCR) or quantitative PCR (qPCR). However, true values may be underestimated due to challenges involved in a multi-step viral concentration process and due to PCR inhibition.  In this study, water samples were concentrated from 25 drinking water treatment plants (DWTPs) across the US to study the occurrence of enteric viruses in source water and removal after treatment.  The five different types of viruses studied were adenovirus, norovirus GI, norovirus GII, enterovirus, and polyomavirus. Quantitative PCR was performed on all samples to determine presence or absence of these viruses in each sample.  Ten DWTPs showed presence of one or more viruses in source water, with four DWTPs having treated drinking water testing positive.  Furthermore, PCR inhibition was assessed for each sample using an exogenous amplification control, which indicated that all of the DWTP samples, including source and treated water samples, had some level of inhibition, confirming that inhibition plays an important role in PCR-based assessments of environmental samples.   PCR inhibition measurements, viral recovery, and other assessments were incorporated into a Bayesian model to more accurately determine viral load in both source and treated water.  Results of the Bayesian model indicated that viruses are present in source water and treated water.  By using a Bayesian framework that incorporates inhibition, as well as many other parameters that affect viral detection, this study offers an approach for more accurately estimating the occurrence of viral pathogens in environmental waters. \n\nThis dataset is associated with the following publication:\nVarughese, E., N. Brinkman, E. Anneken, J. Cashdollar, S. Fout, E. Furlong, D. Kolpin, S. Glassmeyer, and S. Keely. Estimating virus occurrence using Bayesian modeling in multiple drinking water systems of the United States.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 619620: 1330-1339, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407504",
            "keyword": [
                "Bayesian statistics",
                "enteric viruses",
                "drinking water treatment",
                "enterovirus",
                "norovirus",
                "adenovirus"
            ],
            "contactPoint": {
                "fn": "Eunice Varughese",
                "hasEmail": "mailto:varughese.eunice@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure 2 data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407504/Figure%202%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "HepG results.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407504/HepG%20results.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 3 data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407504/Figure%203%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "qPCR master standard curves - Calculations.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407504/qPCR%20master%20standard%20curves%20-%20Calculations.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Summary of Results.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407504/Summary%20of%20Results.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Supplemental-file-2.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407504/Supplemental-file-2.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "Supplemental-file-3.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407504/Supplemental-file-3.txt",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2017-10-26",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2017.10.267"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Links to underwater videos ",
            "description": "Data is a video. Meta data in reprint. \n\nThis dataset is associated with the following publication:\nAngradi, T. A field observation of rotational feeding by Neogobius melanostomus.   Fishes. MDPI AG, Basel,  SWITZERLAND, 3(1): 1-6, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1419037",
            "keyword": [
                "round goby",
                "Dreissena",
                "Great Lakes",
                "video"
            ],
            "contactPoint": {
                "fn": "Theodore Angradi",
                "hasEmail": "mailto:angradi.theodore@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://zenodo.org/record/1157438#.WmhXvKjiaUl",
                    "accessURL": "https://zenodo.org/record/1157438#.WmhXvKjiaUl"
                }
            ],
            "modified": "2018-02-01",
            "references": [
                "https://doi.org/10.3390/fishes3010005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1419037/documents/fishes-03-00005.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Spatial pattern data for NLCD 2001-2011 land cover change accuracy",
            "description": "URL: interested users can create a NLCD 2001-2011 Level I change map and apply Equation listed in table 3 of the Open Access paper published in IJRS (https://doi.org/10.1080/01431161.2017.1410298) to replicate results.\n\nData: excel files of the accuracy assessment results. The data can be used to replicate slope and intercepts reported in IJRS paper. \n\nThis dataset is associated with the following publication:\nWickham, J., S.V. Stehman, and C.G. Homer. Spatial Patterns of NLCD Land Cover Change Thematic Accuracy (2001 - 2011).   INTERNATIONAL JOURNAL OF REMOTE SENSING. Taylor & Francis, Inc., Philadelphia, PA, USA, 39(6): 1729-1743, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1433645",
            "keyword": [
                "land cover change accuracy",
                "logistic regression",
                "NLCD",
                "spatial modeling"
            ],
            "contactPoint": {
                "fn": "James Wickham",
                "hasEmail": "mailto:wickham.james@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.mrlc.gov/",
                    "accessURL": "https://www.mrlc.gov/"
                },
                {
                    "title": "XclFiles.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1433645/XclFiles.zip",
                    "mediaType": "application/zip"
                }
            ],
            "modified": "2018-04-19",
            "references": [
                "https://doi.org/10.1080/01431161.2017.1410298"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "High-resolution Mass Spectrometry of Skin Mucus for Monitoring Physiological Impacts and Contaminant Biotransformation Products in Fathead Minnows Exposed to Wastewater Effluent",
            "description": "High-resolution mass spectrometry is advantageous for monitoring physiological impacts and contaminant biotransformation products in fish exposed to complex wastewater effluent.  We evaluated this technique using skin mucus from male and female fathead minnows (Pimephales promelas) exposed to control water or treated wastewater effluent at 5%, 20%, and 100% levels for 21 d, using an onsite, flow-through system providing real-time exposure.  Both sex-specific and non-sex-specific responses were observed in the mucus metabolome, the latter suggesting the induction of general compensatory pathways for xenobiotic exposures.  Altogether, 85 statistically significant treatment-dependent metabolite changes were observed and 30 of those annotated with probable structures.  The mummichog software package was used to elucidate impacted biochemical pathways and enhance metabolite annotation.  Partial least squares regression models revealed relationships between the mucus metabolomes and upregulated hepatic mRNA transcripts reported previously for these same fish.  These regression models suggest that mucus metabolomic changes reflected, in part, processes by which the fish biotransformed xenobiotics in the effluent.  Further, we detected a phase II transformation product of bisphenol A in the skin mucus of male fish.  Collectively, these findings demonstrate the utility of mucus as a minimally invasive matrix for simultaneously assessing exposures and effects of real-world mixtures of contaminants. \n\nThis dataset is associated with the following publication:\nMosley, J., D. Ekman, J.E. Cavallin, D. Villeneuve, G. Ankley, and T. Collette. High\u2010resolution mass spectrometry of skin mucus for monitoring physiological impacts and contaminant biotransformation products in fathead minnows exposed to wastewater effluent.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(3): 788-796, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1372899",
            "keyword": [
                "Complex Mixtures",
                "biotransformation",
                "Fish Skin Mucus",
                "metabolomics"
            ],
            "contactPoint": {
                "fn": "Drew Ekman",
                "hasEmail": "mailto:ekman.drew@epa.gov"
            },
            "distribution": [
                {
                    "title": "WLSSD 21d FHM Mucus Metabolome Dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1372899/WLSSD%2021d%20FHM%20Mucus%20Metabolome%20Dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-05-16",
            "references": [
                "https://doi.org/10.1002/etc.4003"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Greenspaces and biomarkers of allostatic load",
            "description": "Residential greenness, biomarkers of stress and allostatic load, demographic and health characteristics from 300 subjets. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: See above. Format: Data are stored in SAS and MS Excel. \n\nThis dataset is associated with the following publication:\nEgorov, A., S. Griffin, R. Converse, J. Styles, E. Sams, A. Wilson, L. Jackson, and T. Wade. Vegetated land cover near residence is associated with reduced allostatic load and improved biomarkers of neuroendocrine, metabolic and immune functions.   ENVIRONMENTAL RESEARCH. Academic Press Incorporated, Orlando, FL, USA, 158: 508-21, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390164",
            "keyword": [
                "Greenspace",
                "multiple stressors",
                "allostatic load"
            ],
            "contactPoint": {
                "fn": "Andrey Egorov",
                "hasEmail": "mailto:egorov.andrey@epa.gov"
            },
            "distribution": [],
            "modified": "2017-06-15",
            "references": [
                "https://doi.org/10.1016/j.envres.2017.07.009"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Arden-Literature Review of Constructed Wetlands for greywater recycle and reuse",
            "description": "\u2022\tConstructed wetlands are a low-tech, low energy water treatment alternative that show potential to adequately treat greywater for nonpotable reuse\r\n\u2022\tDespite providing the necessary physical, chemical and biological removal mechanisms for greywater contaminants, removal dynamics are complex and less predictable than more engineered systems\r\n\u2022\tPathogen reductions provided by constructed wetlands alone are likely not reliable enough to meet regulatory standards for reuse, particularly in the US\r\n\u2022\tIf combined with common disinfection technologies (chlorination, UV) constructed wetlands may be an acceptable, low energy alternative for decentralized, nonpotable reuse. \n\nThis dataset is associated with the following publication:\nArden, S., and C. Ma. Constructed Wetlands for Greywater Recycle and Reuse.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 630: 587-599, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407637",
            "keyword": [
                "constructed wetlands",
                "water reuse",
                "nonpotable water",
                "low energy water treatment",
                "greywater reuse",
                "pathogen and chemical risks"
            ],
            "contactPoint": {
                "fn": "Xin Ma",
                "hasEmail": "mailto:ma.cissy@epa.gov"
            },
            "distribution": [
                {
                    "title": "Arden - Literature Review Manuscript Draft - Figures.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407637/Arden%20-%20Literature%20Review%20Manuscript%20Draft%20-%20Figures.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Arden - Literature Review Manuscript Draft.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407637/Arden%20-%20Literature%20Review%20Manuscript%20Draft.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Arden - Literature Review.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407637/Arden%20-%20Literature%20Review.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-18",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.02.218"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Rapid Effects of the Aromatase Inhibitor Fadrozole on Steroid Production and Gene Expression in the Ovary of Female Fathead Minnows (Pimephales promelas)",
            "description": "Aromatase inhibition is one of the chemical modes of action of concern to EPA's Endocrine Disruptor Screening Program (EDSP). In vitro bioassays that can detect aromatase inhibition are part of both the EDSP tier 1 screening program and are included subset of ToxCast assays employed for EDSP21 screening. An adverse outcome pathway (AOP) linking aromatase inhibition to reproductive dysfunction in fish has been described and endorsed by the OECD, establishing a scientifically sound connection between aromatase inhibition and adverse apical outcomes relevant to risk assessment and regulatory decision-making. Further, computational models that allow for quantitative prediction of dose-response time-course behaviors and the potential severity of the adverse outcome based on in vitro screening data have been developed. The present study provides further weight of evidence to support this AOP and its use in regulatory decision-making. In particular, it identifies rapid responses to aromatase inhibition that can be expected to occur within the first 24 h of exposure, examines the dynamic stability of gene expression responses over that period to help identify appropriate time periods in which characteristic gene expression responses may serve as effective biomarkers of exposure to aromatase inhibitors, and provides insights into different gene regulatory mechanisms that may be operating over the first few hours of exposure versus more systemic endocrine-related regulation that appear to take over after 6-12 h of exposure. These data continue to refine our understanding of this important mode of endocrine disruption and how to more efficiently and effectively both model and test for it to support regulatory decision-making. \n\nThis dataset is associated with the following publication:\nSchroeder, A., G. Ankley, T. Habib, N. Garcia-Reyero, B. Escalon, K. Jensen, M. Kahl, E. Durhan, E. Makynen, J. Cavallin, D. Martinovic-Weigelt, E. Perkins, and D. Villeneuve. Rapid effects of the aromatase inhibitor fadrozole on steroid production and gene expression in the ovary of female fathead minnows (Pimephales promelas).   GENERAL AND COMPARATIVE ENDOCRINOLOGY. Academic Press Incorporated, Orlando, FL, USA, 252: 79-87, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1390114",
            "keyword": [
                "transcriptomics",
                "adverse outcome pathway",
                "ecotoxicology",
                "endocrine disruption",
                "screening and prioritization",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "6,12, 24 hour Fad quantile normalized.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390114/6%2C12%2C%2024%20hour%20Fad%20quantile%20normalized.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "Fad 0-6h quantile normalized data from GeneSpring.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390114/Fad%200-6h%20quantile%20normalized%20data%20from%20GeneSpring.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "FAD 6_12_24h GSI CHEM STEROIDS for Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390114/FAD%206_12_24h%20GSI%20CHEM%20STEROIDS%20for%20Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "FAD 0-6 h time course data for Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390114/FAD%200-6%20h%20time%20course%20data%20for%20Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "FAD 0-24 h QPCR data for Science Hub 02-10-2017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390114/FAD%200-24%20h%20QPCR%20data%20for%20Science%20Hub%2002-10-2017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Supplementary Tables for Fadrozole 2017-01-31.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390114/Supplementary%20Tables%20for%20Fadrozole%202017-01-31.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "GEO Accession Information.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390114/GEO%20Accession%20Information.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-02-23",
            "references": [
                "https://doi.org/10.1016/j.ygcen.2017.07.022"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Excel spreadsheet of data used in Figure 3",
            "description": "Distribution of doses of a volatile organic compound from inhalation of one consumer product, other near -field sources, far-field sources, and aggregate (total) exposure. In this instance, far-field scenarios account for several orders of magnitude of less of the predicted dose compared to near-field scenarios. \n\nThis dataset is associated with the following publication:\nVallero, D. Air Pollution Monitoring Changes to Accompany the Transition from a Control to a Systems Focus.   Sustainability. MDPI AG, Basel,  SWITZERLAND, 8(12): 1216, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1434939",
            "keyword": [
                "air pollution exposure",
                "near-field exposure",
                "life cycle assessment",
                "microenvironment",
                "exposure-based screening"
            ],
            "contactPoint": {
                "fn": "Daniel Vallero",
                "hasEmail": "mailto:vallero.daniel@epa.gov"
            },
            "distribution": [
                {
                    "title": "Chin Csisar based SHEDs modeling results.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434939/Chin%20Csisar%20based%20SHEDs%20modeling%20results.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-04-27",
            "references": [
                "https://doi.org/10.3390/su8121216"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1434939/documents/Chin%20Csisar%20based%20SHEDs%20modeling%20results.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "SHP-2 Mediates Cryptosporidium parvum Infectivity in Human Intestinal Epithelial Cells",
            "description": "The metadata include quantifications of western blots and values for number of infections when using various inhibitors.  The quantification data are included in one spreadsheet labeled \u201cWestern Blot quants\u201d and the infection data is included in another spreadsheet labeled \u201cInhibitor quants\u201d. \n\nThis dataset is associated with the following publication:\nVarughese , E., S. Kasper, E. Anneken, and J. Yadav. SHP-2 Mediates Cryptosporidium parvum Infectivity in Human Intestinal Epithelial Cells.   PLoS ONE. Public Library of Science, San Francisco, CA, USA, 10(11): e0142219, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390089",
            "keyword": [
                "cryptosporidium",
                "virulence factor",
                "infection",
                "SHP2",
                "paxillin",
                "in vitro"
            ],
            "contactPoint": {
                "fn": "Eunice Varughese",
                "hasEmail": "mailto:varughese.eunice@epa.gov"
            },
            "distribution": [
                {
                    "title": "Western Blot quants.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390089/Western%20Blot%20quants.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Inhibitor quants.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390089/Inhibitor%20quants.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-07-10",
            "references": [
                "https://doi.org/10.1371/journal.pone.0142219"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The mouse thermoregulatory system: Its impact on translating biomedical data to humans",
            "description": "Ambient temperature vs.Core temperature. \n\nThis dataset is associated with the following publication:\nGordon, C. THE MOUSE THERMOREGULATORY SYSTEM:\r\nITS IMPACT ON TRANSLATING BIOMEDICAL DATA TO HUMANS.   Physiology & Behavior. Elsevier B.V., Amsterdam,  NETHERLANDS,  55-66, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407598",
            "keyword": [
                "behavior",
                "core temperature",
                "extrapolation",
                "hypothermia",
                "metabolic rate",
                "preferred temperature",
                "thermal conductance"
            ],
            "contactPoint": {
                "fn": "Christopher Gordon",
                "hasEmail": "mailto:gordon.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "The mouse thermoregulatory system - Its impact on translating biomedical data to humans.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407598/The%20mouse%20thermoregulatory%20system%20-%20Its%20impact%20on%20translating%20biomedical%20data%20to%20humans.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-28",
            "references": [
                "https://doi.org/10.1016/j.physbeh.2017.05.026"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Indianapolis Research Duplex Total Database",
            "description": "Complete database for research conducted at the EPA's research house in Indianapolis, IN.  Data contained includes weather parameters, sampling dates/times/method, and resultant VOC contaminants. \n\nThis dataset is associated with the following publication:\nLutes, C., R. Truesdale, B. Cosky, J. Zimmerman , and B. Schumacher. Comparing Vapor Intrusion Mitigation System Performance for VOCs and Radon.   Remediation Journal. John Wiley & Sons, Inc., Hoboken, NJ, USA, 25(7): 7-26, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390081",
            "keyword": [
                "radon",
                "vapor intrusion",
                "mitigation",
                "monitoring"
            ],
            "contactPoint": {
                "fn": "Brian Schumacher",
                "hasEmail": "mailto:schumacher.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "TO-013_Database_March_2014.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390081/TO-013_Database_March_2014.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-09-15",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Water stable isotopes data from Pipestem Creek, North Dakota, 2014-2015",
            "description": "Water stable isotope data (hydrogen and oxygen isotopes of H2O) from wetlands and streams within the Pipestem Creek watershed.  This data was collected over two open water seasons (May-September): 2014 and 2015. \n\nThis dataset is associated with the following publication:\nBrooks, J.R., D. Mushet, M. Vanderhoof, S. Leibowitz, J. Christensen, B. Neff, D. Rosenberry, W. Rugh, and L. Alexander. Estimating wetland connectivity to streams in the Prairie Pothole Region: an isotopic and remote sensing approach.   WATER RESOURCES RESEARCH. American Geophysical Union, Washington, DC, USA, 54(2): 995-977, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407662",
            "keyword": [
                "connectivity",
                "wetlands",
                "stable isotope analsis",
                "evaporation"
            ],
            "contactPoint": {
                "fn": "Jacqueline Brooks",
                "hasEmail": "mailto:brooks.reneej@epa.gov"
            },
            "distribution": [
                {
                    "title": "SSWR 3.01G Prairie Pothole Isotope & QA Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407662/SSWR%203.01G%20Prairie%20Pothole%20Isotope%20%26%20QA%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-10-03",
            "references": [
                "https://doi.org/10.1002/2017wr021016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Coupling of organic and inorganic systems and the effect on gas-particle partitioning in the southeastern United States",
            "description": "Several models were used to describe the partitioning of ammonia, water, and organic compounds between the gas and particle phases for conditions in the southeastern US during summer 2013. Existing equilibrium models and frameworks were found to be sufficient, although additional improvements in terms of estimating pure-species vapor pressures are needed. Thermodynamic model predictions were consistent, to first order, with a molar ratio of ammonium to sulfate of approximately 1.6 to 1.8 (ratio of ammonium to 2\u202f\u2009\u00d7\u2009\u202fsulfate, RN\u22152S\u202f\u2009\u2248\u2009\u202f0.8 to 0.9) with approximately 70\u202f% of total ammonia and ammonium (NHx) in the particle. Southeastern Aerosol Research and Characterization Network (SEARCH) gas and aerosol and Southern Oxidant and Aerosol Study (SOAS) Monitor for AeRosols and Gases in Ambient air (MARGA) aerosol measurements were consistent with these conditions. CMAQv5.2 regional chemical transport model predictions did not reflect these conditions due to a factor of 3 overestimate of the nonvolatile cations. In addition, gas-phase ammonia was overestimated in the CMAQ model leading to an even lower fraction of total ammonia in the particle. Chemical Speciation Network (CSN) and aerosol mass spectrometer (AMS) measurements indicated less ammonium per sulfate than SEARCH and MARGA measurements and were inconsistent with thermodynamic model predictions. Organic compounds were predicted to be present to some extent in the same phase as inorganic constituents, modifying their activity and resulting in a decrease in [H+]air (H+ in \u00b5g\u202fm\u22123 air), increase in ammonia partitioning to the gas phase, and increase in pH compared to complete organic vs. inorganic liquid\u2013liquid phase separation. In addition, accounting for nonideal mixing modified the pH such that a fully interactive inorganic\u2013organic system had a pH roughly 0.7 units higher than predicted using traditional methods (pH\u202f\u2009=\u2009\u202f1.5 vs. 0.7). Particle-phase interactions of organic and inorganic compounds were found to increase partitioning towards the particle phase (vs. gas phase) for highly oxygenated (O\u202f:\u202fC\u202f\u2009\u2265\u2009\u202f0.6) compounds including several isoprene-derived tracers as well as levoglucosan but decrease particle-phase partitioning for low O\u202f:\u202fC, monoterpene-derived species. \n\nThis dataset is associated with the following publication:\nPye, H., W. Appel, H. Foroutan, A. Zuend, J. Fry, G. Isaacman-VanWertz , N.L. Ng, A. Goldstein, S. Capps, and L. Xu. Coupling of organic and inorganic aerosol systems and the effect on gas\u2013particle partitioning in the southeastern US.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 18: 357-370, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1422410",
            "keyword": [
                "Aerosol",
                "sulfate",
                "Ammonium",
                "SOAS",
                "SOA",
                "nitrogen",
                "ammonia",
                "Secondary Organic Aerosol",
                "levoglucosan"
            ],
            "contactPoint": {
                "fn": "Havala Pye",
                "hasEmail": "mailto:pye.havala@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.atmos-chem-phys.net/18/357/2018/acp-18-357-2018.html",
                    "accessURL": "https://www.atmos-chem-phys.net/18/357/2018/acp-18-357-2018.html"
                },
                {
                    "title": "https://github.com/USEPA/CMAQ/",
                    "accessURL": "https://github.com/USEPA/CMAQ/"
                },
                {
                    "title": "https://esrl.noaa.gov/csd/groups/csd7/measurements/2013senex/",
                    "accessURL": "https://esrl.noaa.gov/csd/groups/csd7/measurements/2013senex/"
                },
                {
                    "title": "pye_acp-18-357-2018.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1422410/pye_acp-18-357-2018.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-02-13",
            "references": [
                "https://doi.org/10.5194/acp-18-357-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "VIC soil moisture for MRB",
            "description": "50-yr VIC model output for MRB. \n\nThis dataset is associated with the following publication:\nTang, C., and D. Chen. Interaction between Soil Moisture and Air Temperature in the Mississippi River Basin.   Journal of Water Resource and Protection. Scientific Research Publishing, Inc., Irvine, CA, USA, 9(10): 1119-1131, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1415933",
            "keyword": [
                "soil moisture",
                "surfact temperture",
                "runoff",
                "baseflow",
                "air temperature",
                "quantile regression model",
                "wavelet transform coherency",
                "climate change (extremes"
            ],
            "contactPoint": {
                "fn": "Chunling Tang",
                "hasEmail": "mailto:tang.chunling@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHub-details.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1415933/ScienceHub-details.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-03",
            "references": [
                "https://doi.org/10.4236/jwarp.2017.910073"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Zebrafish Locomotor Responses Reveal Irritant Effects of Fine PM Extracts and a Role for TRPA1",
            "description": "This dataset contains 60-min locomotor response data for all control, chemical and particulate-extract-treated zebrafish. \n\nThis dataset is associated with the following publication:\nStevens, J., S. Padilla, D. DeMarini, D. Hunter, K. Martin, L. Thompson, I. Gilmour, M. Hazari, and A. Farraj. Zebrafish Locomotor Responses Reveal Irritant Effects of Fine Particulate Matter Extracts and a Role for TRPA1.   TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA,  161(2): 290-299, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1376224",
            "keyword": [
                "air pollution",
                "particulate matter",
                "Diesel Exhaust",
                "organic extracts",
                "health",
                "zebrafish",
                "locomotor",
                "behavior",
                "irritant responses",
                "TRPA1"
            ],
            "contactPoint": {
                "fn": "Aimen Farraj",
                "hasEmail": "mailto:farraj.aimen@epa.gov"
            },
            "distribution": [
                {
                    "title": "Zebrafish behavior_CDEP_All data_May2017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376224/Zebrafish%20behavior_CDEP_All%20data_May2017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-05-30",
            "references": [
                "https://doi.org/10.1093/toxsci/kfx217"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The development and implementation of a method using blue mussels (Mytilus spp.) as biosentinels of Cryptosporidium spp. and Toxoplasma gondii contamination in marine aquatic environments",
            "description": "Data set includes occurrence and genotypes of T. gondii and Cryptosporidium species found in central California coastlines. \n\nThis dataset is associated with the following publication:\nStaggs , S., S. Keely , M. Ware , N. Schable, M. See , D. Gregorio, X. Zou, C. Su, J.P. Dubey, and E. Villegas. The development and implementation of a method using blue mussels (Mytilus spp.) as biosentinels of Cryptosporidium spp. and Toxoplasma gondii contamination in marine aquatic environments.   Parasitology Research. Springer, New York, NY, USA, 114(12): 4655-4667, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1390090",
            "keyword": [
                "mussel",
                "bivalve",
                "Toxoplasma gondii",
                "cryptosporidium",
                "Methods development",
                "surface water",
                "water quality"
            ],
            "contactPoint": {
                "fn": "Eric Villegas",
                "hasEmail": "mailto:villegas.eric@epa.gov"
            },
            "distribution": [
                {
                    "title": "Staggs_data_scihub-vDDS.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390090/Staggs_data_scihub-vDDS.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-12",
            "references": [
                "https://doi.org/10.1007/s00436-015-4711-9"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Determining Pathogen and Indicator Levels in Class B Municipal Organic Residuals Used for Land Application",
            "description": "Biosolids are nutrient rich organic residuals that are currently used to amend soils for food production.  Treatment requirements to inactivate pathogens for production of Class A biosolids are energy intensive.  One less energy intensive alternative is to treat biosolids to Class B standards, but it could result in higher pathogen loads.  Quantitative microbial risk assessments models have been developed on land application of Class B biosolids, but contain many uncertainties because of limited data on specific pathogen densities and the use of fecal indicator organisms as accurate surrogates of pathogen loads.   To address this gap, a 12-month study of the levels and relationships between Cryptosporidium, Giardia, and human adenovirus (HAdV) with fecal coliform, somatic and F-RNA coliphage levels in Class B biosolids from nine wastewater treatment plants throughout the United States was conducted.  Results revealed that fecal coliform, somatic, and F-RNA coliphage densities were consistent throughout the year.  More importantly, results revealed that HAdV (\uf7c2=2.5x103 genome copies/dry g) and Giardia (\uf7c2=4.14 x103 cysts/dry g) were in all biosolids samples regardless of treatment processes, location, or season.  Cryptosporidium oocysts were also detected (38 % positive; range: 0 -1.9 x 103 oocysts/dry g), albeit sporadically.  Positive correlations among three fecal indicator organisms and HAdV, but not protozoa, were also observed.  Overall, study reveals the high concentrations of enteric pathogens (e.g., Cryptosporidium, Giardia, and HAdV) are present in biosolids throughout the US.  Microbial densities found can further assist management and policy makers establish more accurate risk assessment models associated with land application of Class B biosolids. \n\nThis dataset is associated with the following publication:\nRhodes , E., L. Boczek , M. Ware , M. McKay, J. Hoelle , M. Schoen, and E. Villegas. Determining pathogen and indicator levels in Class B municipal organic residuals used for land application.   JOURNAL OF ENVIRONMENTAL QUALITY. American Society of Agronomy, MADISON, WI, USA, 44(1): 265-274, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390080",
            "keyword": [
                "biosolids",
                "giardia",
                "cryptosporidium",
                "fecal indicator bacteria",
                "organic residual",
                "wastewater",
                "occurrence"
            ],
            "contactPoint": {
                "fn": "Eric Villegas",
                "hasEmail": "mailto:villegas.eric@epa.gov"
            },
            "distribution": [
                {
                    "title": "VillegasEric_A-ftts_data_20160720.docx.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390080/VillegasEric_A-ftts_data_20160720.docx.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-01-29",
            "references": [
                "https://doi.org/10.2134/jeq2014.04.0142"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supporting data for \"Stuhldreher, M., Kargul, J., Barba, D., McDonald, J. et al. 2018. Benchmarking a 2016 Honda Civic 1.5-liter L15B7 Turbocharged Engine and Evaluating the Future Efficiency Potential of Turbocharged Engines, SAE 2018-01-0319\" V1",
            "description": "A 2016 Honda Civic with a 4-cylinder 1.5-liter L15B7 turbocharged engine and continuously variable transmission (CVT) was benchmarked. The test method involved installing the engine and its CVT in an engine dynamometer test cell with the engine wiring harness tethered to its vehicle parked outside\nthe test cell. Engine and transmission torque, fuel flow, key engine temperatures and pressures, and onboard diagnostics\n(OBD)/CAN bus data were recorded. The paper published as part of this work documents the test results for idle, low,\nmedium and high load engine operation, as well as motoring\ntorque, wide-open throttle torque and fuel consumption during transient operation using both EPA Tier 2 and Tier 3 test\nfuels. Particular attention is given to characterizing enrichment\ncontrol during high load engine operation. Results have been used to create complete engine fuel consumption and efficiency maps and estimate CO2 emissions using EPA\u2019s ALPHA full vehicle simulation model, over regulatory drive cycles. Within the published paper, the design and performance of the 1.5-liter Honda engine are compared to several other past, present, and future downsized-boosted engines and potential advancements were evaluated. \n\nThis dataset is associated with the following publication:\nDekraker, P., S. Bohac, J. McDonald, J. Kargul, and D. Barba. Benchmarking a 2016 Honda Civic 1.5L Turbo Engine and Evaluating the Future Efficiency Potential of Turbocharged Engines.   SAE Technical Paper Series. SAE International, Warrendale, PA, USA,  34, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1435430",
            "keyword": [
                "GHG",
                "Light-duty Vehicles",
                "air quality",
                "Energy Demand",
                "Internal Combustion Engines",
                "Hybrid Electric Vehicles",
                "Electric Vehicles"
            ],
            "contactPoint": {
                "fn": "Joseph McDonald",
                "hasEmail": "mailto:mcdonald.joseph@epa.gov"
            },
            "distribution": [
                {
                    "title": "SAE 2018-01-0319 Honda L15B7 Engine.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435430/SAE%202018-01-0319%20Honda%20L15B7%20Engine.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-05-01",
            "references": [
                "https://doi.org/10.4271/2018-01-0319"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Biofiltration of trihalomethanes stripped from chlorinated drinking water ",
            "description": "This study examined the removal of chloroform under two environmental conditions (anaerobic and aerobic), and in the presence of ethanol as co-metabolite.  Investigations of the biological community structure within the BTFs were also conducted. The use of aerobic fungi BTF under acidic condition successfully enhanced the biodegradation process of chloroform. The BTF provided more stable performance by having smaller standard deviation in the removal efficiency as compared to the anaerobic BTF. Hence, acidic aerobic BTF had achieved significant improvement in the removal of chloroform. \n\nThis dataset is associated with the following publication:\nSahle-Demessie, E., J. Lu, B. Mezgebe, and G. Sorial. Performance of Anaerobic Biotrickling Filter and Its Microbial Diversity for the Removal of Stripped Disinfection By-products.   INTERNATIONAL JOURNAL OF ENVIRONMENTAL POLLUTION. Universidad Nacional Autonoma de Mexico,    228: 437, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407602",
            "keyword": [
                "trihalomethanes",
                "disinfection byproducts",
                "biofiltration",
                "choloform",
                "Aerobic",
                "anaerobic",
                "Biotrickling Filter",
                "Microbial diversity"
            ],
            "contactPoint": {
                "fn": "Endalkac Sahle-Demessie",
                "hasEmail": "mailto:sahle-demessie.endalkachew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Mezgebe-comparative-paper REVISED_June2017_Rev.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407602/Mezgebe-comparative-paper%20REVISED_June2017_Rev.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Mezgebe-comparative paper2 Table 1.doc",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407602/Mezgebe-comparative%20paper2%20Table%201.doc",
                    "mediaType": "application/msword"
                },
                {
                    "title": "Mezgebe-comparative-paper-Figures - Revised.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407602/Mezgebe-comparative-paper-Figures%20-%20Revised.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-05-01",
            "references": [
                "https://doi.org/10.1007/s11270-017-3616-x"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1407602/documents/Data%20Dictionary_BiotrickleFiltration.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Seasonal Variation of Natural Organic Matter influence on the fate and transport of engineered nanomaterials",
            "description": "This study characterized Ohio river natural organic matter (NOM) during winter and summer times, and demonstrated the effects of these NOM samples on stability and transport of ceria nanoparticles in saturated porous media. Ohio river NOM samples that were characterized by thermal analysis, spectroscopic method, solid state NMR spectrometer and elemental analysis showed to have structural and compositional differences from standard humic acid that is used for laboratory tests,  This study explored the effects of Ohio river NOM in enhancing the transport and breakthrough of ceria nanoparticles in moderate (1-10 mM) ionic strength solutions. The enhancement in stability and transport appear to be dominated by the altered electrokinetic properties of the ceria NPs. \n\nThis dataset is associated with the following publication:\nLi, Z., E. Sahle-Demessie, A. Aly Hassan, J. Pressman, C. Han, and G. Sorial. Effects of source and seasonal variations of natural organic matters on the fate and transport of CeO2 nanoparticles in the environment.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 609: 1616-1626, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407604",
            "keyword": [
                "Engineered nanoparticles (NP)",
                "natural organic matter",
                "Ohio River",
                "Nanoparticles",
                "CeO2",
                "ssNMR-FTIR",
                "packed-column transport"
            ],
            "contactPoint": {
                "fn": "Endalkac Sahle-Demessie",
                "hasEmail": "mailto:sahle-demessie.endalkachew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Effects of source and seasonal variations of natural organic matters on the fate and transport of CeO2 nanoparticles i.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407604/Effects%20of%20source%20and%20seasonal%20variations%20of%20natural%20organic%20matters%20on%20the%20fate%20and%20transport%20of%20CeO2%20nanoparticles%20i.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Supplementary Data_NOM_CeO2_PPR.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407604/Supplementary%20Data_NOM_CeO2_PPR.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-03-01",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2017.07.154"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1407604/documents/Seasonal%20Variation%20of%20NOM_Data%20Dictionary.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Polypropylene-MWCNT degradation and Nanomaterials release",
            "description": "Degradation kinetics of nanocomposite in the environment.  Nano-polymer composites are exposed to sunlight and oxidizing conditions that cause weathering of the polymers, leading to degradation and the release of nanoparticles. \n\nThis dataset is associated with the following publication:\nHan, C., E. Sahle-Demessie, A. Zhao, T. Richardson, and J. Wang. Environmental aging and degradation of multiwalled carbon nanotube reinforced polypropylene.   CARBON. Pergamon Press Ltd., New York, NY, USA, 129: 137-151, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407600",
            "keyword": [
                "degradation",
                "nanocomposites",
                "nanorelease",
                "engineered nanomaterials",
                "multiwalled carbon nanotubes",
                "environmental degredation"
            ],
            "contactPoint": {
                "fn": "Endalkac Sahle-Demessie",
                "hasEmail": "mailto:sahle-demessie.endalkachew@epa.gov"
            },
            "distribution": [
                {
                    "title": "PP_MWCNT_Degradation_TEXT_August2017.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407600/PP_MWCNT_Degradation_TEXT_August2017.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "PP_MWCNT_Degradation_Figure_August2017.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407600/PP_MWCNT_Degradation_Figure_August2017.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "G-STD-0010591-JA-12-1_Supp_Info.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407600/G-STD-0010591-JA-12-1_Supp_Info.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "PP_MWCNT_Degradation_Table_August2017.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407600/PP_MWCNT_Degradation_Table_August2017.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-08-01",
            "references": [
                "https://doi.org/10.1016/j.carbon.2017.10.038"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1407600/documents/Data%20Dictionary_MWCNT_PlolymerComposite.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Linking Field-based Metabolomics and Chemical Analyses to Prioritize Contaminants of Emerging Concern in the Great Lakes Basin",
            "description": "Matrix of contaminant measurements and endogenous metabolite intensities (measured by NMR). \n\nThis dataset is associated with the following publication:\nDavis, J., D. Ekman, Q. Teng , G. Ankley , J. Berninger , J. Cavallin , K. Jensen , M. Kahl , A. Schroeder , D. Villeneuve , Z. Jorgenson, K. Lee, and T. Collette. Linking field-based metabolomics and chemical analyses to prioritize contaminants of emerging concern in the Great Lakes basin.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 35(10): 2493\u20132502, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1389783",
            "keyword": [
                "Great Lakes",
                "chemicals of emerging concern",
                "nuclear magnetic resonance spectroscopy",
                "Fathead minnows",
                "metabolomics"
            ],
            "contactPoint": {
                "fn": "Drew Ekman",
                "hasEmail": "mailto:ekman.drew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Davis et al._2016_ET&C.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1389783/Davis%20et%20al._2016_ET%26C.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-04-30",
            "references": [
                "https://doi.org/10.1002/etc.3409"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1389783/documents/Data%20Dictionary%20for%20Davis%20et%20al.%202017_Input%20File.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Metabolite profiles of repeatedly sampled urine from male fathead minnows (Pimephales promelas) contain unique lipid signatures following exposure to anti-androgens",
            "description": "The purpose of this study was twofold. First, we sought to identify candidate markers of exposure to antiandrogens\r\nby analyzing endogenous metabolite profiles in the urine of male fathead minnows (mFHM,\r\nPimephales promelas). Based on earlier work, we hypothesized that unidentified lipids in the urine of mFHM\r\nwere selectively responsive to exposure to androgen receptor antagonists,which is otherwise difficult to confirm\r\nusing established fish toxicity assays. A second goal was to evaluate the feasibility of non-lethally and repeatedly\r\nsampling urine from individual mFHMs over the time course of response to a chemical exposure. Accordingly, we\r\nexposed mFHM to the model anti-androgens vinclozolin or flutamide. Urine was collected from each fish at\r\n48 hour intervals over the course of a 14 day exposure. Parallel experiments were conducted with mFHM exposed\r\nto bisphenol A or control water. The frequent handling/sampling regime did not cause apparent adverse\r\neffects on the fish. Endogenous metabolite profiling was conducted with gas chromatography\u2013mass spectrometry\r\n(GC\u2013MS), which exhibited lower variation for the urinary metabolome than was found in earlier work with\r\nnuclear magnetic resonance (NMR) spectroscopy. Specifically, for inter- and intra-individual variations, the median\r\nspectrum-wide relative standard deviation (RSD) was 32.6% and 33.3%, respectively, for GC\u2013MS analysis of\r\nurine from unexposed mFHM. These results compared favorably with similar measurements of urine from other\r\nmodel species, including the Sprague Dawley rat. In addition, GC\u2013MS allowed us to identify several lipids\r\n(e.g., certain saturated fatty acids) in mFHM urine as candidate markers of exposure to androgen receptor\r\nantagonists.\r\nThe dataset that is uploaded here is the complete processed data from GC-MS instrument. \n\nThis dataset is associated with the following publication:\nCollette , T., D. Skelton, J. Davis , J. Cavallin , K. Jensen , M. Kahl , G. Ankley , G. Ankley , D. Martinovic-Weigelt, and D. Ekman. Metabolite profiles of repeatedly sampled urine from male fathead minnows (Pimephales promelas) contain unique lipid signatures following exposure to anti-androgens.   COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY - PART D: GENOMICS AND PROTEOMICS. Elsevier BV, AMSTERDAM,  NETHERLANDS, 19: 190-198, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1396186",
            "keyword": [
                "anti-androgens",
                "metabolomics"
            ],
            "contactPoint": {
                "fn": "Drew Ekman",
                "hasEmail": "mailto:ekman.drew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Final dataset_RUS study.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1396186/Final%20dataset_RUS%20study.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-04-17",
            "references": [
                "https://doi.org/10.1016/j.cbd.2016.01.001"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1396186/documents/Data%20Dictionary%20for%20Collette%20et%20al._repeately%20sample%20urine_Input%20File.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A Nitrogen Physical Input-Output Model for Illinois",
            "description": "This file provides all the data that was used to estimate the physical input outputs for the State of Illinois.  The attached paper describes how the data was collected and provides all the metadata. \n\nThis dataset is associated with the following publication:\nSingh, S., J. Compton, T. Hawkins, D. Sobota, and E. Cooter. A Nitrogen Physical Input-Output Table (PIOT) Model for Illinois.   ECOLOGICAL MODELLING. Elsevier Science BV, Amsterdam,  NETHERLANDS, 360: 194-203, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1407646",
            "keyword": [
                "illinois",
                "nitrogen",
                "life cycle assessment",
                "input-output data"
            ],
            "contactPoint": {
                "fn": "Jana Compton",
                "hasEmail": "mailto:compton.jana@epa.gov"
            },
            "distribution": [
                {
                    "title": "Singh et al. 2017 Ecol Modell Supp Data.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407646/Singh%20et%20al.%202017%20Ecol%20Modell%20Supp%20Data.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Singh et al. 2017 Ecol Modell N PIOT.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407646/Singh%20et%20al.%202017%20Ecol%20Modell%20N%20PIOT.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2017-01-31",
            "references": [
                "https://doi.org/10.1016/j.ecolmodel.2017.06.015"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Linking terrestrial phosphorus inputs to riverine export across the US",
            "description": "Phosphorus inputs to the landscape from fertilizer and manure inputs, P surplus and P removal by crop harvest and hydrologic export.  The input layers are now available on EPA's EnviroAtlas under Pollutants: Nutrients and specifically the layers include 1) Phosphorus application as manure and 2) Phosphorus fertilizer application. \n\nThis dataset is associated with the following publication:\nMetson, G., J. Lin, J.A. Harrison, and J. Compton. Linking terrestrial phosphorus inputs to riverine export across the United States.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 124: 177-191, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1407649",
            "keyword": [
                "manure",
                "crop harvest P",
                "fertilizer P",
                "surplus P",
                "nutrients",
                "algal blooms",
                "phosphorus",
                "water quality",
                "legacies"
            ],
            "contactPoint": {
                "fn": "Jana Compton",
                "hasEmail": "mailto:compton.jana@epa.gov"
            },
            "distribution": [
                {
                    "title": "SI Tables_Jan19.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407649/SI%20Tables_Jan19.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "FactSheetphosphorus_crop_uptake_V2.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407649/FactSheetphosphorus_crop_uptake_V2.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "FactSheetphosphorus_fertilizer_v2.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407649/FactSheetphosphorus_fertilizer_v2.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "FactSheetphosphorus_agricultural_balance_V2.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407649/FactSheetphosphorus_agricultural_balance_V2.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "FactSheetphosphorus_manure V2.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407649/FactSheetphosphorus_manure%20V2.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-02-01",
            "references": [
                "https://doi.org/10.1016/j.watres.2017.07.037"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Metabolism of Diazinon in Rainbow Trout Liver Slices version 1 Tapper A-12jq 09122017",
            "description": "Understanding biotransformation pathways in aquatic species is an integral part of ecological risk assessment with respect to the potential bioactivation of chemicals to more toxic metabolites. The long-range goal is to gain sufficient understanding of fish metabolic transformation reactions to be able to accurately predict fish xenobiotic metabolism. While some metabolism data exist, there are few fish in vivo exposure studies where metabolites have been identified and the metabolic pathways proposed. Previous biotransformation work has focused on in vitro studies which have the advantage of high throughput but may have limited metabolic capabilities, and in vivo studies which have full metabolic capacity but are low throughput. An aquatic model system with full metabolic capacity in which a large number of chemicals could be tested would be a valuable tool. The current study evaluated the ex vivo rainbow trout liver slice model, which has the advantages of high throughput as found in vitro models and non-dedifferentiated cells and cell to cell communication found in in vivo systems. The pesticide diazinon, which has been previously tested both in vitro and in vivo in a number of mammalian and aquatic species including rainbow trout, was used to evaluate the ex vivo slice model as a tool to study biotransformation pathways. While somewhat limited by the analytical chemistry method employed, results of the liver slice model, mainly that hydroxypyrimidine was the major diazinon metabolite, are in line with the results of previous rainbow trout in vivo studies. Therefore, the rainbow trout liver slice model is a useful tool for the study of metabolism in aquatic species. \n\nThis dataset is associated with the following publication:\nTapper, M., J. Serrano, P. Schmieder, D. Hammermeister, and R. Kolanczyk. Metabolism of diazinon in rainbow trout liver slices.   Applied In Vitro Toxicology. Mary Ann Liebert, Inc., Larchmont, NY, USA, 4(1): 13-23, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1389587",
            "keyword": [
                "Metabolism",
                "trout",
                "liver slices",
                "diazinon",
                "biotransformation"
            ],
            "contactPoint": {
                "fn": "Mark Tapper",
                "hasEmail": "mailto:tapper.mark@epa.gov"
            },
            "distribution": [
                {
                    "title": "Tapper A-12jq-Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1389587/Tapper%20A-12jq-Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-12",
            "references": [
                "https://doi.org/10.1089/aivt.2017.0025"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "NEEAR Water Study",
            "description": "Epidemiological data from the NEEAR Water Study. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Request from Tim Wade- wade.tim@epa.gov. Format: Data are stored in comma-delimited databases. \n\nThis dataset is associated with the following publications:\nWade, T., S. Augustine, S. Griffin, E. Sams, K. Oshima, A. Egorov, K. Simmons, T. Eason, and A. Dufour. Asymptomatic norovirus infection associated with swimming at a tropical beach: A prospective cohort study.   PLoS ONE. Public Library of Science, San Francisco, CA, USA, 13(3): e0195056, (2018).\nDeflorio-Barker, S., B. Arnold, E. Sams, A. Dufour, J. Colford, S. Weisberg, K. Schiff, and T. Wade. Child environmental exposures to water and sand at the beach: Findings from studies of over 60,000 subjects at 12 beaches.   Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London,  UK, 28(2): 93-100, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1375932",
            "keyword": [
                "beach water quality",
                "swimming",
                "diarrhea"
            ],
            "contactPoint": {
                "fn": "Timothy Wade",
                "hasEmail": "mailto:wade.tim@epa.gov"
            },
            "distribution": [],
            "modified": "2015-04-15",
            "references": [
                "https://doi.org/10.1371/journal.pone.0195056",
                "https://doi.org/10.1038/jes.2017.23"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "All raw data used to generate results",
            "description": "This dataset contains all data used in this study, including site ID, latitude, longitude, watershed land cover, water chemistry, and carbon and nitrogen stable isotope ratios of periphyton, invertebrate functional feeding groups, and five most frequently observed invertebrate families. Also included is a list of all invertebrates collected in this study along with their functional feeding group and stable isotope ratios. \n\nThis dataset is associated with the following publication:\nSmucker, N., A. Kuhn, C. Cruz-Quinones, J. Serbst, and J. Lake. Stable isotopes of algae and macroinvertebrates in streams respond to watershed urbanization, inform management goals, and indicate food web relationships.   ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 90: 295-304, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1434636",
            "keyword": [
                "nitrogen",
                "Algae",
                "benthic macroinvertebrates",
                "nutrients",
                "watersheds",
                "land cover",
                "food webs",
                "Impervious cover",
                "urban"
            ],
            "contactPoint": {
                "fn": "Nathan Smucker",
                "hasEmail": "mailto:smucker.nathan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Smucker_stable_istotope_study_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434636/Smucker_stable_istotope_study_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-04-23",
            "references": [
                "https://doi.org/10.1016/j.ecolind.2018.03.024"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data",
            "description": "The data set contains all of the raw spectra for the XAFS data analysis and the data that was used to generate the figures and table in the manuscript and supporting information.  The XAFS data requires the use of Demeter Software to access. \n\nThis dataset is associated with the following publication:\nClar, J., W. Platten, E. Baumann, A. Remsen, S. Harmon, C. Bennett-Stamper, T. Thomas, and T. Luxton. Dermal transfer and environmental release of CeO2 nanoparticles used as UV inhibitors on outdoor surfaces: Implications for human and environmental health.   ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA,  714-723, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1435623",
            "keyword": [
                "Nanoparticles",
                "Cerium Oxide",
                "exposure",
                "Synchrotron X-ray Absorption",
                "consumer products",
                "Wipe Exposure",
                "synchrotron speciation"
            ],
            "contactPoint": {
                "fn": "Todd Luxton",
                "hasEmail": "mailto:luxton.todd@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data description.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435623/Data%20description.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435623/Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "XAFS Projects.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435623/XAFS%20Projects.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-05-02",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2017.09.050"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data",
            "description": "the data set contains a summary of all measurements that were collected at the cottage grove reservoir over the time period of the study. This dataset is associated with the following publication:\nEckley , C., T. Luxton , J. McKernan , J. Goetz , and J. Goulet. Influence of Reservoir Water-Level Fluctuations on Mercury Methylation Downstream of the Historic Black Butte Mercury Mine, OR.  Michael Kersten  APPLIED GEOCHEMISTRY. Elsevier Science Ltd, New York, NY, USA, 61: 284-293, (2015). NOTE: This dataset has been removed from public access due to revocation. Please refer inquiries regarding this dataset to the listed contact person.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1435629",
            "keyword": [
                "mercury",
                "methylmercury",
                "reservoir",
                "porewater",
                "mercury methylation",
                "dissolved organic carbon"
            ],
            "contactPoint": {
                "fn": "Todd Luxton",
                "hasEmail": "mailto:luxton.todd@epa.gov"
            },
            "distribution": [],
            "modified": "2018-05-02",
            "references": null,
            "publisher": {
                "name": "U.S. Environmental Protection Agency",
                "subOrganizationOf": {
                    "name": "U.S. Government"
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Open source data summaries - Fish, Rat, and Goat Metabolism Studies",
            "description": "Public versions of EFSA DAR's - metabolism study summaries for the pesticides; Fluazinam, Halauxifen-methyl, Kresoxim-methyl, Mandestrobin, Tolclofos-methyl in fish (bluegill or rainbow trout), rat, and goat. \n\nThis dataset is associated with the following publication:\nKolanczyk, R., J. Serrano, M. Tapper, and P. Schmieder. A comparison of fish pesticide metabolic pathways with those of the rat and goat.   REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 94: 124-143, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407629",
            "keyword": [
                "Rat",
                "Goat",
                "Bluegill Sunfish",
                "rainbow trout",
                "biotransformation",
                "Metabolism",
                "Metabolic Map",
                "Draft Assessment Report",
                "EFSA",
                "MetaPath",
                "Risk Assessment",
                "Species Extrapolation"
            ],
            "contactPoint": {
                "fn": "Richard Kolanczyk",
                "hasEmail": "mailto:kolanczyk.rick@epa.gov"
            },
            "distribution": [
                {
                    "title": "SpeciesComparisonFiles.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407629/SpeciesComparisonFiles.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-09-12",
            "references": [
                "https://doi.org/10.1016/j.yrtph.2018.01.019"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Bioactive Contaminants of Emerging Concern in National Park Waters of the Northern Colorado Plateau, USA",
            "description": "Water and sediment was collected to assess the occurrence of contaminants of emerging concern (CECs) in National Park waters of the northern Colorado Plateau, USA. CEC presence in water and sediment is reported for 21 sites in eight U.S. national parks in the northern Colorado Plateau region. From 2012 to 2016, at least one PPCP and/or WWI was detected at most sites on over half of sampling visits, indicating that CECs are not uncommon even in isolated areas. Maximum concentrations in this study were generally below available water quality benchmarks, sediment quality guidelines, and concentrations known to induce biological activity in vitro. C occurrence patterns and similarities between continuous and isolated flow locations suggest that direct contamination from individual visitors may also occur. While the data indicate there is little aquatic health risk associated with CECs at our sites, results demonstrate the ubiquity of CECs on the landscape and a continued need for public outreach concerning resource-use ethics and the potential effects of upstream development. \n\nThis dataset is associated with the following publication:\nWeissinger, R., B. Blackwell, K. Keteles, W. Battaglin, and P. Bradley. Bioactive contaminants of emerging concern in national park waters of the northern Colorado plateau, USA.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 636: 910-918, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1434490",
            "keyword": [
                "National parks",
                "Northern Colorado Plateau",
                "contaminants of emerging concern (CEC)",
                "exposure activity ratio",
                "adverse outcome pathway",
                "endocrine disruption",
                "ecotoxicology",
                "aquatic ecosystems",
                "screening and prioritization"
            ],
            "contactPoint": {
                "fn": "Brett Blackwell",
                "hasEmail": "mailto:blackwell.brett@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://doi.org/10.1016/j.scitotenv.2018.04.332",
                    "accessURL": "https://doi.org/10.1016/j.scitotenv.2018.04.332"
                },
                {
                    "title": "https://doi.org/10.5066/F7NP23PC",
                    "accessURL": "https://doi.org/10.5066/F7NP23PC"
                }
            ],
            "modified": "2018-05-01",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.04.332"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Assessing the Impact of Overburden Materials Selection from an Appalachian Region Coal Mine in Mine Water Quality Using a Standard Columns Leaching Test",
            "description": "The objective of this study was to evaluate the leachate conductivity generated by overburden materials in a columns test representing the surface coal mining conditions and its correlation with cations, anions, pH, and alkalinity in two scenarios: \u201cAltered\u201d and \u201cUnaltered\u201d with the application of the screening and segregation proposed method. . For the Unaltered scenario, all strata were included; while the Altered scenario excluded the overburden strata with the highest 15% conductivities measured in the screening-level assessment. The 15% selection criterion was based on the best professional judgment that this would be a reasonable overburden quantity to be selectively identified and isolated in a surface coal mining operation. \n\nThis dataset is associated with the following publication:\nPinto, P., S. Al-Abed , C. Holder, R. Warner, J. McKernan , S. Fulton, and E. Somerville. Assessing the Impact of Removing Select Materials from Coal Mine Overburden, Central Appalachia Region, USA.  Robert Kleinmann  Mine Water and the Environment. Springer-Verlag, BERLIN-HEIDELBERG,  GERMANY, 37(1): 31-41, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1500002",
            "keyword": [
                "coal mine water",
                "total dissolved solids",
                "mine waste leaching",
                "conductivity",
                "materials management"
            ],
            "contactPoint": {
                "fn": "Souhail Al-Abed",
                "hasEmail": "mailto:al-abed.souhail@epa.gov"
            },
            "distribution": [
                {
                    "title": "TDS manuscript Metadata data tables with data dictionary 2016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500002/TDS%20manuscript%20Metadata%20data%20tables%20with%20data%20dictionary%202016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-06-15",
            "references": [
                "https://doi.org/10.1007/s10230-017-0462-4"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1500002/documents/TDS%20manuscript%20Data%20Dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Summary of test data for CIPP liner",
            "description": "Table 1. Selected Innovative Rehabilitation Technologies - summarizes the descriptions of the technologies.\nTable 2.  Summary of test data for CIPP liner - gives the values of the lab results.\nTable 3.  Summary of Four Technology Evaluations - summarizes the benefits of technologies. \n\nThis dataset is associated with the following publication:\nSelvakumar , A., and J. Matthews. Demonstration and Evaluation of Innovative Rehabilitation Technologies for Water Infrastructure Systems.   Journal of Pipeline Systems Engineering and Practice. American Society of Civil Engineers  (ASCE), Reston, VA, USA, 8(4): 1949-1204, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1500004",
            "keyword": [
                "cured-in-place pipe",
                "Field demonstration",
                "water main",
                "wastewater pipe",
                "spray on lining",
                "geopolymer mortar",
                "internal pipe sealing"
            ],
            "contactPoint": {
                "fn": "Ariamalar Selvakumar",
                "hasEmail": "mailto:selvakumar.ariamalar@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data set.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500004/Data%20set.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2018-05-03",
            "references": [
                "https://doi.org/10.1061/(asce)ps.1949-1204.0000268"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cao et al 20xx Data Set (Version 1)",
            "description": "HF183/BacR287 qPCR data from standard curves and coastal water samples used to seed simulations in study. \n\nThis dataset is associated with the following publication:\nCao, Y., M. Sivaganesan, C. Kelty, D. Wang, A. Boehm, J. Griffith, S. Weisberg, and O. Shanks. A Human Fecal Contamination Score for Ranking Recreational Sites using the HF183/BacR287 Quantitative Real-Time PCR Method.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 128: 148-156, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407638",
            "keyword": [
                "Microbial Source Tracking",
                "human fecal pollution",
                "qPCR",
                "site prioritization",
                "water quality"
            ],
            "contactPoint": {
                "fn": "Orin Shanks",
                "hasEmail": "mailto:shanks.orin@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cao et al 20xx_Data Set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407638/Cao%20et%20al%2020xx_Data%20Set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-18",
            "references": [
                "https://doi.org/10.1016/j.watres.2017.10.071"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Wilkin et al. (2017) As Se Co-contamination",
            "description": "The dataset includes groundwater information for: water stable isotopes, As concentrations, Se concentrations, and spectroscopic scans. \n\nThis dataset is associated with the following publication:\nWilkin, R.T., T. Lee, D. Beak, R. Anderson, and B. Burns. Groundwater Co-Contaminant Behavior of Arsenic and Selenium at a Lead and Zinc Smelting Facility.   APPLIED GEOCHEMISTRY. Elsevier Science Ltd, New York, NY, USA, 89: 255-264, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390568",
            "keyword": [
                "arsenic",
                "Selenium",
                "groundwater",
                "metalloids"
            ],
            "contactPoint": {
                "fn": "Richard Wilkin",
                "hasEmail": "mailto:wilkin.rick@epa.gov"
            },
            "distribution": [
                {
                    "title": "Wilkin et al. (2017) As Se Co-contamination.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390568/Wilkin%20et%20al.%20%282017%29%20As%20Se%20Co-contamination.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-09-15",
            "references": [
                "https://doi.org/10.1016/j.apgeochem.2017.12.011"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Year-round presence of neonicotinoid insecticides in tributaries to the Great Lakes, USA",
            "description": "To better understand the transport of neonicotinoid insecticides into the Great Lakes, monthly samples (October 2015-September 2016) were collected from 10 tributaries to the Great Lakes, USA. At least one neonicotinoid was detected in 74% of the monthly samples with up to three neonicotinoids detected in an individual sample (10% of all samples). The most frequently detected neonicotinoid was imidacloprid (53%) followed by clothianidin (44%), thiamethoxam (22%), acetamiprid (2%), and dinotefuran (1%). Thiacloprid was not detected in any samples. More spatially intensive samples from were collected in an agriculturally dominated area (Maumee River, Ohio) twice during spring 2016. Three neonicotinoids were ubiquitously detected (clothiandin, imidacloprid, thiamethoxam) in all water samples collected within this basin. \n\nThis dataset is associated with the following publication:\nHladik, M., S. Corsi, D. Kolpin, A. Baldwin, B. Blackwell, and J. Cavallin. Year-round presence of neonicotinoid insecticides in tributaries to the Great Lakes, USA.   ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 235: 102-1029, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1411959",
            "keyword": [
                "neonicotinoids",
                "adverse outcome pathway",
                "endocrine disruption",
                "ecotoxicology",
                "aquatic ecosystems",
                "screening and prioritization"
            ],
            "contactPoint": {
                "fn": "Brett Blackwell",
                "hasEmail": "mailto:blackwell.brett@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://doi.org/10.1016/j.envpol.2018.01.013",
                    "accessURL": "https://doi.org/10.1016/j.envpol.2018.01.013"
                }
            ],
            "modified": "2018-01-23",
            "references": [
                "https://doi.org/10.1016/j.envpol.2018.01.013"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Social media data for Great Lakes AOCs",
            "description": "This data is an Excel file that has links to downloaded photographs posted to social media sites.  There is a sheet with metadata in the file. This dataset is associated with the following publication:\nAngradi, T., J. Launspach, and R. Debbout. Determining preferences for ecosystem benefits in Great Lakes Areas of Concern from photographs posted to social media.   JOURNAL OF GREAT LAKES RESEARCH. International Association for Great Lakes Research, Ann Arbor, MI, USA, 44(2): 340-351, (2018). NOTE: This dataset has been removed from public access due to revocation. Please refer inquiries regarding this dataset to the listed contact person.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1419012",
            "keyword": [
                "Great Lakes Areas of Concern",
                "social media",
                "Ecosystem services and benefits",
                "Decision making",
                "restoration"
            ],
            "contactPoint": {
                "fn": "Theodore Angradi",
                "hasEmail": "mailto:angradi.theodore@epa.gov"
            },
            "distribution": [],
            "modified": "2018-02-01",
            "references": null,
            "publisher": {
                "name": "U.S. Environmental Protection Agency",
                "subOrganizationOf": {
                    "name": "U.S. Government"
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dilbit Dateset",
            "description": "Raw data and calculation. \n\nThis dataset is associated with the following publication:\nDeshpande, R., D. Sundaravadivelu, S. Techmann, R. Conmy, J. Santodomingo, and P. Campo. Microbial degradation of Cold Lake Blend and Western Canadian Select Dilbits in Freshwater.   JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, USA, 352: 111-120, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1500012",
            "keyword": [
                "dilbit",
                "hydrocarbon"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [
                {
                    "title": "DilbitData (2).xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500012/DilbitData%20%282%29.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-10",
            "references": [
                "https://doi.org/10.1016/j.jhazmat.2018.03.030"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Evaluating Weathering of Food Packaging Polyethylene-Nano-clay Composites: Release of Nanoparticles and their Impacts",
            "description": "When nanomaterials added to consumer products create products with improved properties. However, it is necessary to evaluate the potential of adverse impacts on the environment and the human health. This study has shown there is strong evidence that the stability of two types of food packaging low density polyethylene (LDPE)-clay composite films are altered when exposed to environmental conditions, UV-irradiation or ozone in the presence of moisture. Both LDPE samples underwent oxidative degradation during UV irradiation or ozone exposure resulting in a substantial change in physical, structural, and thermal properties releasing clay nanoparticles. \n\nThis dataset is associated with the following publication:\nHan, C., E. Sahle-Demessie, A. Zhao, and E. Varughese. Evaluating weathering of food packaging polyethylene-nano-clay composites: Release of nanoparticles and their impacts.   NanoImpact. Elsevier B.V., Amsterdam,  NETHERLANDS, 9: 61-71, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1500001",
            "keyword": [
                "nanoclay",
                "polymer composite",
                "weathering",
                "nanorelease",
                "nanotoxicity"
            ],
            "contactPoint": {
                "fn": "Endalkac Sahle-Demessie",
                "hasEmail": "mailto:sahle-demessie.endalkachew@epa.gov"
            },
            "distribution": [
                {
                    "title": "LDPE_nanoclay_Highlights_.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500001/LDPE_nanoclay_Highlights_.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "LDPE_nanoclay_Figures_text_11_24_16.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500001/LDPE_nanoclay_Figures_text_11_24_16.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "LDPE_nanoclay_Text_Revised_Han_Sahle.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500001/LDPE_nanoclay_Text_Revised_Han_Sahle.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "LDPE_nanoclay_Text_Revised_HeighlightedCorrection.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500001/LDPE_nanoclay_Text_Revised_HeighlightedCorrection.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "LDPE_nanoclay_Supplmenta_11_24_16.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500001/LDPE_nanoclay_Supplmenta_11_24_16.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "LDPE_nanoclay_Supplmenta_Revised_3_21_2017.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500001/LDPE_nanoclay_Supplmenta_Revised_3_21_2017.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "https://www.sciencedirect.com/search?authors=sahle-demessie&pub=NanoImpact&show=25&sortBy=relevance&origin=jrnl_issue&zone=search&cid=313695",
                    "accessURL": "https://www.sciencedirect.com/search?authors=sahle-demessie&pub=NanoImpact&show=25&sortBy=relevance&origin=jrnl_issue&zone=search&cid=313695"
                }
            ],
            "modified": "2017-09-01",
            "references": [
                "https://doi.org/10.1016/j.impact.2017.10.005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1500001/documents/Data%20Dictionary_MWCNT_PlolymerComposite.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "RLINE model algrotihms to account for NO2 near-road chemistry data set - RLINE_N02",
            "description": "This data set is associated with the results found in the journal article: Valencia et al, 2018. Development and evaluation of the R-LINE model algorithms to account for chemical transformation in the near-road environment. Transportation Research Part D, https://doi.org/10.1016/j.trd.2018.01.028. \nTo address the need to estimate near-road NO2 concentrations, we implemented three different approaches in order of increasing degrees of complexity and barrier to implementation from simplest to more complex. The first is an empirical approach based upon fitting a 4th order polynomial to existing near-road observations across the continental U.S., the second involves a simplified Two-reaction chemical scheme, and the third involves a more detailed set of chemical reactions based upon the Generic Reaction Set (GRS) mechanism. All models were able to estimate more than 75% of  concentrations within a factor of two of the near-road monitoring data and produced comparable performance statistics. These results indicate that the performance of the new R-LINE chemistry algorithms for predicting NO2 is comparable to other models (i.e. ADMS-Roads with GRS), both showing less than\u00b115% fractional bias and less than 45% normalized mean square error. \n\nThis dataset is associated with the following publication:\nValencia, A., A. Venkatram, D. Heist, D. Carruthers , and S. Arunachalam. Development and evaluation of the R-LINE model algorithms to account for chemical transformation in the near-road environment.   Transportation Research Part D: Transport and Environment. Elsevier BV, AMSTERDAM,  NETHERLANDS, 59: 464-477, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1433507",
            "keyword": [
                "air pollution",
                "dispersion modeling",
                "Mobile sources",
                "exposure",
                "near road"
            ],
            "contactPoint": {
                "fn": "Vladilen Isakov",
                "hasEmail": "mailto:isakov.vlad@epa.gov"
            },
            "distribution": [
                {
                    "title": "HeistDavid_A-z099_Datafiles_RLINE_NO2.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1433507/HeistDavid_A-z099_Datafiles_RLINE_NO2.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-11-15",
            "references": [
                "https://doi.org/10.1016/j.trd.2018.01.028"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1433507/documents/HeistDavid_A-z099_DataDictionary_RLINE_NO2.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Characterization of Emissions from Liquid Fuel and Propane Open Burns",
            "description": "emission factor data. \n\nThis dataset is associated with the following publication:\nAurell, J., D. Hubble, B. Gullett, A. Holder, E. Washburn, and D. Tabor. Characterization of Emissions from Liquid Fuel and Propane Open Burns.   Fire Technology. Springer International Publishing AG, Cham (ZG),  SWITZERLAND, 53(6): 2023-2038, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407527",
            "keyword": [
                "emissions",
                "kerosene",
                "JP-5",
                "propane",
                "open fire",
                "pool fire",
                "fast cook off"
            ],
            "contactPoint": {
                "fn": "Brian Gullett",
                "hasEmail": "mailto:gullett.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data Table Science Hub Dahlgren 01-26-2017 JA.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407527/Data%20Table%20Science%20Hub%20Dahlgren%2001-26-2017%20JA.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-01-26",
            "references": [
                "https://doi.org/10.1007/s10694-017-0670-2"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Biofiltration of chloroform in a trickle bed air biofilter under acidic conditions",
            "description": "In this paper, the application of biofiltration is investigated for controlled removal of gas phase chloroform through cometabolic degradation with ethanol. A trickle bed air biofilter (TBAB) operated under acidic pH 4 is subjected to aerobic biodegradation of chloroform and ethanol. The TBAB is composed of pelleted diatomaceous earth filter media inoculated with filamentous fungi species, which served as the principle biodegrading microorganism. \n\nThis dataset is associated with the following publication:\nPalanisamy , K., B.  Mezgebe , G. Sorial, and E. Sahle-Demessie. Biofiltration of Chloroform in a Trickle Bed Air Biofilter Under Acidic Conditions.   WATER, AIR, & SOIL POLLUTION. Springer, New York, NY, USA, 227: 478, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1435556",
            "keyword": [
                "biofiltration",
                "Chloroform",
                "filamentous fungi",
                "cometabolism",
                "ethanol",
                "trickle bed air biofilter"
            ],
            "contactPoint": {
                "fn": "Endalkac Sahle-Demessie",
                "hasEmail": "mailto:sahle-demessie.endalkachew@epa.gov"
            },
            "distribution": [
                {
                    "title": "G-STD-0016294-JA-5-0_Kertee'sPPR.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435556/G-STD-0016294-JA-5-0_Kertee%27sPPR.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "G-STD-0016294-JA-5-0_Kertee'sPPR_Figures.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435556/G-STD-0016294-JA-5-0_Kertee%27sPPR_Figures.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-06-01",
            "references": [
                "https://doi.org/10.1007/s11270-016-3194-3"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1435556/documents/Data%20Dictionary_BiotrickleFiltration.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Effect of natural organic matter effec on fate and transport of engineered nanoparticles ",
            "description": "This study characterized Ohio river natural organic matter during winter and summer seasons, and demonstrated the effects of these natural organic samples on stability and transport of cerium oxide nanoparticles in saturated porous media. OR-NOM samples that were characterized by thermal analysis, Fourier transfer solid state neutron magnetic resonance spectrometer and elemental analysis showed to have structural and compositional differences from standard humic acid. This study explored the effects of OR-NOM in enhancing the transport and breakthrough of ceria nanoparticle in moderate (1-10 mM) ionic strength solutions. The enhancement in stability and transport appear to be dominated by the altered electrokinetic properties of the nanopraticles. \n\nThis dataset is associated with the following publication:\nLi, Z., E. Sahle-Demessie, A. Aly Hassan, J. Pressman, C. Han, and G. Sorial. Effects of source and seasonal variations of natural organic matters on the fate and transport of CeO2 nanoparticles in the environment.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 609: 1616-1626, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407605",
            "keyword": [
                "engineered nanomaterials",
                "natural organic matter",
                "fourier transfer spectroscopy",
                "Nanoparticles",
                "CeO2",
                "ssNMR-FTIR",
                "packed-column transport",
                "Ohio River"
            ],
            "contactPoint": {
                "fn": "Endalkac Sahle-Demessie",
                "hasEmail": "mailto:sahle-demessie.endalkachew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Effects of source and seasonal variations of natural organic matters on the fate and transport of CeO2 nanoparticles i.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407605/Effects%20of%20source%20and%20seasonal%20variations%20of%20natural%20organic%20matters%20on%20the%20fate%20and%20transport%20of%20CeO2%20nanoparticles%20i.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Supplementary Data_NOM_CeO2_PPR.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407605/Supplementary%20Data_NOM_CeO2_PPR.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-02-01",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2017.07.154"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1407605/documents/Seasonal%20Variation%20of%20NOM_Data%20Dictionary.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "SA-PM versus SA-O3 complete data set_May 2014-August 2015",
            "description": "Raw data of cardiac and ventilatory responses to SA-PM and SA-O3. \n\nThis dataset is associated with the following publication:\nHazari, M., K. Stratford, T. Krantz, C. King, J. Krug, A. Farraj, and I. Gilmour. Comparative cardiopulmonary effects of particulate matter- and ozone-enhanced smog atmospheres in mice.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(5): 3071-3080, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1375203",
            "keyword": [
                "Smog",
                "cardiac",
                "mouse",
                "electrocardiogram",
                "heart rate variability",
                "PM",
                "Ozone",
                "heart rate"
            ],
            "contactPoint": {
                "fn": "Mehdi Hazari",
                "hasEmail": "mailto:hazari.mehdi@epa.gov"
            },
            "distribution": [
                {
                    "title": "SA-PM vs SA-O3_all data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375203/SA-PM%20vs%20SA-O3_all%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-13",
            "references": [
                "https://doi.org/10.1021/acs.est.7b04880"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figure Data and Table Data for Differential exposure and acute health impacts of inhaled solid-fuel emissions from rudimentary and advanced cookstoves in female CD-1 mice. ",
            "description": "To link health benefits derived from advanced CS usage to increasing combustion efficiencies of the cookstove, a wide variety of general health and respiratory system parameters that are often altered acutely following exposure to air pollutants were assessed.  The figures and tables reflect the health outcomes. \n\nThis dataset is associated with the following publication:\nGibbs-Flournoy, E., I. Gilmour, M. Higuchi, J. Jetter, I. George, L. Copeland, R. Harrison, V. Moser, and J. Dye. Differential exposure and acute health impacts of inhaled solid-fuel emissions from rudimentary and advanced cookstoves in female CD-1 mice..   ENVIRONMENTAL RESEARCH. Academic Press Incorporated, Orlando, FL, USA, 161: 35-48, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1377833",
            "keyword": [
                "cookstoves",
                "incomplete combustion",
                "lung injury",
                "oxidative stress",
                "phagocytosis"
            ],
            "contactPoint": {
                "fn": "Janice Dye",
                "hasEmail": "mailto:dye.janice@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHub-Gibbs-Cookstoves_Figs&TablesFINAL.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377833/ScienceHub-Gibbs-Cookstoves_Figs%26TablesFINAL.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-30",
            "references": [
                "https://doi.org/10.1016/j.envres.2017.10.043"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "See appendices K-N in report at http://ofmpub.epa.gov/eims/eimscomm.getfile?p_download_id=530693",
            "description": "See report at: http://ofmpub.epa.gov/eims/eimscomm.getfile?p_download_id=530693. \n\nThis dataset is associated with the following publication:\nJulius , S., J. Blue, and N. Hiremath. Urban Resilience to Climate Change: Washington, DC and Worcester, MA Case Studies. U.S. Environmental Protection Agency, Washington, DC, USA, 2017.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407611",
            "keyword": [
                "Qualitative indicators",
                "quantitative indicators",
                "Worcester MA",
                "Washington DC",
                "climate change",
                "adaptation",
                "mixed methods",
                "urban resilience",
                "Vulnerability",
                "indicators"
            ],
            "contactPoint": {
                "fn": "Susan Julius",
                "hasEmail": "mailto:julius.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://ofmpub.epa.gov/eims/eimscomm.getfile?p_download_id=530693",
                    "accessURL": "https://ofmpub.epa.gov/eims/eimscomm.getfile?p_download_id=530693"
                }
            ],
            "modified": "2017-01-13",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://ofmpub.epa.gov/eims/eimscomm.getfile?p_download_id=530693",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "AOP-Wiki Event Component Annotation",
            "description": "This dataset contains ontology terms associated with key events from the AOP-Wiki.  This information was used to seed the AOP-Wiki with a carefully selected set of ontology terms prior to opening up the option for authors to tag their own AOPs. This is intended to provide existing examples for authors and improve consistency when assigning terms to the key events. \n\nThis dataset is associated with the following publication:\nIves, C., I. Campia, R. Wang, C. Wittwehr, and S. Edwards. Creating a Structured Adverse Outcome Pathway Knowledgebase via Ontology-Based Annotations.   Applied In Vitro Toxicology. Mary Ann Liebert, Inc., Larchmont, NY, USA, 3(4): 298-311, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407549",
            "keyword": [
                "adverse outcome pathway",
                "key event",
                "ontology",
                "knowledgebase"
            ],
            "contactPoint": {
                "fn": "Stephen Edwards",
                "hasEmail": "mailto:edwards.stephen@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://aopwiki.org",
                    "accessURL": "https://aopwiki.org"
                },
                {
                    "title": "CIvesSupplementaryTables_revised_08-04-17.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407549/CIvesSupplementaryTables_revised_08-04-17.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-05-16",
            "references": [
                "https://doi.org/10.1089/aivt.2017.0017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": " Safe Drinking Water Information System (SDWIS) Federal Reports Advanced Search Tool",
            "description": "A database where EPA has compiled data on public drinking water systems and whether they have certain drinking water violations.  This data is collected by the states and given to the EPA. \n\nThis dataset is associated with the following publication:\nPennino, M., J. Compton, and S. Leibowitz. Trends in Drinking Water Nitrate Violations Across the United States.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA,  13450-13460, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407575",
            "keyword": [
                "violation",
                "contaminants in water systems",
                "Clean Water Act",
                "drinking water",
                "nitrate",
                "nitrate in groundwater",
                "maximum contaminant level",
                "surface water",
                "public water systems"
            ],
            "contactPoint": {
                "fn": "Michael Pennino",
                "hasEmail": "mailto:pennino.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://ofmpub.epa.gov/apex/sfdw/f?p=108:9:::NO::P9_REPORT:VIO",
                    "accessURL": "https://ofmpub.epa.gov/apex/sfdw/f?p=108:9:::NO::P9_REPORT:VIO"
                },
                {
                    "title": "Mean_Annual_NO3_Pop_Served_County_1994-2016_FINAL.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407575/Mean_Annual_NO3_Pop_Served_County_1994-2016_FINAL.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Mean_Annual_NO3_Violations_County_1994-2016_FINAL.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407575/Mean_Annual_NO3_Violations_County_1994-2016_FINAL.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "SDWIS_NO3_Violation_Duration_State_1994-2016_FINAL.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407575/SDWIS_NO3_Violation_Duration_State_1994-2016_FINAL.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "SDWIS_NO3_Violations_Over_Time_1994-2016_FINAL.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407575/SDWIS_NO3_Violations_Over_Time_1994-2016_FINAL.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "SDWIS_GW_NO3_Violations_County_1994-2016_FINAL.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407575/SDWIS_GW_NO3_Violations_County_1994-2016_FINAL.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "SDWIS_NO3_Pop_Served_County_1994-2016_FINAL.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407575/SDWIS_NO3_Pop_Served_County_1994-2016_FINAL.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "SDWIS_NO3_Violations_County_1994-2016_FINAL.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407575/SDWIS_NO3_Violations_County_1994-2016_FINAL.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "SDWIS_Percent_GW_NO3_Violations_County_1994-2016_FINAL.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407575/SDWIS_Percent_GW_NO3_Violations_County_1994-2016_FINAL.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "SDWIS_Percent_GWSW_Violations_County_1994-2016_FINAL.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407575/SDWIS_Percent_GWSW_Violations_County_1994-2016_FINAL.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "SDWIS_Percent_SW_NO3_Violations_County_1994-2016_FINAL.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407575/SDWIS_Percent_SW_NO3_Violations_County_1994-2016_FINAL.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "SDWIS_SW_NO3_Violations_County_1994-2016_FINAL.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407575/SDWIS_SW_NO3_Violations_County_1994-2016_FINAL.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-06-30",
            "references": [
                "https://doi.org/10.1021/acs.est.7b04269"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Photochemical smog and vitamin D deficiency",
            "description": "The dataset contains the results of a study examining the impact of vitamin D deficiency on the cardiopulmonary response of mice to photochemical smog. \n\nThis dataset is associated with the following publication:\nStratford, K., N. Coates, L. Thompson, T. Krantz, C. King, J. Krug, I. Gilmour, A. Farraj, and M. Hazari. Early-Life Persistent Vitamin D Deficiency Alters Cardiopulmonary Responses to Particulate Matter-Enhanced Atmospheric Smog in Adult Mice.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(5): 3054-3061, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1375240",
            "keyword": [
                "vitamin d deficiency",
                "Smog",
                "cardiac",
                "mouse",
                "heart rate",
                "heart rate variability",
                "PM",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Mehdi Hazari",
                "hasEmail": "mailto:hazari.mehdi@epa.gov"
            },
            "distribution": [
                {
                    "title": "Vitamin D and smog ECG.HRV.WBP data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375240/Vitamin%20D%20and%20smog%20ECG.HRV.WBP%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-08-09",
            "references": [
                "https://doi.org/10.1021/acs.est.7b04882"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Light-absorbing organic carbon from prescribed and laboratory biomass burning and gasoline vehicle emissions",
            "description": "This dataset is a compilation of optical properties of the organic fraction of particulate matter emitted from prescribed burning and from gasoline vehicles. \n\nThis dataset is associated with the following publication:\nXie, M., M. Hays, and A. Holder. Light absorbing organic carbon from prescribed and laboratory biomass burning and gasoline vehicle emissions.   Scientific Reports. Nature Publishing Group, London,  UK,  online, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1375575",
            "keyword": [
                "Prescribed Fires",
                "Gasoline Vehicle Emissions",
                "Combustion Emissions",
                "Black Carbon",
                "Brown Carbon",
                "Fine Particulate Matter",
                "Aerosol Optical Properties",
                "Secondary Organic Aerosol"
            ],
            "contactPoint": {
                "fn": "Amara Holder",
                "hasEmail": "mailto:holder.amara@epa.gov"
            },
            "distribution": [
                {
                    "title": "Scientific Reports2017 Data Tables and Dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375575/Scientific%20Reports2017%20Data%20Tables%20and%20Dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-01",
            "references": [
                "https://doi.org/10.1038/s41598-017-06981-8"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data set for Light Absorption of Secondary Organic Aerosol: Composition and Contribution of Nitro-aromatic Compounds",
            "description": "This is the data used to generate the figures published in the journal article titled, \"Light Absorption of Secondary Organic Aerosol: Composition and Contribution of Nitro-aromatic Compounds\". \n\nThis dataset is associated with the following publication:\nXie, M., X. Chen, M. Hays, M. Lewandowski, J. Offenberg, T. Kleindienst, and A. Holder. Light absorption of secondary organic aerosol: Composition and contribution of nitro-aromatic compounds.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(20): 11607-11616, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407634",
            "keyword": [
                "Nitro-aromatic compounds",
                "Combustion Emissions",
                "Black Carbon",
                "Brown Carbon",
                "Fine Particulate Matter",
                "Aerosol Optical Properties",
                "Secondary Organic Aerosol"
            ],
            "contactPoint": {
                "fn": "Amara Holder",
                "hasEmail": "mailto:holder.amara@epa.gov"
            },
            "distribution": [
                {
                    "title": "Environmental Science and Technology 2017 Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407634/Environmental%20Science%20and%20Technology%202017%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-28",
            "references": [
                "https://doi.org/10.1021/acs.est.7b03263"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data used in manuscript \"Modeling crop residue burning experiments and assessing the fire impacts on air quality\"",
            "description": "The data sets includes the data used to generate the figures presented in the manuscript.  Each worksheet in the attached file provides data for a specific figure (as labeled). \n\nThis dataset is associated with the following publication:\nZhou, L., K. Baker, S. Napelenok, G. Pouliot, R. Elleman, S. O'Neill, S. Urbanski, and D. Wong. Modeling crop residue burning experiments to evaluate smoke emissions and plume transport.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 627: 523-533, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434485",
            "keyword": [
                "air quality",
                "biomass burning",
                "emissions",
                "smoke plume"
            ],
            "contactPoint": {
                "fn": "Sergey Napelenok",
                "hasEmail": "mailto:napelenok.sergey@epa.gov"
            },
            "distribution": [
                {
                    "title": "Zhou2017_agburn_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434485/Zhou2017_agburn_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-31",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.01.237"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Estimation of spatial and temporal variation in light attenuation due to epigrowth on Zostera marina in Yaquina Bay",
            "description": "Data on epiphyte load, Zostera marina biomass, nutrients, and mesograzers on epiphytes for a 4 year period at six stations within Yaquina Bay, OR. Data were used to generate the figures contained in the paper \"An evaluation of factors controlling the abundance of epiphytes on Zostera marina along an estuarine gradient in Yaquina Bay, Oregon, USA\". \n\nThis dataset is associated with the following publication:\nNelson, W. An evaluation of factors controlling the abundance of epiphytes on Zostera marina along an estuarine gradient in Yaquina Bay, Oregon, USA..   AQUATIC BOTANY. Elsevier Science Ltd, New York, NY, USA, 148: 53-63, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1375802",
            "keyword": [
                "Epiphyte load",
                "nutrients",
                "Yaquina Bay",
                "dissolved inorganic nitrogen",
                "phosphorus",
                "Mesograzers"
            ],
            "contactPoint": {
                "fn": "Walter Nelson",
                "hasEmail": "mailto:nelson.walt@epa.gov"
            },
            "distribution": [
                {
                    "title": "Nelson factors controlling Epiphyte Load SciHub figure data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375802/Nelson%20factors%20controlling%20Epiphyte%20Load%20SciHub%20figure%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-08",
            "references": [
                "https://doi.org/10.1016/j.aquabot.2018.04.010"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "TDS-TSS-Flow Data Used_IMWA_Eval Relationships between TDS and TSS in a mining-influenced watershed",
            "description": "TDS, TSS, and Flow data used for developing and testing relationships in the Clear Creek Watershed, Colorado.  Data for development of relationships was collected by Barbara Butler while at the Colorado School of Mines.  Data for testing relationships was obtained from Tim Steele of TDS Consulting in Colorado as provided by the Upper Clear Creek Watershed Association. \n\nThis dataset is associated with the following publication:\nButler, B., and R. Ford. Evaluating Relationships Between Total Dissolved Solids (TDS) and Total Suspended Solids (TSS) in a Mining-Influenced Watershed.  Bob Kleinmann  Mine Water and the Environment. Springer-Verlag, BERLIN-HEIDELBERG,  GERMANY, 37(1): 18-30, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1407561",
            "keyword": [
                "TDS",
                "TSS",
                "Flow",
                "conductivity",
                "loads",
                "TDS/TSS Ratio",
                "mining-influenced water",
                "water quality monitoring"
            ],
            "contactPoint": {
                "fn": "Barbara Butler",
                "hasEmail": "mailto:butler.barbara@epa.gov"
            },
            "distribution": [
                {
                    "title": "TDS-TSS-Flow Data Used_IMWA_Eval Relationships between TDS and TSS in a mining-influenced watershed.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407561/TDS-TSS-Flow%20Data%20Used_IMWA_Eval%20Relationships%20between%20TDS%20and%20TSS%20in%20a%20mining-influenced%20watershed.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-07",
            "references": [
                "https://doi.org/10.1007/s10230-017-0484-y"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Florida Estuary Optics 2009-2012",
            "description": "Small boat surveys were conducted in four Florida estuaries along the northern Gulf of Mexico from September 2009 through January 2012.  The systems selected represent a range of optical characteristics (e.g., high vs. low particulate loads) and were of sufficient size to be adequately resolved with remote sensing imagery. The systems sampled were Pensacola Bay, Choctawhatchee Bay, St. Andrews Bay, and St. Joseph Bay.  Field data collection included discrete water samples, profiling water quality data, and above/below water in-situ hyperspectral optical measures.. \n\nThis dataset is associated with the following publication:\nSari Austuti, I., D. Mishra, S. Mishra, and B. Schaeffer. Spatio-temporal dynamics of inherent optical properties in oligotrophic northern Gulf of Mexico estuaries.   Continental Shelf Research. Elsevier BV, AMSTERDAM,  NETHERLANDS, 166: 92-107, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1424031",
            "keyword": [
                "Hybrid model",
                "Quasi-analytical algorithm",
                "water quality",
                "Florida estuaries",
                "MERIS",
                "Choctawhatchee Bay",
                "St. Andrew Bay",
                "Pensacola Bay",
                "and St. Joseph Bay"
            ],
            "contactPoint": {
                "fn": "Blake Schaeffer",
                "hasEmail": "mailto:schaeffer.blake@epa.gov"
            },
            "distribution": [
                {
                    "title": "FL_Optics_data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1424031/FL_Optics_data.zip",
                    "mediaType": "application/zip"
                },
                {
                    "title": "FL_Estuaries_updated.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1424031/FL_Estuaries_updated.zip",
                    "mediaType": "application/zip"
                }
            ],
            "modified": "2015-01-01",
            "references": [
                "https://doi.org/10.1016/j.csr.2018.06.016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1424031/documents/FL_estuaries_data_dictionary.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset for paper: Evaluating the performance of household liquefied petroleum gas cookstoves",
            "description": "This dataset provides supporting information for figures in the journal article entitled: Evaluating the performance of household liquefied petroleum gas cookstoves. \n\nThis dataset is associated with the following publication:\nShen, G., J. Jetter, K. Smith, C. Williams, J. Faircloth, and M. Hays. Evaluating the Performance of Household Liquefied Petroleum Gas Cookstoves.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(2): 904-915, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407647",
            "keyword": [
                "LPG",
                "Liquefied Petroleum Gas",
                "cookstove",
                "stove",
                "emission",
                "efficiency"
            ],
            "contactPoint": {
                "fn": "James Jetter",
                "hasEmail": "mailto:jetter.jim@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data in LPG paper- 20180505.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407647/Data%20in%20LPG%20paper-%2020180505.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-21",
            "references": [
                "https://doi.org/10.1021/acs.est.7b05155"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Blood Pb prediction with SHEDS-MM witth IEUBK",
            "description": "The data is related to all figures and tables presented in the journal article. All data is written using the SAS software data format. \n\nThis dataset is associated with the following publication:\nZartarian, V., J. Xue, R. Tornero-Velez, and J. Brown. Children\u2019s Lead Exposure: A Multimedia Modeling Analysis to Guide Public Health Decision-Making.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 125(9): 1-10, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1407554",
            "keyword": [
                "Time activity",
                "Soil and Dust ingestion rate",
                "soil and dust Pb concentration",
                "Water consumption rate",
                "SHEDS-IEUBK",
                "lead",
                "exposure",
                "model evaluation",
                "lead copper rule"
            ],
            "contactPoint": {
                "fn": "Valerie Zartarian Morrison",
                "hasEmail": "mailto:zartarian.valerie@epa.gov"
            },
            "distribution": [
                {
                    "title": "XueJianping_2.63.6_Data_5-22-2017.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407554/XueJianping_2.63.6_Data_5-22-2017.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-05-01",
            "references": [
                "https://doi.org/10.1289/ehp1605",
                "https://www.epa.gov/dwstandardsregulations/lead-modeling-peer-review"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Gridded Hourly O3 Data for BASE case contributed by USEPA",
            "description": "This dataset contains data contributed by EPA/ORD/NERL/CED researchers to the manuscript \" Assessment and economic valuation of air pollution impacts on human health over Europe and the United States as calculated by a multi-model ensemble in the framework of AQMEII3\" led by Dr. Ulas Im of Aarhus University in Denmark. \n\nThis dataset is associated with the following publication:\nIm, U., J. Brandt, C. Geels, K. Hansen, J. Christensen, M. Andersen, E. Solazzo, I. Kioutsioukis, U. Alyuz, A. Balzarini, R. Baro, R. Bellasio, R. Bianconi, J. Bieser, A. Colette, G. Curci, A. Farrow, J. Flemming, A. Fraser, P. Jimenez-Guerrero, N. Kitwiroon, C. Liang, U. Nopmongcol, G. Pirovano, L. Pozzoli, M. Prank, R. Rose, R. Sokhi, P. Tuccella, A. Unal, M. Garcia Vivanco, J. West, G. Yarwood, C. Hogrefe, and S. Galmarini. Assessment and economic valuation of air pollution impacts on human health over Europe and the United States as calculated by a multi-model ensemble in the framework of AQMEII3.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 18: 5967-5989, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1378452",
            "keyword": [
                "ensemble modeling",
                "air quality health impacts",
                "economic valuation of health impacts",
                "model evaluation"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "ImEtAl_Gridded_Data_O3_Base.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378452/ImEtAl_Gridded_Data_O3_Base.zip",
                    "mediaType": "application/zip"
                }
            ],
            "modified": "2016-09-01",
            "references": [
                "https://doi.org/10.5194/acp-18-5967-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1378452/documents/HogrefeChristian_A-02v7_DataDescription_ImEtAl.zip",
            "describedByType": "application/zip",
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            "identifier": "https://doi.org/10.23719/1378465",
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                "economic valuation of health impacts",
                "model evaluation"
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                "economic valuation of health impacts",
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        },
        {
            "title": "Gridded Hourly SO2 Data for GLO case contributed by USEPA",
            "description": "This dataset contains data contributed by EPA/ORD/NERL/CED researchers to the manuscript \" Assessment and economic valuation of air pollution impacts on human health over Europe and the United States as calculated by a multi-model ensemble in the framework of AQMEII3\" led by Dr. Ulas Im of Aarhus University in Denmark. \n\nThis dataset is associated with the following publication:\nIm, U., J. Brandt, C. Geels, K. Hansen, J. Christensen, M. Andersen, E. Solazzo, I. Kioutsioukis, U. Alyuz, A. Balzarini, R. Baro, R. Bellasio, R. Bianconi, J. Bieser, A. Colette, G. Curci, A. Farrow, J. Flemming, A. Fraser, P. Jimenez-Guerrero, N. Kitwiroon, C. Liang, U. Nopmongcol, G. Pirovano, L. Pozzoli, M. Prank, R. Rose, R. Sokhi, P. Tuccella, A. Unal, M. Garcia Vivanco, J. West, G. Yarwood, C. Hogrefe, and S. Galmarini. Assessment and economic valuation of air pollution impacts on human health over Europe and the United States as calculated by a multi-model ensemble in the framework of AQMEII3.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 18: 5967-5989, (2018).",
            "accessLevel": "public",
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                "020:094"
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            "identifier": "https://doi.org/10.23719/1378467",
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                "ensemble modeling",
                "air quality health impacts",
                "economic valuation of health impacts",
                "model evaluation"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
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            },
            "distribution": [
                {
                    "title": "ImEtAl_Gridded_Data_SO2_GLO.zip",
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                    "subOrganizationOf": {
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                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1378467/documents/HogrefeChristian_A-02v7_DataDescription_ImEtAl.zip",
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            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
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        },
        {
            "title": "A Workflow for Identifying Metabolically Active Chemicals to Complement in vitro Toxicity Screening",
            "description": "This data includes metabolite predictions for in vitro inactive chemicals, predictions of those metabolite's estrogen receptor binding activity, in vitro and in silico information regarding parent compound binding activities, linking of metabolite structures and routes to parent compounds, and estimates of binding activity obtained from literature when possible. \n\nThis dataset is associated with the following publication:\nLeonard, J., C. Stevens, K. Mansouri, D. Chang, H. Pudukodu, S. Smith, and C. Tan. A Workflow for Identifying Metabolically Active Chemicals to Complement in vitro Toxicity Screening.   Computational Toxicology. Elsevier B.V., Amsterdam,  NETHERLANDS, 6: 71-83, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407568",
            "keyword": [
                "Metabolism",
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                "in vitro assays",
                "bioactivity"
            ],
            "contactPoint": {
                "fn": "Yu-Mei Tan",
                "hasEmail": "mailto:tan.cecilia@epa.gov"
            },
            "distribution": [
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                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407568/ScienceHub_Files.zip",
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            "modified": "2017-06-25",
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                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
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            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
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        {
            "title": "Predict_Organ_Toxicity_ChemResTox_Data",
            "description": "We use a supervised machine learning strategy to systematically investigate the relative importance of study type, machine learning algorithm, and type of descriptor on predicting in vivo repeat-dose toxicity at the organ-level.   A total of 985 compounds were represented using chemical structural descriptors, ToxPrint chemotype descriptors, and bioactivity descriptors from ToxCast in vitro high-throughput screening assays.  Using ToxRefDB, a total of 35 target organ outcomes were identified that contained at least 100 chemicals (50 positive and 50 negative). Supervised machine learning was performed using Na&iuml;ve Bayes, k-nearest neighbor, random forest, classification and regression trees, and support vector classification approaches. Model performnce was assessed based on F1 scores using five-fold cross-validation with balanced bootstrap replicates.  Fixed effects modeling showed the variance in F1 scores was explained mostly by target organ outcome, followed by descriptor type, machine learning algorithm, and interactions between these three factors.  A combination of bioactivity and chemical structure or chemotype descriptors were the most predictive. Model performance improved with more chemicals (up to a maximum of 24%) and these gains were correlated (&rho;= 0.92) with the number of chemicals. \n\nThis dataset is associated with the following publication:\nLiu, J., G. Patlewicz, A. Williams, R. Thomas, and I. Shah. (Chemical Research in Toxicology) Predicting organ toxicity using in vitro bioactivity data and chemical structure.   CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, USA, 30: 2046\u22122059, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
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                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407008",
            "keyword": [
                "machine learning",
                "qsar",
                "bioactivity",
                "chemotypes",
                "ToxCast",
                "ToxRefDB",
                "High throughput screening",
                "high throughput toxicology"
            ],
            "contactPoint": {
                "fn": "Keith Houck",
                "hasEmail": "mailto:houck.keith@epa.gov"
            },
            "distribution": [
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                    "title": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/ShahImran/Predicting_Organ_Toxicity/",
                    "accessURL": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/ShahImran/Predicting_Organ_Toxicity/"
                }
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            "modified": "2017-09-28",
            "references": [
                "https://doi.org/10.1021/acs.chemrestox.7b00084"
            ],
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                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
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            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Chlorine and DBP formation experimental data and kinetic modeling analysis to derive chlorine decay and DBP formation kinetic constants under different pipe flow conditions",
            "description": "Experimental and modeling datasets and results. \n\nThis dataset is associated with the following publication:\nYang, J., Y. Zhao, Y. Shao, T. Speth, and T. Zhang. The Dependence of Chlorine Decay and DBP Formation Kinetics On Pipe Flow Properties in Drinking Water Distribution.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 141: 32-45, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
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            "keyword": [
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                "THM formation",
                "Pipe flow hydrodynamics",
                "Drinking water distribution system",
                "DBP formation",
                "modeling"
            ],
            "contactPoint": {
                "fn": "Yingping Yang",
                "hasEmail": "mailto:yang.jeff@epa.gov"
            },
            "distribution": [
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                    "title": "regression constant.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407631/regression%20constant.xlsx",
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                    "title": "Loop4&5Results121107.xls",
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                {
                    "title": "Loop4&5Results041107.xls",
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                    "title": "Loop4&5Results041807.xls",
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                {
                    "title": "Loop4&5Results061907.xls",
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                },
                {
                    "title": "Loop4&5Results062607.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407631/Loop4%265Results062607.xls",
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                },
                {
                    "title": "Loop4&5Results071007.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407631/Loop4%265Results071007.xls",
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                },
                {
                    "title": "Loop4&5Results091107.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407631/Loop4%265Results091107.xls",
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                {
                    "title": "Loop4&5Results091807.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407631/Loop4%265Results091807.xls",
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            ],
            "modified": "2017-09-13",
            "references": [
                "https://doi.org/10.1016/j.watres.2018.04.048"
            ],
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                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Use of Targeted and Untargeted Effects-based Monitoring Tools to Assess Impacts of Wastewater Effluents on Fish in the South Platte River, CO",
            "description": "Results of partial least squares (PLS) analysis of metabolite changes and contaminant concentrations to determine contaminants most likely to responsible for biological effects and to screen against those contaminants not responsible. \n\nThis dataset is associated with the following publication:\nEkman, D., K. Keteles, J. Beihoffer, J. Cavallin, K. Dahlin, J. Davis, A. Jastrow, J. Lazorchak, M. Mills, M. Murphy, D. Nguyen, A. Vajda, D. Villeneuve, D. Winkelman, and T. Collette. Evaluation of targeted and untargeted effects-based monitoring tools to assess impacts of contaminants of emerging concern on fish in the South Platte River, CO.   ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 239: 706-713, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1378558",
            "keyword": [
                "NMR",
                "vitellogenin",
                "fathead minnow",
                "environmental estrogens",
                "metabolomics"
            ],
            "contactPoint": {
                "fn": "Drew Ekman",
                "hasEmail": "mailto:ekman.drew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Ekman et al._2018_Env. Pollut.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378558/Ekman%20et%20al._2018_Env.%20Pollut.xlsx",
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                }
            ],
            "modified": "2018-05-01",
            "references": [
                "https://doi.org/10.1016/j.envpol.2018.04.054"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1378558/documents/Data%20Dictionary%20for%20Ekman%20et%20al._S.%20Platte_Input%20File.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "State and regional sensitivity spreadsheets for bar and pie charts",
            "description": "These files represent the state and regional summaries of sensitivities to formaldehyde, acetaldehyde and ozone to various sources and compounds. \n\nThis dataset is associated with the following publication:\nLuecken, D., S. Napelenok, M. Strum, R. Scheffe, and S. Phillips. Sensitivity of Ambient Atmospheric Formaldehyde and Ozone to Precursor Species and Source Types Across the United States.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(8): 4668\u20134675, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407657",
            "keyword": [
                "Formaldehyde",
                "NATA",
                "HAPs",
                "Sensitivity"
            ],
            "contactPoint": {
                "fn": "Deborah Luecken",
                "hasEmail": "mailto:luecken.deborah@epa.gov"
            },
            "distribution": [
                {
                    "title": "FORM_sens_Jan_2017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407657/FORM_sens_Jan_2017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Form_sens_July_2017.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407657/Form_sens_July_2017.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Ozone_sens_Jan_2017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407657/Ozone_sens_Jan_2017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Ozone_sens_July_2017.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407657/Ozone_sens_July_2017.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "ALD2_sens_Jan_2017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407657/ALD2_sens_Jan_2017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "ALD_sens_July_2017.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407657/ALD_sens_July_2017.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "emissions.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407657/emissions.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-07",
            "references": [
                "https://doi.org/10.1021/acs.est.7b05509"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Aircraft emission impacts on air quality",
            "description": "Data sets include information on emissions of air pollutants, description of 3-D meteorological state of the atmosphere, and output from the CMAQ model over the northern hemisphere and contiguous U.S. This dataset is not publicly accessible because: This research was conducted a part of the primary author's Ph.D. dissertation at the University of North Carolina at Chapel Hill. All data sets were created on the UNC computers and are housed there. Since the data sets are not directly available to the EPA investigator, they are not included in ScienceHub. It can be accessed through the following means: Data sets can be accessed by contacting Dr. Sarav Arunachalam at UNC - sarav@email.unc.edu. Format: Model input (3D meteorological fields and 3D emission files) and output are in netcdf format. Observational data sets used are publicly available and typically available as ascii files. \n\nThis dataset is associated with the following publication:\nVennam, L., W. Vizuete, K. Talgo, M. Omary, F. Binkowski, J. Xing, R. Mathur, and S. Arunachalam. Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 122(24): 13,472\u201313,494, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407531",
            "keyword": [
                "Aircraft emissions",
                "Hemispheric CMAQ",
                "air pollution",
                "modeling"
            ],
            "contactPoint": {
                "fn": "Rohit Mathur",
                "hasEmail": "mailto:mathur.rohit@epa.gov"
            },
            "distribution": [],
            "modified": "2016-10-28",
            "references": [
                "https://doi.org/10.1002/2017jd026598"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
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                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "WRF and CMAQ Model Output",
            "description": "WRF and CMAQ model output for July 2011. This dataset is not publicly accessible because: The files are too large. It can be accessed through the following means: The data can be accessed through NCC's tape archival storage system (ASM). Format: WRF and CMAQ model output for July 2011. \n\nThis dataset is associated with the following publication:\nForoutan, H., and J. Pleim. Improving the simulation of convective dust storms in regional-to-global models.   Journal of Advances in Modeling Earth Systems. John Wiley & Sons, Inc., Hoboken, NJ, USA, 9(5): 2046\u20132060, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407597",
            "keyword": [
                "Dust",
                "haboob",
                "convective parameterization",
                "lightning assimilation",
                "CMAQ"
            ],
            "contactPoint": {
                "fn": "Hosein Foroutan",
                "hasEmail": "mailto:foroutan.hosein@epa.gov"
            },
            "distribution": [],
            "modified": "2017-03-01",
            "references": [
                "https://doi.org/10.1002/2017ms000953"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1407597/documents/ForoutanHosein_A-15dz_Data_Dictionary_20170808.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "LCA of fuels and stoves in India, China, Ghana, and Kenya",
            "description": "This provides 4 results workbooks and 7 workbooks documenting the inventory. \n\nThis dataset is associated with the following publications:\nMorelli, B., S. Cashman, and M. Rodgers. Life Cycle Assessment of Cookstoves and Fuels in India, China, Kenya, and Ghana. U.S. Environmental Protection Agency, Washington, DC, USA, 2017.\nCashman, S. Life-Cycle Assessment of Cookstove Fuels in India and China. U.S. Environmental Protection Agency, Washington, DC, USA, 2016.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407614",
            "keyword": [
                "Life cycle assessment (LCA)",
                "openLCA",
                "cookstoves",
                "indoor air quality",
                "energy ladder"
            ],
            "contactPoint": {
                "fn": "Susan Thorneloe-Howard",
                "hasEmail": "mailto:thorneloe.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "archive.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407614/archive.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "EPA Phase II Cookstove LCA Results - KE.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407614/EPA%20Phase%20II%20Cookstove%20LCA%20Results%20-%20KE.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "EPA Phase II Cookstove LCA Results - IN.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407614/EPA%20Phase%20II%20Cookstove%20LCA%20Results%20-%20IN.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "EPA Phase II Cookstove LCA Results - CN.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407614/EPA%20Phase%20II%20Cookstove%20LCA%20Results%20-%20CN.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "EPA Phase II Cookstove LCA Results - GH.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407614/EPA%20Phase%20II%20Cookstove%20LCA%20Results%20-%20GH.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "SI6. Charcoal Kiln Supplementary Information.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407614/SI6.%20Charcoal%20Kiln%20Supplementary%20Information.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "SI3. Fuel Mix Scenario Supplementary Information.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407614/SI3.%20Fuel%20Mix%20Scenario%20Supplementary%20Information.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "SI4. Cookstove Electricity Scenario Supplementary Information.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407614/SI4.%20Cookstove%20Electricity%20Scenario%20Supplementary%20Information.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "SI2. Stove LCI Supplementary Information.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407614/SI2.%20Stove%20LCI%20Supplementary%20Information.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "SI7. Biogas Modeling Supplementary Information.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407614/SI7.%20Biogas%20Modeling%20Supplementary%20Information.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "SI1. Stove Use and Emissions Supplementary Information.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407614/SI1.%20Stove%20Use%20and%20Emissions%20Supplementary%20Information.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "SI5. Crop Residue Supplementary Information.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407614/SI5.%20Crop%20Residue%20Supplementary%20Information.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-14",
            "references": [
                "https://nepis.epa.gov/Exe/ZyPDF.cgi/P100T7UD.PDF?Dockey=P100T7UD.PDF"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "StreamCat",
            "description": "The StreamCat Dataset provides summaries of natural and anthropogenic landscape features for ~2.65 million streams, and their associated catchments, within the conterminous USA. \n\nThis dataset is associated with the following publications:\nHill, R.A., M. Weber , S. Leibowitz , T. Olsen , and D.J. Thornbrugh. The Stream-Catchment (StreamCat) Dataset: A database of watershed metrics for the conterminous USA.   JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION. American Water Resources Association, Middleburg, VA, USA,  9, (2015).\nHill, R., E. Fox, S. Leibowitz, T. Olsen, D. Thornbrugh, and M. Weber. Predictive Mapping of the Biotic Condition of Conterminous-USA Rivers and Streams.   ECOLOGICAL APPLICATIONS. Ecological Society of America, Ithaca, NY, USA, 27(8): 2397-2415, (2017).\nFox, E., R. Hill, S. Leibowitz, T. Olsen, D. Thornbrugh, and M. Weber. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.   ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 189(316): 1-20, (2017).\nThornbrugh, D., S. Leibowitz, R. Hill, M. Weber, Z. Johnson, T. Olsen, J. Flotemersch, J. Stoddard, and D. Peck. Mapping watershed integrity for the conterminous United States...   ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 85: 1133-1148, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407613",
            "keyword": [
                "streams",
                "catchments",
                "watersheds",
                "watershed metrics",
                "National Hydrography Dataset",
                "National Hydrography Dataset Plus (NHDPlus)",
                "spatial prediction",
                "aquatic condition",
                "National Aquatic Resource Surveys"
            ],
            "contactPoint": {
                "fn": "Scott Leibowitz",
                "hasEmail": "mailto:leibowitz.scott@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/streamcat-dataset"
                }
            ],
            "modified": "2017-07-11",
            "references": [
                "https://doi.org/10.1111/1752-1688.12372",
                "https://doi.org/10.1002/eap.1617",
                "https://doi.org/10.1007/s10661-017-6025-0",
                "https://doi.org/10.1016/j.ecolind.2017.10.070"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://gaftp.epa.gov/EPADataCommons/ORD/NHDPlusLandscapeAttributes/StreamCat/Documentation/DataDictionary.html",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "LaneCharles_A-dv4f_Data_20180430.xls",
            "description": "Data associated with the paper, \"Comparing pixel- and object-based approaches in effectively classifying wetland-dominated landscapes\". \n\nThis dataset is associated with the following publication:\nBerhane, T., C. Lane, Q. Wu, O. Anenkhonov, V. Chepinoga, B. Autrey, and H. Liu. Comparing Pixel- and Object-Based Approaches in Effectively Classifying Wetland-Dominated Landscapes.   Remote Sensing. MDPI AG, Basel,  SWITZERLAND, 10(1): 46, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1500025",
            "keyword": [
                "wetlands"
            ],
            "contactPoint": {
                "fn": "Charles Lane",
                "hasEmail": "mailto:lane.charles@epa.gov"
            },
            "distribution": [
                {
                    "title": "LaneCharles_A-dv4f_Data_20180430.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500025/LaneCharles_A-dv4f_Data_20180430.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-05-08",
            "references": [
                "https://doi.org/10.3390/rs10010046"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "LaneCharles_A-zpd2_Data_30042018.xlsx",
            "description": "Data associated with the paper, \"Decision-Tree, Rule-Based, and Random Forest Classification of High-Resolution Multispectral Imagery for Wetland Mapping and Inventory\". \n\nThis dataset is associated with the following publication:\nBerhane, T., C. Lane, Q. Wu, B. Autrey, O. Anenkhonov, V. Chepinoga, and H. Liu. Decision-Tree, Rule-Based, and Random Forest Classification of High-Resolution Multispectral Imagery for Wetland Mapping and Inventory.   Remote Sensing. MDPI AG, Basel,  SWITZERLAND, 10(4): 580, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1500026",
            "keyword": [
                "wetland"
            ],
            "contactPoint": {
                "fn": "Charles Lane",
                "hasEmail": "mailto:lane.charles@epa.gov"
            },
            "distribution": [
                {
                    "title": "LaneCharles_A-zpd2_Data_30042018.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500026/LaneCharles_A-zpd2_Data_30042018.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-05-08",
            "references": [
                "https://doi.org/10.3390/rs10040580"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Las Vegas Near Road Data - PM2.5 and Black Carbon",
            "description": "Las Vegas Near Road Data PM2.5 and Black Carbon Data. \n\nThis dataset is associated with the following publication:\nKimbrough, S., T. Hanley, G. Hagler, R. Baldauf, M. Snyder, and H. Brantley. Influential factors affecting black carbon trends at four sites of differing distance from a major highway in Las Vegas.   Air Quality, Atmosphere & Health. Springer Netherlands,   NETHERLANDS, 11(2): 181-196, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1373706",
            "keyword": [
                "Black Carbon",
                "pm2.5",
                "near road",
                "near source",
                "air quality",
                "air pollution"
            ],
            "contactPoint": {
                "fn": "Evelyn Kimbrough",
                "hasEmail": "mailto:kimbrough.sue@epa.gov"
            },
            "distribution": [
                {
                    "title": "PM and BC data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1373706/PM%20and%20BC%20data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-01-25",
            "references": [
                "https://doi.org/10.1007/s11869-017-0519-3"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Space-time paired simulation-observation records",
            "description": "Files uploaded to ScienceHub pair the model results in space and time to observations of NCAR NOy, NO, NO2 and O3, UC Berkeley NO2, peroxy nitrates, alkyl nitrates, and nitric acid, made aboard the NASA P3B aircraft during the DISCOVER-AQ, Maryland, 2011. Data are paired as follows: Model predictions are paired with aircraft measurements in space where aircraft latitude, longitude, altitude were matched to nearest grid cell center and model layer center height.  Fifteen second averages of measurements were matched to modeled estimates in time to the nearest hour.\r\n\r\nObservational data is also archived at the NASA LaRC Atmospheric Sciences Data Center (https://www-air.larc.nasa.gov/data.htm). \n\nThis dataset is associated with the following publication:\nSimon, H., K. Baker, L. Valin, J. Crawford, S. Puesede, J. Kelly, K. Foley, R. Cohen, B. Timin, A. Weinheimer, N. Possiel, C. Owen, C. Misenis, G. Diskin, A. Fried, and B. Henderson. Characterizing CO and NOy Sources and Relative Ambient Ratios in the Baltimore Area Using Ambient Measurements and Source Attribution Modeling.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 123(6): 3304-3320, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407577",
            "keyword": [
                "Ozone",
                "air quality",
                "NOx emissions",
                "CO emissions",
                "Air Quality Model"
            ],
            "contactPoint": {
                "fn": "Lukas Valin",
                "hasEmail": "mailto:valin.lukas@epa.gov"
            },
            "distribution": [
                {
                    "title": "paired-DISCOVER-AQ_CMAQ-ISAM_datafiles.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407577/paired-DISCOVER-AQ_CMAQ-ISAM_datafiles.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "https://www-air.larc.nasa.gov/missions/discover-aq/dataaccess.htm",
                    "accessURL": "https://www-air.larc.nasa.gov/missions/discover-aq/dataaccess.htm"
                }
            ],
            "modified": "2017-04-06",
            "references": [
                "https://doi.org/10.1002/2017jd027688"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Census and Facility Emissions Dataset",
            "description": "Data Sources, including links; \nData Dictionary; \n2009-2013 American Community Survey, Block group-level Population Data; \n2010 Decennial Census, Block group-level Population Data; \n2008 National Emissions Inventory, Facility-level Data; \n2011 National Emissions Inventory, Facility-level Data; \n2014 National Emissions Inventory, Facility-level Data; \n2010 Rural-Urban Commuting Area Codes, Tract-level Data;\n2011 PM 2.5 Daily Average Fused Air Quality Surface Using Downscaling (FAQSD) Output, mean Tract-level Data, CONUS. \n\nThis dataset is associated with the following publication:\nMikati, I., A. Benson, T. Luben, J. Sacks, and J. Richmond-Bryant. Disparities in Distribution of Particulate Matter Emission Sources by Race and Poverty Status.   American Journal of Public Health. American Public Health Association, Washington, DC, USA, 108(4): 480-485, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:062"
            ],
            "identifier": "https://doi.org/10.23719/1407543",
            "keyword": [
                "particulate matter",
                "national emissions inventory",
                "american community survey"
            ],
            "contactPoint": {
                "fn": "Ihab Mikati",
                "hasEmail": "mailto:mikati.ihab@epa.gov"
            },
            "distribution": [
                {
                    "title": "Mikati_A-hdrp_census-facility-emissions-dataset-20170509.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407543/Mikati_A-hdrp_census-facility-emissions-dataset-20170509.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-05-09",
            "references": [
                "https://doi.org/10.2105/ajph.2017.304297"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "LVdata 05182016 on-road estimates",
            "description": "Meteorological and concentration data at the Las Vegas I-15 monitoring site. \n\nThis dataset is associated with the following publications:\nRichmond-Bryant, J., M. Snyder, C. Owen, and S. Kimbrough. Factors associated with NO2 and NOx concentration gradients near a highway.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA,  214-226, (2017).\nRichmond-Bryant , J., C. Owen , S. Graham , M. Snyder, S. McDow , M. Oakes, and S. Kimbrough. Estimation of on-road NO2 concentrations, NO2/NOx ratios, and related roadway gradients from near-road monitoring data.   Air Quality, Atmosphere & Health. Springer Netherlands,   NETHERLANDS,  611-625, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407612",
            "keyword": [
                "near road",
                "oxides of nitrogen",
                "nitrogen dioxide",
                "NO2",
                "NOx"
            ],
            "contactPoint": {
                "fn": "Evelyn Kimbrough",
                "hasEmail": "mailto:kimbrough.sue@epa.gov"
            },
            "distribution": [
                {
                    "title": "LVdata 05182016 on-road estimates REVISED Q3 only.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407612/LVdata%2005182016%20on-road%20estimates%20REVISED%20Q3%20only.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-05-18",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2017.11.026",
                "https://doi.org/10.1007/s11869-016-0455-7"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1407612/documents/dictionary%2005212018%20v2.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Acrolein Inhalation Alters Myocardial Synchrony and Performance at and Below Exposure Concentration that Cause Ventilatory Responses in Mice",
            "description": "we examined the cardiovascular effects acrolein inhalation, particularly on myocardial synchrony and performance via ultrasound echocardiography. Male C57Bl/6J mice (n=6/group) were exposed to filtered air (FA), 0.3 ppm acrolein, or 3.0 ppm acrolein for 3 hours in whole body plethysmography chambers. Cardiac strain data, heart function, and transmitral blood flow were investigated with echocardiography (40 MHz) 1 day prior to exposure, 1 hour after exposure, and 1 day after exposure. During the first 30 minutes of exposure, breathing frequency decreased. tidal volume increased, and expiratory/inspiratory time ratio increased in response to 3.0 ppm acrolein. Elapsed time between peak strain in adjacent wall segments (i.e. myocardial strain delay), a measure of myocardial dyssynchrony, increased significantly in mice exposed to 3.0 ppm acrolein at 1 and 24 hours post-exposure. Mice exposed to 0.3 ppm acrolein did not demonstrate changes in myocardial synchrony but did show decreases in myocardial performance, i.e. increased Tei index, at both 1 and 24 hours post-exposure. \n\nThis dataset is associated with the following publication:\nThompson, L., A. Ledbetter , N. Coates , W. Cascio , M. Hazari , and A. Farraj. Acrolein inhalation alters myocardial synchrony and performance at and below exposure concentrations that cause ventilatory responses.   Cardiovascular Toxicology. Humana Press Incorporated, Totowa, NJ, USA, 17(2): 97-108, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1427298",
            "keyword": [
                "air quality",
                "air pollution",
                "acrolein",
                "Ambient air quality",
                "heart function",
                "myocardial synchrony",
                "myocardial dyssynchrony",
                "echocardiography"
            ],
            "contactPoint": {
                "fn": "Leslie Thompson",
                "hasEmail": "mailto:thompson.leslie@epa.gov"
            },
            "distribution": [
                {
                    "title": "LT1 Thompson et al Acrolein Study_Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1427298/LT1%20Thompson%20et%20al%20Acrolein%20Study_Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-03-20",
            "references": [
                "https://doi.org/10.1007/s12012-016-9360-4"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Hong and Purucker sensitivity analysis code and data",
            "description": "Code and data associated with Hong T, Purucker ST, 2018. Spatiotemporal sensitivity analysis of vertical transport of pesticides in soil, Environmental Modelling and Software, 105: 24-38, https://doi.org/10.1016/j.envsoft.2018.03.018. \n\nThis dataset is associated with the following publication:\nHong, T., and T. Purucker. Spatiotemporal sensitivity analysis of vertical transport of pesticides in soil.   ENVIRONMENTAL MODELLING & SOFTWARE. Elsevier Science, New York, NY,   105: 24-38, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1435024",
            "keyword": [
                "Pesticide Root Zone Model (PRZM)",
                "Sobol' sensitivity analysis",
                "global sensitivity analysis"
            ],
            "contactPoint": {
                "fn": "Steven Purucker",
                "hasEmail": "mailto:purucker.tom@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://github.com/puruckertom/hongpurucker_przm_sobol",
                    "accessURL": "https://github.com/puruckertom/hongpurucker_przm_sobol"
                }
            ],
            "modified": "2018-05-14",
            "references": [
                "https://doi.org/10.1016/j.envsoft.2018.03.018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supporting data for \"Conway, G., Robertson, D., Chadwell, C., McDonald, J. et al. 2018 Evaluation of Emerging Technologies on a 1.6 L Turbocharged GDI Engine. SAE 2018-01-1423\" V1",
            "description": "Low-pressure loop exhaust gas recirculation (LP- EGR) combined with higher compression ratio, is a technology package that has been a focus of research to increase engine thermal efficiency of downsized, turbocharged gasoline direct injection (GDI) engines. Research shows that the addition of LP-EGR reduces the propensity to knock that is experienced at higher compression ratios. To investigate the interaction and compatibility between increased compression ratio and LP-EGR, a 1.6 L Turbocharged GDI engine was modified to run with LP-EGR at a higher compression ratio (12:1 versus 10.5:1) via a piston change. This work includes the results of baseline testing on an engine run with a prototype controller and initially tuned to mimic an original equipment manufacturer (OEM) baseline control strategy running on premium fuel (92.8 anti-knock index). This paper then presents test results after first adding LP-EGR to the baseline engine, and then also increasing the compression ratio (CR) using 12:1 pistons. As a last step, the 10.5 CR engine with LP-EGR was run on regular fuel (87.7 anti-knock index) to verify that this configuration could be calibrated to maintain performance like the baseline engine running on premium fuel. To understand the effect of each technology and operating strategy combination on vehicle fuel economy, the various engine maps were compared in EPA\u2019s Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool over U.S. regulatory drive cycles. This work was done as part of the EPA's continuing assessment of advanced light-duty automotive technologies to support a Midterm Evaluation of Light-duty Vehicle GHG Standards. \n\nThis dataset is associated with the following publication:\nMcDonald, J., M. Stuhldreher, D. Barba, J. Kargul, G. Conway, D. Robertson, and C. Chadwell. Evaluation of Emerging Technologies on a 1.6 L Turbocharged GDI Engine.   SAE Technical Paper Series. SAE International, Warrendale, PA, USA,  15, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1435450",
            "keyword": [
                "GHG",
                "Light-duty Vehicles",
                "air quality",
                "Energy Demand",
                "Internal Combustion Engines",
                "Hybrid Electric Vehicles",
                "Electric Vehicles"
            ],
            "contactPoint": {
                "fn": "Joseph McDonald",
                "hasEmail": "mailto:mcdonald.joseph@epa.gov"
            },
            "distribution": [
                {
                    "title": "SAE 2018-01-1423 Evaluation of Emerging Tech. on a 1.6 L TGDI Engine.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435450/SAE%202018-01-1423%20Evaluation%20of%20Emerging%20Tech.%20on%20a%201.6%20L%20TGDI%20Engine.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-05-01",
            "references": [
                "https://doi.org/10.4271/2018-01-1423"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Gap to gap region data: soil, water level, modflow output hyporheic flow pathlines (2013-2015)",
            "description": ". In this study Light Detection and Ranging (LiDAR) data were used along with the head data from observation wells and stage data from rivers to setup and calibrate a groundwater model for 458 km2 of area within Gap to Gap reach of the Yakima River, WA. \n\nThis dataset is associated with the following publication:\nSingh, H., B. Faulkner, A. Keeley, J. Freudenthal, and K. Forshay. Floodplain restoration increases hyporheic flow in the Yakima River Watershed, Washington.   ECOLOGICAL ENGINEERING. Elsevier Science Ltd, New York, NY, USA, 116: 110-120, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1394800",
            "keyword": [
                "elevation",
                "stage",
                "hyporheic pathlines",
                "hyporheic flow",
                "MODFLOW",
                "Floodplain",
                "Levee setback"
            ],
            "contactPoint": {
                "fn": "Barton Faulkner",
                "hasEmail": "mailto:faulkner.bart@epa.gov"
            },
            "distribution": [
                {
                    "title": "FaulknerBarton_A-rxx2_SDMP_20170825.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394800/FaulknerBarton_A-rxx2_SDMP_20170825.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "HSsdmp_template_short.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394800/HSsdmp_template_short.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "QA.Summary.HarshSingh20170825.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394800/QA.Summary.HarshSingh20170825.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-05-17",
            "references": [
                "https://doi.org/10.1016/j.ecoleng.2018.02.001"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dendrochronological data for western Oregon",
            "description": "Master chronologies of radial stem growth of Douglas-fir for western Oregon. \n\nThis dataset is associated with the following publications:\nLee, E., P. Beedlow, R. Waschmann, D.T. Tingey, S. Cline, M. Bollman, C. Wickham, and C. Carlile. Regional patterns of increasing Swiss needle cast impacts on Douglas-fir growth with warming temperatures..   Ecology and Evolution. Wiley-Blackwell Publishing, Hoboken, NJ, USA, 7(24): 11167-11196, (2017).\nLee, E., C. Wickham, P. Beedlow, R. Waschmann, and D.T. Tingey. A likelihood-based time series modeling approach for application in dendrochronology to examine the growth-climate relations and forest disturbance history.   Dendrochronologia. Elsevier, Shannon,  IRELAND, 45: 132-144, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1419254",
            "keyword": [
                "climate change",
                "dendrochronology",
                "Douglas-fir",
                "Pacific Decadal Oscillation",
                "Pacific Northwest",
                "Swiss needle cast"
            ],
            "contactPoint": {
                "fn": "E. Lee",
                "hasEmail": "mailto:lee.ehenry@epa.gov"
            },
            "distribution": [
                {
                    "title": "falls_creek_douglas-fir_ringwidth.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1419254/falls_creek_douglas-fir_ringwidth.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "horse_creek_trail_upper_douglas-fir_ringwidth.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1419254/horse_creek_trail_upper_douglas-fir_ringwidth.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "cascade_head_14_douglas-fir_ringwidth.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1419254/cascade_head_14_douglas-fir_ringwidth.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "horse_creek_trail_lower_douglas-fir_ringwidth.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1419254/horse_creek_trail_lower_douglas-fir_ringwidth.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "jackson_place_douglas-fir_ringwidth.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1419254/jackson_place_douglas-fir_ringwidth.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "moose_mtn_douglas-fir_ringwidth.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1419254/moose_mtn_douglas-fir_ringwidth.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "toad_creek_douglas-fir_ringwidth.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1419254/toad_creek_douglas-fir_ringwidth.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "woods_creek_douglas-fir_ringwidth.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1419254/woods_creek_douglas-fir_ringwidth.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "soapgrass_mtn_douglas-fir_ringwidth.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1419254/soapgrass_mtn_douglas-fir_ringwidth.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2018-05-15",
            "references": [
                "https://doi.org/10.1002/ece3.3573",
                "https://doi.org/10.1016/j.dendro.2017.08.003"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1419254/documents/Data%20dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supporting data for \"Lee, S.D., Cherry, J., Safoutin, M., McDonald, J. et al. 2018. Modeling and Validation of 48 V Mild Hybrid Lithium-Ion Battery Pack. SAE 2018-01-0433\" V1",
            "description": "The purpose of this work was to develop and validate a 48 V lithium-ion battery model for integration into EPA\u2019s ALPHA vehicle simulation model and that can also be used within Gamma Technologies, LLC (Westmont, IL) GT-DRIVE\u2122 vehicle simulations.  These vehicle models allow simulation of energy flows and CO2 emissions for mild hybrid electric vehicles over EPA regulatory drive cycles and during real-world driving.  The battery model is a standard equivalent circuit model with two-time constant resistance-capacitance (RC) blocks. Resistances and capacitances were calculated using test data from an 8 Ah, 0.4 kWh, 48 V (nominal) lithium-ion battery obtained from a Tier 1 automotive supplier, A123 Systems, and developed specifically for 48 V MHEV applications. The A123 Systems battery has 14 pouch-type lithium ion cells arranged in a 14 series and 1 parallel (14S1P) configuration. The RC battery model was validated using battery test data generated by a hardware-in-the-loop (HIL) system that simulated the impact of mild hybrid electric vehicle (MHEV) operation on the A123 systems 48 V battery pack over U.S. regulatory drive cycles. The HIL system matched charge and discharge data originally generated by Argonne National Laboratory (ANL) during chassis dynamometer testing of a 2013 Chevy Malibu Eco 115 V MHEV. All validation testing was performed at the Battery Test Facility (BTF) at the U.S. EPA National Vehicle and Fuel Emissions Laboratory (NVFEL) in Ann Arbor, Michigan. The simulated battery voltages, currents, and state of charge (SOC) of the HIL tests were in good agreement with vehicle test data over a number of different drive cycles and excellent agreement was achieved between RC model simulations of the 48 V battery and HIL battery test data. \n\nThis dataset is associated with the following publication:\nLee, S., J. Cherry, M. Safoutin, J. McDonald, and M. Olechiw. Modeling and Validation of 48V Mild Hybrid Lithium-ion Battery Pack.   SAE Technical Paper Series. SAE International, Warrendale, PA, USA,  11, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1435437",
            "keyword": [
                "GHG",
                "Light-duty Vehicles",
                "air quality",
                "Energy Demand",
                "Internal Combustion Engines",
                "Hybrid Electric Vehicles",
                "Electric Vehicles"
            ],
            "contactPoint": {
                "fn": "Joseph McDonald",
                "hasEmail": "mailto:mcdonald.joseph@epa.gov"
            },
            "distribution": [
                {
                    "title": "SAE 2018-01-0433 48V Li-Ion Battery Model.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435437/SAE%202018-01-0433%2048V%20Li-Ion%20Battery%20Model.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-05-01",
            "references": [
                "https://doi.org/10.4271/2018-01-0433"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supporting data for \"Lee, S., Cherry, J., Safoutin, M., Neam, A., McDonald, J., Newman, K.  2018. Modeling and Controls Development of 48 V Mild Hybrid Electric Vehicles. SAE 2018-01-0413\" V1",
            "description": "The purpose of this work was to develop a 48 V mild hybrid electric vehicle (MHEV) model for drive cycle simulation using the EPA Advanced Light-Duty Powertrain and Hybrid Analysis tool (ALPHA).  The work included controls development, component and vehicle modeling , and model validation for simulations of a vehicle with a 48 V Belt Integrated Starter Generator (BISG) MHEV system.  An initial model design was also developed for a 48 V inline on-axis P2-configuration MHEV and will be validated as part of future work. Both MHEV configurations were developed into sub-models using a MATLAB/Simulink/Stateflow tool.  The sub-models have subsequently been integrated into EPA\u2019s ALPHA vehicle model.  Initial sub-model development and validation was conducted using the commercially-available Gamma Technology GT-DRIVE vehicle simulation model. The mild hybrid electric vehicle model was validated using vehicle data obtained from Argonne National Laboratory (ANL) chassis dynamometer tests of a 2013 Chevrolet Malibu Eco 115 V 15 kW BISG mild hybrid electric vehicle. The simulated fuel economy, engine torque/speed, motor torque/speed, engine on-off controls, battery voltage, current, and State of Charge (SOC) were all in good agreement with the vehicle test data on a number of drive schedules. The developed 48 V mild hybrid electric vehicle model can be used to estimate the GHG emissions and fuel economy of 48 V mild hybrid electric vehicles over the EPA regulatory drive cycles and to estimate off-cycle GHG emissions, real-world GHG emissions, and vehicle energy flows. The 48 V mild hybrid electric vehicle model will be further validated with additional 48 V mild hybrid electric vehicle test data in the future as more vehicle models become available. EPA has included 48 V BISG mild hybrid electric vehicle technology in its assessment of CO2-reducing technologies available for compliance with U.S. GHG standards. \n\nThis dataset is associated with the following publication:\nLee, S., M. Safoutin, A. Neam, J. Cherry, and J. McDonald. Modeling and Controls Development of 48V Mild Hybrid Electric Vehicles.   SAE Technical Paper Series. SAE International, Warrendale, PA, USA,  15, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1435438",
            "keyword": [
                "GHG",
                "Light-duty Vehicles",
                "air quality",
                "Energy Demand",
                "Internal Combustion Engines",
                "Hybrid Electric Vehicles",
                "Electric Vehicles"
            ],
            "contactPoint": {
                "fn": "Joseph McDonald",
                "hasEmail": "mailto:mcdonald.joseph@epa.gov"
            },
            "distribution": [
                {
                    "title": "SAE 2018-01-0413 48V MHEV Model.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435438/SAE%202018-01-0413%2048V%20MHEV%20Model.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-05-01",
            "references": [
                "https://doi.org/10.4271/2018-01-0413"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supporting data for \"Robertson, D., Conway, G., Chadwell, C., McDonald, J. et al. 2018. Predictive GT-Power Simulation for VNT Matching on a 1.6 L Turbocharged GDI Engine. SAE 2018-01-0161\" V1",
            "description": "Low-pressure loop exhaust gas recirculation (LP- EGR) combined with higher compression ratio, is a technology package that has been a focus of research to increase engine thermal efficiency of downsized, turbocharged gasoline direct injection (GDI) engines. Research shows that the addition of LP-EGR reduces the propensity to knock that is experienced at higher compression ratios [1]. To investigate the interaction and compatibility between increased compression ratio and LP-EGR, a 1.6 L Turbocharged GDI engine was modified to run with LP-EGR at a higher compression ratio (12:1 versus 10.5:1) via a piston change. This paper presents the results of the baseline testing on an engine run with a prototype controller and initially tuned to mimic an original equipment manufacturer (OEM) baseline control strategy running on premium fuel (92.8 anti-knock index). This paper then presents test results after first adding LP-EGR to the baseline engine, and then also increasing the compression ratio (CR) using 12:1 pistons. As a last step, the 10.5 CR engine with LP-EGR was run on regular fuel (87.7 anti-knock index) to verify that this configuration could be calibrated to maintain performance like the baseline engine running on premium fuel. To understand the effect of each technology and operating strategy combination on vehicle fuel economy, the various engine maps were compared in EPA\u2019s Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool over U.S. regulatory drive cycles. This work was done as part of the EPA's continuing assessment of advanced light-duty automotive technologies to support a Midterm Evaluation of Light-duty Vehicle GHG Standards. \n\nThis dataset is associated with the following publication:\nMcDonald, J., J. Kargul, D. Barba, G. Conway, D. Robertson, and C. Chadwell. Predictive GT-Power Simulation for VNT Matching on a 1.6 L GDI Turbocharged Engine.   SAE Technical Paper Series. SAE International, Warrendale, PA, USA,  16, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1435449",
            "keyword": [
                "GHG",
                "Light-duty Vehicles",
                "air quality",
                "Energy Demand",
                "Internal Combustion Engines",
                "Hybrid Electric Vehicles",
                "Electric Vehicles"
            ],
            "contactPoint": {
                "fn": "Joseph McDonald",
                "hasEmail": "mailto:mcdonald.joseph@epa.gov"
            },
            "distribution": [
                {
                    "title": "SAE 2018-01-0161  1.6 L TGDI VNT Engine Model.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435449/SAE%202018-01-0161%20%201.6%20L%20TGDI%20VNT%20Engine%20Model.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-05-01",
            "references": [
                "https://doi.org/10.4271/2018-01-0161"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supporting datasets for paper \"Estimating Future Temperature Maxima in Lakes across the United States using a Surrogate Modeling Approach\"",
            "description": "Model input and simulation output files. \n\nThis dataset is associated with the following publication:\nButcher, J., T. Zi, M. Schmidt, T. Johnson, D. Nover, and C. Clark. Critical Lake Temperature Response to Climate Change across the United States.   PLoS ONE. Public Library of Science, San Francisco, CA, USA, 12(11): 1-16, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1376237",
            "keyword": [
                "climate",
                "change",
                "lake",
                "thermal"
            ],
            "contactPoint": {
                "fn": "Thomas Johnson",
                "hasEmail": "mailto:johnson.thomas@epa.gov"
            },
            "distribution": [
                {
                    "title": "Lakes_Data Files.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376237/Lakes_Data%20Files.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "https://osf.io/4r44z/",
                    "accessURL": "https://osf.io/4r44z/"
                }
            ],
            "modified": "2017-08-24",
            "references": [
                "https://doi.org/10.1371/journal.pone.0183499"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "MBRs LCI and LCIA data",
            "description": "This study calculated the cumulative energy and greenhouse gas (GHG) life cycle and cost profiles of transitional aerobic membrane bioreactors (AeMBR) and anaerobic MBRs (AnMBR). Membrane bioreactors (MBR) represent a promising technology for decentralized wastewater treatment and can produce recycled water to displace potable water. Energy recovery is also possible with methane generated from AnMBRs. In this study, scenarios for these technologies were investigated for different scale systems serving various population densities under various climate conditions with multiple methane recovery options. Details of the GHG life cycle and cost profiles for the AeMBR and AnMBR can be found in AeMBR_LCI_Cost_9-9-15.xls and AnMBR_LCI_Cost_9-9-15.xls respectively. Results of the previously described comparisons can be found can be found in MBR_LCIAResults_9-9-15.xlsx. \n\nThis dataset is associated with the following publication:\nCashman, S., C. Ma, J. Mosley, J. Garland, B. Crone, and X. Xue. Energy and greenhouse gas life cycle assessment and cost analysis of aerobic and anaerobic membrane bioreactor systems: Influence of scale, population density, climate, and methane recovery.   Bioresource Technology. Elsevier Online, New York, NY, USA, 254: 56-66, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1413477",
            "keyword": [
                "life cycle assessment",
                "Membrane Bioreactor",
                "Energy Demand",
                "Greenhouse gas",
                "Life Cycle Cost",
                "e Cycle Assessment"
            ],
            "contactPoint": {
                "fn": "Jay Garland",
                "hasEmail": "mailto:garland.jay@epa.gov"
            },
            "distribution": [
                {
                    "title": "AeMBR_LCI_Cost_9-9-15.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413477/AeMBR_LCI_Cost_9-9-15.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "AnMBR_LCI_Cost_9-9-15.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413477/AnMBR_LCI_Cost_9-9-15.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "MBR_LCIAResults_9-9-15.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413477/MBR_LCIAResults_9-9-15.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-04-23",
            "references": [
                "https://doi.org/10.1016/j.biortech.2018.01.060"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for MAMA Study and modeled predictions for PBDEs",
            "description": "Data set contains concentrations of persistent organic chemicals measured breast milk and blood for a small cohort of North Carolina women. \n\nThis dataset is associated with the following publication:\nMarchitti, S., S. Fenton, P. Mendola, J. Kenneke , and E. Hines. Polybrominated Diphenyl Ethers in Human Milk and Serum from the U.S. EPA MAMA Study: Modeled Predictions of Infant Exposure and Considerations for Risk Assessment.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 125(4): 706\u2013713, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407656",
            "keyword": [
                "breast milk",
                "POPs",
                "blood",
                "exposure",
                "life stage",
                "infant",
                "PBDE",
                "transporter",
                "Metabolism"
            ],
            "contactPoint": {
                "fn": "John Kenneke",
                "hasEmail": "mailto:kenneke.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "MAMA Study Data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407656/MAMA%20Study%20Data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-01-25",
            "references": [
                "https://doi.org/10.1289/ehp332"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data set fro Inhibition of Human ABC efflux transporters p-gp and BCRP by BDE-47 hydroxylated metabolite 6-OH-BDE-47",
            "description": "In vitro data from cell-based assays on the inhibition of BDE and its hydroxylated metabolite on ABC transporters. \n\nThis dataset is associated with the following publication:\nMarchitti, S., C. Mazur, C. Dillingham, S. Rawat, A. Sharma, J. Zastre, and J. Kenneke. Inhibition of the Human ABC Efflux Transporters P-gp and BCRP by the BDE-47 Hydroxylated Metabolite 6-OH-BDE-47: Considerations for Human Exposure.   TOXICOLOGICAL SCIENCES. Society of Toxicology,    155(1): 270-282, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407655",
            "keyword": [
                "p-gp",
                "BCRP",
                "transporter",
                "exposure",
                "life stage",
                "breast milk",
                "infant",
                "PBDE",
                "Metabolism"
            ],
            "contactPoint": {
                "fn": "John Kenneke",
                "hasEmail": "mailto:kenneke.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data for Figures Marchitti SOT 2017.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407655/Data%20for%20Figures%20Marchitti%20SOT%202017.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-09-13",
            "references": [
                "https://doi.org/10.1093/toxsci/kfw209"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "McEachran target NTA Sciencehub entry 170926",
            "description": "This dataset contains:\nNTA Features - Aligned, processed, and matched HRMS features from non-target analysis for both positive and negative ESI modes for both sites and all three sampling months \nTargeted FWRS data - Monthly concentrations and chemical identifiers of all targeted CECs at the Forest Water Reuse System (FWRS)\nConventional WWTP Data - Monthly concentrations and chemical identifiers of all targeted CECs at the Conventional WWTP. \n\nThis dataset is associated with the following publication:\nMcEachran, A., M. Hedgespeth, S. Newton, R. McMahen, M. Strynar, D. Shea, and E. Guthrie Nichols. Comparison of emerging contaminants in receiving waters downstream of a conventional wastewater treatment plant and a forest-water reuse system.   ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH. Ecomed Verlagsgesellschaft AG, Landsberg,  GERMANY, 25(13): 12451-12463, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407653",
            "keyword": [
                "wastewater",
                "contaminants of emerging concern (CEC)",
                "forest-water reuse",
                "non-targeted analysis",
                "surface water"
            ],
            "contactPoint": {
                "fn": "Seth Newton",
                "hasEmail": "mailto:newton.seth@epa.gov"
            },
            "distribution": [
                {
                    "title": "McEachran target NTA Sciencehub entry 170926.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407653/McEachran%20target%20NTA%20Sciencehub%20entry%20170926.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-26",
            "references": [
                "https://doi.org/10.1007/s11356-018-1505-5"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Comparative study on the performance of Anaerobic and Aerobic Biotrickling Filter for the Removal of Chloroform",
            "description": "Method for the removal and degradation of harmful disinfection byproducts from drinking water. \n\nThis dataset is associated with the following publication:\nMezgebe, B., K. Palanisamy,, G. Sorial, E. Sahle-Demessie, A. Aly Hassan, and J. Lu. Comparative Study on the Performance of Anaerobic and Aerobic Biotrickling Filter for Removal of Chloroform.   ENVIRONMENTAL ENGINEERING SCIENCE. Mary Ann Liebert, Inc., Larchmont, NY, USA, 35(5): 462-471, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1435446",
            "keyword": [
                "Aerobic",
                "anaerobic",
                "Biotrickling Filter",
                "Microbial diversity",
                "trihalomethanes"
            ],
            "contactPoint": {
                "fn": "Endalkac Sahle-Demessie",
                "hasEmail": "mailto:sahle-demessie.endalkachew@epa.gov"
            },
            "distribution": [
                {
                    "title": "G-STD-0016294-JA-7-0_figs.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435446/G-STD-0016294-JA-7-0_figs.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "G-STD-0016294-JA-7-0.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435446/G-STD-0016294-JA-7-0.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-06-01",
            "references": [
                "https://doi.org/10.1089/ees.2017.0275"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1435446/documents/Data%20Dictionary_BiotrickleFiltration.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Las Vegas Data",
            "description": "Las Vegas Near Road Data. \n\nThis dataset is associated with the following publication:\nKimbrough , S., C. Owen, M. Snyder, and J. Richmond-Bryant. NO to NO2 conversion rate analysis and implications for dispersion model chemistry\r\nmethods using Las Vegas, Nevada near-road field measurements.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 165: 23-24, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1373703",
            "keyword": [
                "NO2",
                "NOx",
                "no2/nox ratio",
                "near source",
                "air quality",
                "air pollution"
            ],
            "contactPoint": {
                "fn": "Evelyn Kimbrough",
                "hasEmail": "mailto:kimbrough.sue@epa.gov"
            },
            "distribution": [
                {
                    "title": "LVdata.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1373703/LVdata.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2015-10-23",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2017.06.027"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Climate differentiates forest structure across a residential macrosystem",
            "description": "The extent of urban ecological homogenization depends on how humans build, inhabit, and manage cities.  Morphological and socio-economic facets of neighborhoods can drive the homogenization of forest cover, thus affecting urban ecological and hydrological processes, and ecosystem services.  Recent evidence, however, suggests that the same biophysical drivers differentiating composition and structure of natural forests can further counteract the homogenization of urban forests.  We hypothesize that climate can differentiate forest structure across residential macrosystems, regional-to-continental discontinuous systems of urban land.  To test this hypothesis, forest structure (tree and shrub cover and volume) was measured using LiDAR data and multispectral imagery across a residential macrosystem composed of 9 cities, 1503 neighborhoods, and 1.4 million residential parcels.  Cities were selected along a potential evapotranspiration (PET) gradient in the conterminous United States, ranging from the colder continental climate of Fargo, North Dakota (PET = 66.21 mm) to the hotter subtropical climate of Tallahassee, Florida (PET = 160.49 mm).  The relative effects of climate, urban morphology, and socio-economic variables on residential forest structure were assessed by using generalized linear models.  Climate differentiated forest structure of the residential macrosystem as hypothesized.  Average forest cover doubled along the PET gradient (0.39 - 0.78 m2 m-2), whereas average forest volume had a threefold increase (2.50 \u2013 8.12 m3 m-2).  Forest volume across neighborhoods increased exponentially with forest cover.  Urban morphology had a greater effect in homogenizing forest structure on residential parcels compared to socio-economics.  Climate and urban morphology variables best predicted residential forest structure, whereas socio-economic variables had the lowest predictive power.  Results indicate that climate can differentiate forest structure across residential macrosystems and may counteract the homogenizing effects of urban morphology and socio-economic drivers at city-wide scales.  This resonates with recent empirical work suggesting the existence of complex multi-scalar mechanisms that regulate ecological homogenization and ecosystem convergence among cities.  The study initiates high-resolution assessments of forest structure across entire urban macrosystems and breaks new ground for research on the ecological and hydrological significance of urban vegetation at subcontinental scale. \n\nThis dataset is associated with the following publication:\nOssola, A., and M. Hopton. Climate differentiates forest structure across a residential macrosystem.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 639: 1164-1174, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1393851",
            "keyword": [
                "Green Infrastructure",
                "socio-ecological systems",
                "urban ecology",
                "urban trees",
                "urban ecosystem convergence theory",
                "ecosystem services"
            ],
            "contactPoint": {
                "fn": "Matthew Hopton",
                "hasEmail": "mailto:hopton.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393851/Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Ranalyses.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1393851/Ranalyses.txt",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2017-08-17",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.05.237"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supporting Simulation Output - Earth Interactions article \"The Effects of Downscaling Method on the Variability of Simulated Watershed Response to Climate Change in Five U.S. Basins\"",
            "description": "Monthly summaries of simulated watershed responses to mid-century climate change scenarios in 5 U.S. basins. \n\nThis dataset is associated with the following publication:\nNover, D., J. Witt , J. Butcher, T. Johnson , and C. Weaver. The Effects of Downscaling Method on the Variability of Simulated Watershed Response to Climate Change in Five U.S. Basins.   Earth Interactions. American Meteorological Society, Boston, MA, USA, 20, 1-27, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390087",
            "keyword": [
                "climate change streamflow water quality downscaling",
                "climate",
                "change",
                "downscaling",
                "method"
            ],
            "contactPoint": {
                "fn": "Thomas Johnson",
                "hasEmail": "mailto:johnson.thomas@epa.gov"
            },
            "distribution": [
                {
                    "title": "ACF River.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390087/ACF%20River.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Minnesota River.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390087/Minnesota%20River.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Salt River.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390087/Salt%20River.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Susquehanna River.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390087/Susquehanna%20River.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Willamette River.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390087/Willamette%20River.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-01-04",
            "references": [
                "https://doi.org/10.1175/ei-d-15-0024.1"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A small, lightweight multipollutant sensor system for ground-mobile and aerial emission sampling from open area sources",
            "description": "Emission data from UAV flights. \n\nThis dataset is associated with the following publication:\nZhou, X., J. Aurell, B. Mitchell, D. Tabor, and B. Gullett. A small, lightweight multipollutant sensor system for ground-mobile and aerial emission sampling from open area sources.   JOURNAL OF AIR AND WASTE MANAGEMENT. Air & Waste Management Association, Pittsburgh, PA, USA, 154: 31-41, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1390075",
            "keyword": [
                "emissions",
                "unmanned aerial vehicle",
                "Sensors",
                "air pollution",
                "unmanned aerial vehicles",
                "aerostats"
            ],
            "contactPoint": {
                "fn": "Brian Gullett",
                "hasEmail": "mailto:gullett.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data Table for Science Hub Zhou paper Gullett.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390075/Data%20Table%20for%20Science%20Hub%20Zhou%20paper%20Gullett.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-08",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2017.01.029"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Aerial sampling of emissions from biomass pile burns in Oregon",
            "description": "Emissions from burning slash biomass piles in western Oregon. \n\nThis dataset is associated with the following publication:\nAurell, J., B. Gullett, D. Tabor, and N. Yonker. Emissions from  prescribed burning of timber slash piles in Oregon..   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 150: 395-406, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1390074",
            "keyword": [
                "emission factors",
                "timber slash",
                "pile cover",
                "moisture",
                "polyethylene"
            ],
            "contactPoint": {
                "fn": "Brian Gullett",
                "hasEmail": "mailto:gullett.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data Table Science Hub Oregon 07-25-2016 JA.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390074/Data%20Table%20Science%20Hub%20Oregon%2007-25-2016%20JA.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-07-25",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2016.11.034"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "LakeCat",
            "description": "The LakeCat Dataset provides summaries of watershed features for 378,088 lakes within the conterminous USA and provides several hundred watershed-level metrics that summarize both natural (e.g., soils, geology, climate, and land cover) and anthropogenic (e.g., urbanization,\nagriculture, and mines) features. \n\nThis dataset is associated with the following publication:\nHill, R., M. Weber, R. Debbout, S. Leibowitz, and T. Olsen. The Lake-Catchment (LakeCat) Dataset: Characterizing landscape features for lake basins within the conterminous USA.   Freshwater Science. The Society for Freshwater Science, Springfield, IL,  37: 208-221, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1500884",
            "keyword": [
                "lakes",
                "streams",
                "catchments",
                "watersheds",
                "watershed metrics",
                "National Hydrography Dataset",
                "National Hydrography Dataset Plus (NHDPlus)",
                "spatial prediction",
                "aquatic condition",
                "National Aquatic Resource Surveys"
            ],
            "contactPoint": {
                "fn": "Scott Leibowitz",
                "hasEmail": "mailto:leibowitz.scott@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/lakecat-dataset"
                }
            ],
            "modified": "2017-07-11",
            "references": [
                "https://doi.org/10.1086/697966"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://gaftp.epa.gov/EPADataCommons/ORD/NHDPlusLandscapeAttributes/LakeCat/Documentation/DataDictionary.html",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "in vitro and microsome experiment data",
            "description": "exposure_experiment.csv: \r\ntime: length of time that amphibian was exposed to that pesticide in hours.  \r\nparent: is the active ingredient that the amphibian was exposed to.  \r\nanalyte: either the main parent compound or the metabolite that was quantified.  \r\nmatrix: the sample that was analyzed either the amphibian or soil.  \r\nconc: is the concentration for that specific analyte in that matrix for that specific species in microg/g\r\nreplicate: is the individual amphibian or soil exposed to that pesticide.\r\n\r\nmicrosome_experiment3.csv:  \r\ntime: is the length of time that the microsomes were exposed before being quenched in minutes.  \r\nparent: is the active ingredient that the amphibian was exposed to.  \r\nanalyte: either the main parent compound or the metabolite that was quantified.  \r\nmatrix: the sample that was analyzed microsomes.  \r\nconc: is the concentration for that specific analyte in that matrix for that specific species.  in micromolar (uM)\r\nreplicate: is the individual microsome exposed to that pesticide. \r\nmicroMexp: is the concentration in micromolar (uM) that the microsomes were exposed to for that pesticide. \n\nThis dataset is associated with the following publication:\nGlinski, D., M. Henderson, R. Van Meter, and T. Purucker. Using in vitro derived enzymatic reaction rates of metabolism to inform pesticide body burdens in amphibians.   TOXICOLOGY LETTERS. Elsevier Science Ltd, New York, NY, USA, 288: 9-16, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407588",
            "keyword": [
                "microsomes",
                "Metabolism",
                "pesticides",
                "amphibians"
            ],
            "contactPoint": {
                "fn": "Steven Purucker",
                "hasEmail": "mailto:purucker.tom@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://zenodo.org/record/837834#.WYD9BfnythE",
                    "accessURL": "https://zenodo.org/record/837834#.WYD9BfnythE"
                }
            ],
            "modified": "2017-04-12",
            "references": [
                "https://doi.org/10.1016/j.toxlet.2018.02.016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Adverse Outcome Pathway Networks I: Development and Applications",
            "description": "In September, 2015, a water sample was collected downstream of a major metropolitan waste water treatment plant that discharges to the South Platte River, Colorado, USA. The grab sample, 1L, was collected just below the water surface, directly into a pre-cleaned, organic-free, amber glass bottle. The water sample was extracted by solid phase extraction using an Oasis-HLB glass catridge. Cartidges were conditioned sequentially using 5mL each of ethyl acetate, 50:50 methanol (MeOH):dichloromethane (DCM), MeOH, and water. The extract in DMSO was tested in the Attagene cis- and trans-FactorialTM assays (http://www.attagene.com/technology.php; Martin and others 2010; Romanov and others 2008). Data were analyzed using an established analysis pipeline for analyzing ToxCast\u2122 high throughput screening data (Filer and others 2017). \"Active hits\" in the Attagene assay are included in the data table. \n\nThis dataset is associated with the following publication:\nKnapen, D., M. Angrish, M. Fortin, I. Katsiadaki, M. Leonard, L. Mariotta-Casaluci, S. Munn, J. O'Brien, N. Pollesch, L.C. Smith, X. Zhang, and D. Villeneuve. Adverse outcome pathway networks I: Development and applications.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(6): 1723-1733, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1423303",
            "keyword": [
                "adverse outcome pathway",
                "ecotoxicology",
                "endocrine disruption",
                "screening and prioritization",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "WG1-paper-1-supplementary-2018-02-08.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1423303/WG1-paper-1-supplementary-2018-02-08.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Attagene SP 2014-15_ScienceHub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1423303/Attagene%20SP%202014-15_ScienceHub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-03-01",
            "references": [
                "https://doi.org/10.1002/etc.4125"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Adverse Outcome Pathway Networks II: Network Analytics",
            "description": "The data set provides a set of txt files and cytoscape files that were used to construct the example AOP networks included in the paper. Additionally, a supplementary table file provides all the network statistics discussed in the manuscript (e.g., node degree calculations, betweenness centrality, eccentricity, etc.). \n\nThis dataset is associated with the following publication:\nVilleneuve, D., M. Angrish, M. Fortin, I. Katsiadaki, M. Leonard, L. Margiotta-Casaluci, S. Munn, J. O'Brien, N. Pollesch, C. Smith, X. Zhang, and D. Knapen. Adverse outcome pathway networks II: Network analytics.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(6): 1734-1748, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1430043",
            "keyword": [
                "adverse outcome pathway",
                "ecotoxicology",
                "endocrine disruption",
                "screening and prioritization",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://setac.onlinelibrary.wiley.com/doi/abs/10.1002/etc.4124",
                    "accessURL": "https://setac.onlinelibrary.wiley.com/doi/abs/10.1002/etc.4124"
                },
                {
                    "title": "Networkfiles.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1430043/Networkfiles.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Part-II-supplementary-tables_for submissioin.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1430043/Part-II-supplementary-tables_for%20submissioin.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-03-28",
            "references": [
                "https://doi.org/10.1002/etc.4124"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Self-Cleaning Carbon Nanotube Membranes for Water Purification-confocal microscope pitures and slide preparation procedures",
            "description": "The pictures in the power point file were taken using a confocal microscope with green and red filters which represent viable and dead bacteria cells, respectively. Additionally, we provided the detailed procedures of bacteria propagation and viability staining in a MS word file. The data may provide background/supporting information for other researchers who are planning to perform for microscopic bacteria viability assays. \n\nThis dataset is associated with the following publication:\nAlvarez, N., R. Noga, S. Chae, G. Sorial, H. Ryu, and V. Shanov. Heatable carbon nanotube composite membranes for sustainable recovery from biofouling.   Biofouling. Taylor & Francis Group, London,  UK, 33(10): 847-854, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1378446",
            "keyword": [
                "carbon nanotubes",
                "drawable and spinnable CNT",
                "membranes",
                "ohmic heating",
                "biofouling",
                "water and wastewater treatment",
                "Escherichia coli."
            ],
            "contactPoint": {
                "fn": "Hodon Ryu",
                "hasEmail": "mailto:ryu.hodon@epa.gov"
            },
            "distribution": [
                {
                    "title": "Results (Sep 23, 2016) (revised).pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378446/Results%20%28Sep%2023%2C%202016%29%20%28revised%29.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Bacteria propagation and staining.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378446/Bacteria%20propagation%20and%20staining.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-09-05",
            "references": [
                "https://doi.org/10.1080/08927014.2017.1376322"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Taxonomic summary tables for illumina sequences from MEC study on influence of electrical conductivity by microbial activity in biofilm anode",
            "description": "This study assessed the conductivity of a Geobacter-enriched biofilm anode along with biofilm activity in a microbial electrochemical cell (MxC) equipped with two gold anodes (25 mM acetate medium), as different proton gradients were built throughout the biofilm. There was no pH gradient across the biofilm anode at 100 mM phosphate buffer (current density 2.38 A/m2) and biofilm conductivity (Kbio) was as high as 0.87 mS/cm. In comparison, an inner biofilm became acidic at 2.5 mM phosphate buffer in which approximately 80 \u03bcm of the inner biofilm anode was metabolically inactive. At this low phosphate buffer, Kbio significantly decreased by 0.27 mS/cm, together with declined current density of 0.64 A/m2. This work demonstrates that biofilm conductivity depends on metabolic activity of Geobacter in the conductive biofilm anode. The decreased Kbio at acidic environment implies the presence of multiple conduction-EET pathways in the biofilm anode. \n\nThis dataset is associated with the following publication:\nDhar, B., J. Sim, H. Ryu, H. Ren, J. Santodomingo, J. Chae, and H. Lee. Microbial Activity Influences Electrical Conductivity of Biofilm Anode.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 127: 230-238, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1379483",
            "keyword": [
                "Microbial electrochemical cell",
                "Electrical conductivity",
                "Biofilm anode",
                "Geobacter"
            ],
            "contactPoint": {
                "fn": "Hodon Ryu",
                "hasEmail": "mailto:ryu.hodon@epa.gov"
            },
            "distribution": [
                {
                    "title": "MEC-microbial activity_pH-MMXC_Illumina results_tables.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379483/MEC-microbial%20activity_pH-MMXC_Illumina%20results_tables.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "MEC-microbial activity_pH-MMXC_taxonomy summary.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379483/MEC-microbial%20activity_pH-MMXC_taxonomy%20summary.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-09-06",
            "references": [
                "https://doi.org/10.1016/j.watres.2017.10.028"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Integrated cell culture RT quantitative PCR and UV disinfection dataset",
            "description": "This dataset includes the standard curves for ICCRTqPCR to convert the assay quantities to the concentrations of infectious viruses and all the calculations on inactivation rate constants. Also, all the figures used in the manuscripts are presented. \n\nThis dataset is associated with the following publication:\nRyu, H., K. Schrantz, N. Brinkman, and L. Boczek. Applicability of integrated cell culture reverse transcriptase quantitative PCR (ICC-RTqPCR) for the simultaneous detection of the four human enteric enterovirus species in disinfection studies.   JOURNAL OF VIROLOGICAL METHODS. Elsevier Science Ltd, New York, NY, USA, 258: 35-40, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1422043",
            "keyword": [
                "multiplex integrated cell culture quantitative PCR",
                "enteroviruses",
                "UV disinfection"
            ],
            "contactPoint": {
                "fn": "Hodon Ryu",
                "hasEmail": "mailto:ryu.hodon@epa.gov"
            },
            "distribution": [
                {
                    "title": "ICCRTqPCR_Enterovirus_UV.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1422043/ICCRTqPCR_Enterovirus_UV.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-03-06",
            "references": [
                "https://doi.org/10.1016/j.jviromet.2018.05.008"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "HTMLS of Spatial Stream Network Modeling to Predict Total Phosphorus Concentration in the East Fork of the Little Miami River, Ohio",
            "description": "These files contain data for relating stream total phosphorus concentration, a nutrient, to land cover and land use variables in the East Fork of the Little Miami River watershed near Cincinnati, Ohio.  Water quality grab samples were collected from June 26, 2012 to September 11, 2012, and total phosphorus concentrations were measured on those samples.  The files in the jawr12543-sup-002-R_code_and outputs folder are htmls, which can be opened with any browser to view the data and work flow of the data analysis.  The files in the jawr12543-sup-003-SSN_file_objects contains the dataset as an R object, which can be opened in the open-source R software. \n\nThis dataset is associated with the following publication:\nScown, M., M. McManus, J. Carson, and C. Nietch. Improving predictive models of in-stream phosphorus based on nationally-available spatial data coverages in a Southwestern Ohio watershed.   JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION. American Water Resources Association, Middleburg, VA, USA, 53(4): 944-960, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1415037",
            "keyword": [
                "spatial data",
                "stream networks",
                "spatial statistical network model",
                "phosphorus",
                "spatial autocorrelation"
            ],
            "contactPoint": {
                "fn": "Michael McManus",
                "hasEmail": "mailto:mcmanus.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "jawr12543-sup-0002-R_code_and_outputs.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1415037/jawr12543-sup-0002-R_code_and_outputs.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "jawr12543-sup-0003-SSN_file_objects.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1415037/jawr12543-sup-0003-SSN_file_objects.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-01-26",
            "references": [
                "https://doi.org/10.1111/1752-1688.12543"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1415037/documents/DataDictionary_SpatialStreamNetworkModeling_EastForkLittleMiamiRiver.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supplementary Material for \"The Effects of Source Water Quality on Drinking Water Treatment Costs: A Review and Synthesis of Empirical Literature\"",
            "description": "Characteristics of 24 studies that model drinking water treatment costs to source water quality. \n\nThis dataset is associated with the following publication:\nPrice, J., and M. Heberling. The Effects of Source Water Quality on Drinking Water Treatment Costs: A Review and Synthesis of Empirical Literature - Ecological Economics.   ECOLOGICAL ECONOMICS. Elsevier Science Ltd, New York, NY, USA, 151: 195-209, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407619",
            "keyword": [
                "literature review",
                "source water protection",
                "drinking water",
                "treatment costs",
                "economics"
            ],
            "contactPoint": {
                "fn": "Matthew Heberling",
                "hasEmail": "mailto:heberling.matt@epa.gov"
            },
            "distribution": [
                {
                    "title": "TreatmentCosts&WQReview_SupplementaryMaterial.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407619/TreatmentCosts%26WQReview_SupplementaryMaterial.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-23",
            "references": [
                "https://doi.org/10.1016/j.ecolecon.2018.04.014"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for a PPAR-alpha dependence of developmental effects of PFNA in mouse.",
            "description": "Perfluorononanoic acid (PFNA) is one of the perfluoroalkyl acids found in the environment and in tissues of humans and wildlife. Prenatal exposure to PFNA negatively impacts survival and development of mice and activates the mouse and human peroxisome proliferator-activated receptor-alpha (PPAR\u03b1). In the current study, we used PPAR\u03b1 knockout (KO) and 129S1/SvlmJ wild-type (WT) mice to investigate the role of PPAR\u03b1 in mediating PFNA-induced in vivo effects. Pregnant KO and WT mice were dosed orally with water (vehicle control: 10 ml/kg), 0.83, 1.1, 1.5, or 2mg/kg PFNA on gestational days (GDs) 1\u221218 (day of sperm plug = GD 0). Maternal weight gain, implantation, litter size, and pup weight at birth were unaffected in either strain. PFNA exposure reduced the number of live pups at birth and survival of offspring to weaning in the 1.1 and 2 mg/kg groups in WT. Eye opening was delayed (mean delay 2.1 days) and pup weight at weaning was reduced inWT pups at 2mg/kg. These developmental endpoints were not affected in the KO. Relative liver weight was increased in a dose-dependent manner in dams and pups of theWT strain at all dose levels but only slightly increased in the highest dose group in the KO strain. In summary, PFNA altered liver weight of dams and pups, pup survival, body weight, and development in the WT, while only inducing a slight increase in relative liver weight of dams and pups at 2mg/kg in KO mice. These results suggest that PPAR\u03b1 is an essential mediator of PFNA-induced developmental toxicity in the mouse. \n\nThis dataset is associated with the following publication:\nAbbott, B., C. Wolf, J. Schmid, C. Lau, and R. Zehr. Developmental Effects of Perfluorononanoic Acid in the Mouse Are Dependent on Peroxisome Proliferator-Activated Receptor-alpha..   PPAR research. Hindawi Publishing Corporation, New York, NY, USA,  1-11, (2010).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1435034",
            "keyword": [
                "Developmental Toxicity",
                "PPAR-alpha",
                "PFNA",
                "PFAA",
                "perfluoroalkyl acids"
            ],
            "contactPoint": {
                "fn": "Barbara Abbott",
                "hasEmail": "mailto:abbott.barbara@epa.gov"
            },
            "distribution": [
                {
                    "title": "Wolf et al 2010 SciHub Data Set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435034/Wolf%20et%20al%202010%20SciHub%20Data%20Set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2010-03-17",
            "references": [
                "https://doi.org/10.1155/2010/282896"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Environmental Monitoring and Assessment Program (1990-1998), National Coastal Assessment (2000-2006), National Aquatic Resource Surveys (2000-2015)",
            "description": "These data are from EPA's national coastal monitoring programs and include data from the water column, sediments, and biota, 1990-2015. \n\nThis dataset is associated with the following publication:\nHale, S., H. Buffum, J. Kiddon, and M. Hughes. Subtidal Benthic Invertebrates Shifting Northward Along the U.S. Atlantic Coast.   Estuaries and Coasts. Estuarine Research Federation, Port Republic, MD, USA, 40(6): 1744-1756, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1500437",
            "keyword": [
                "benthic invertebrates",
                "species\u2019 range shifts",
                "U.S. Atlantic coast",
                "Carolinian Biogeographic Province",
                "Virginian Biogeographic Province"
            ],
            "contactPoint": {
                "fn": "Stephen Hale",
                "hasEmail": "mailto:hale.stephen@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://archive.epa.gov/emap/archive-emap/web/html/index-21.html",
                    "accessURL": "https://archive.epa.gov/emap/archive-emap/web/html/index-21.html"
                },
                {
                    "title": "https://archive.epa.gov/emap/archive-emap/web/html/index-124.html",
                    "accessURL": "https://archive.epa.gov/emap/archive-emap/web/html/index-124.html"
                },
                {
                    "title": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys"
                }
            ],
            "modified": "2015-12-31",
            "references": [
                "https://doi.org/10.1007/s12237-017-0236-z"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Traffic Density Parameters",
            "description": "The complete data sets and programs used for data analysis were combined into one zip file. \n\nThis dataset is associated with the following publication:\nLiu , S., J. Burke , F. Chen , and J. Xue. Evaluation of Traffic Density Parameters as an Indicator of Vehicle Emission-Related Near-Road Air Pollution: A Case Study with NEXUS Measurement Data on Black Carbon.   International Journal of Environmental Research and Public Health. Molecular Diversity Preservation International, Basel,  SWITZERLAND, 14(12): 1581, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434295",
            "keyword": [
                "NEXUS",
                "air pollutant",
                "near-road",
                "traffic density",
                "vehicle emission",
                "Black Carbon",
                "exposure"
            ],
            "contactPoint": {
                "fn": "Shi Liu",
                "hasEmail": "mailto:liu.shi@epa.gov"
            },
            "distribution": [
                {
                    "title": "Mj_nexus.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434295/Mj_nexus.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-09-29",
            "references": [
                "https://doi.org/10.3390/ijerph14121581"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "On-road Emissions and Chemical Transformation of Nitrogen Oxides",
            "description": "On-road chase and PEMS measurement data while following traffic.  Time-averaged to assess the emission rate of the followed vehicle, including the presence of a PEMS to measure direct tailpipe exhaust. \n\nThis dataset is associated with the following publication:\nSnow, R., J. Faircloth, R. Baldauf, B. Yand, M. Zhang, P. Deshmukh, and X. Zhang. On-road Emissions and Chemical Transformation of Nitrogen Oxides.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA,  22, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407590",
            "keyword": [
                "chase measurement",
                "PEMS",
                "traffic",
                "nitrogen oxides",
                "emissions",
                "on-road"
            ],
            "contactPoint": {
                "fn": "Richard Baldauf",
                "hasEmail": "mailto:baldauf.richard@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure2b_Right_Daytime East Dominated Wind Net NO2 over 5 ppb.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407590/Figure2b_Right_Daytime%20East%20Dominated%20Wind%20Net%20NO2%20over%205%20ppb.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-07",
            "references": [
                "https://doi.org/10.1021/acs.est.7b05648"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Using methods development efforts ongoing within NRMRL, NERL, and Regional labs, the concentrations of polyfluorinated chemicals",
            "description": "Concentrations of polyfluorinated chemicals in drinking water from homes. \n\nThis dataset is associated with the following publication:\nDasu, K., S. Nakayama, M. Yoshikane, M. Mills, J.M. Wright, and S. Ehrlich. An Ultra-Sensitive Method for the Analysis of Perfluorinated Alkyl Acids in Drinking Water using a Column Switching High-Performance Liquid Chromatography Tandem Mass Spectrometry.  M.C. Breadmore, J.G. Dorsey, P. Dugo, S. Fanali  JOURNAL OF CHROMATOGRAPHY A. Elsevier Science Ltd, New York, NY, USA, 1494: 46-54, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407671",
            "keyword": [
                "Column-switching HPLC",
                "drinking water",
                "Perfluorinated alkyl acids",
                "Solid phase extraction"
            ],
            "contactPoint": {
                "fn": "Marc Mills",
                "hasEmail": "mailto:mills.marc@epa.gov"
            },
            "distribution": [
                {
                    "title": "Mills Dasu et al Science hub data.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407671/Mills%20Dasu%20et%20al%20Science%20hub%20data.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "https://doi.org/10.1016/j.chroma.2017.03.006",
                    "accessURL": "https://doi.org/10.1016/j.chroma.2017.03.006"
                }
            ],
            "modified": "2017-06-26",
            "references": [
                "https://doi.org/10.1016/j.chroma.2017.03.006"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://doi.org/10.1016/j.chroma.2017.03.006",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Wanjugi et al 2016_Data Set",
            "description": "Decomposition data of bacterial and viral fecal indicators in common human pollution types. \n\nThis dataset is associated with the following publication:\nWanjugi, P., M. Sivaganesan, A. Korajkic, C. Kelty, B. McMinn, R. Ulrich, V. Harwood, and O. Shanks. Differential Decomposition of Bacterial and Viral Fecal Indicators in Common Human Pollution Types.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 105: 591-601, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407668",
            "keyword": [
                "human fecal pollution",
                "water quality",
                "qPCR",
                "Microbial Source Tracking",
                "coliphage"
            ],
            "contactPoint": {
                "fn": "Orin Shanks",
                "hasEmail": "mailto:shanks.orin@epa.gov"
            },
            "distribution": [
                {
                    "title": "Wanjugi etal 2016_Data Set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407668/Wanjugi%20etal%202016_Data%20Set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-10-05",
            "references": [
                "http://www.sciencedirect.com/science/article/pii/S0043135416307187"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Fort Riley Tensiometer Data",
            "description": "Tensiometers were installed a various depths and distances to monitor soil moisture tension. The installation was used to monitor subsurface water flow patterns from the storage gallery under the permeable pavement site. \n\nThis dataset is associated with the following publication:\nRazzaghmanesh, M., and M. Borst. Monitoring the performance of urban green infrastructure using a tensiometer approach.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 651: 2535-2545, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1500904",
            "keyword": [
                "Tensiometer",
                "Exfiltration",
                "sidewalls",
                "permeable pavement",
                "stormwater control"
            ],
            "contactPoint": {
                "fn": "Michael Borst",
                "hasEmail": "mailto:borst.mike@epa.gov"
            },
            "distribution": [
                {
                    "title": "Fort Riley Tensiometer Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500904/Fort%20Riley%20Tensiometer%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-05-30",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.10.120"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cylindrospermopsin 90-day oral route toxicology study",
            "description": "General toxicology, clinical chemistry, complete blood counts, histopathology, gene expression. \n\nThis dataset is associated with the following publication:\nChernoff, N., D. Hill, I. Chorus, D. Diggs, H. Huang, D. King, J. Lang, T. Le, J. Schmid, G. Travlos, E. Whitley, R. Wilson, and C. Wood. Cylindrospermopsin toxicity in mice following a 90-d oral exposure.   ENVIRONMENTAL TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA,  549-566, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1375219",
            "keyword": [
                "cylindrospermopsin",
                "algal toxin",
                "cyanobacterial toxin",
                "oral exposure",
                "90-day study",
                "liver toxicity",
                "kidney toxicity"
            ],
            "contactPoint": {
                "fn": "Neil Chernoff",
                "hasEmail": "mailto:chernoff.neil@epa.gov"
            },
            "distribution": [
                {
                    "title": "Combined data sets .docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375219/Combined%20data%20sets%20.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-01-30",
            "references": [
                "https://doi.org/10.1080/15287394.2018.1460787"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1375219/documents/Data%20dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "HESI_Biocrates_TMT_2017",
            "description": "Biocrates metabolomics data for cerebrospinal fluid, serum, plasma, and urine from rats dosed with trimethyl tin at 2, 6, 10, or 14 days after treatmetn. \n\nThis dataset is associated with the following publication:\nImam, S., Z. He, E. Cuevas, H. Rosas-Hernandez, S. Lantz, S. Sarkar, J. Raymick, B. Robinson, J. Hanig, D. Herr, D. MacMillan, A. Smith, S. Liachenko, S. Ferguson, J. O'Callaghan, D. Miller, C. Somps, I. Pardo, W. Slikker, J. Pierson, R. Roberts, B. Gong, W. Tong, M. Aschner, M.J. Kallman, D. Calligaro, and M. Paule. Changes in the metabolome and microRNA levels in biological fluids might represent biomarkers of neurotoxicity: A trimethyltin study.   Experimental Biology and Medicine. SAGE Publications, THOUSAND OAKS, CA, USA, 243(3): 228-236, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1376677",
            "keyword": [
                "Biocrates",
                "neurotoxicity",
                "biomarker",
                "metabolomics",
                "trimethyltin"
            ],
            "contactPoint": {
                "fn": "David Herr",
                "hasEmail": "mailto:herr.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "HESI_Biocrates_2017.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1376677/HESI_Biocrates_2017.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-08-22",
            "references": [
                "https://doi.org/10.1177/1535370217739859"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The Application of a Highly Purified Rat Leydig Cell Assay as a Complement to the H295R Steroidogenesis Assay to Evaluate Toxicant Induced Alterations in Testosterone Production",
            "description": "The greater dynamic range of testosterone production in a highly purified rat Leydig cell assay permitted the detection of chemical induced inhibition that was not detected by the high throughput screening format of the H295R steroidogenesis assay.  This dataset is associated with ORD-022468 entered in STICS. \n\nThis dataset is associated with the following publication:\nBotteri Principato, N., J. Suarez, S. Laws, and G. Klinefelter. The Use of Purified Rat Leydig Cells Complements the H295R Screen to Detect Chemical Induced Alterations in Testosterone Production.   BIOLOGY OF REPRODUCTION. Society for the Study of Reproduction,    98(2): 239-249, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1378085",
            "keyword": [
                "Endocrine Disruptors",
                "cell culture",
                "testosterone",
                "testis",
                "gonadal steroids",
                "male infertility",
                "steroidogenesis",
                "Leydig cell assay",
                "2nd Tier screen"
            ],
            "contactPoint": {
                "fn": "Gary Klinefelter",
                "hasEmail": "mailto:klinefelter.gary@epa.gov"
            },
            "distribution": [
                {
                    "title": "manuscript figures 6-2-17.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1378085/manuscript%20figures%206-2-17.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2017-06-16",
            "references": [
                "https://doi.org/10.1093/biolre/iox177"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data Table for Figures",
            "description": "This excel file contains 7 tabs, each tabs contains the data for one specific figure in the paper. Description of the data and column names is also provided in each tab. \n\nThis dataset is associated with the following publication:\nWang, J., D. Hallinger, A. Murr, A. Buckalew, S. Simmons, S. Laws, and T. Stoker. High-Throughput Screening and Quantitative Chemical Ranking for Sodium Iodide Symporter Inhibitors in ToxCast Phase 1 Chemical Library.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(9): 5417-5426, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1389586",
            "keyword": [
                "Sodium Iodide Symporter",
                "thyroid",
                "endocrine disruptor",
                "high-throughput in vitro screening assay"
            ],
            "contactPoint": {
                "fn": "Tammy Stoker",
                "hasEmail": "mailto:stoker.tammy@epa.gov"
            },
            "distribution": [
                {
                    "title": "NIS ph1 dataset for science-hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1389586/NIS%20ph1%20dataset%20for%20science-hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-25",
            "references": [
                "https://doi.org/10.1021/acs.est.7b06145"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Sediment Porewater Data Set",
            "description": "The data set contains a summary of all measurements that were collected at the cottage grove\nreservoir over the time period of the study. \n\nThis dataset is associated with the following publication:\nEckley, C., T. Luxton, J. Goetz, and J. McKernan. Water-level fluctuations influence sediment porewater chemistry and methylmercury production in a flood-control reservoir..  David Carpenter, and Eddy Zeng  ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 222: 32-41, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1502433",
            "keyword": [
                "mercury",
                "methylmercury",
                "reservoir",
                "porewater",
                "mercury methylation",
                "dissolved organic carbon"
            ],
            "contactPoint": {
                "fn": "Todd Luxton",
                "hasEmail": "mailto:luxton.todd@epa.gov"
            },
            "distribution": [
                {
                    "title": "CGR Data Summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502433/CGR%20Data%20Summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-06-20",
            "references": [
                "https://doi.org/10.1016/j.envpol.2017.01.010"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Predicting Potential Human Health Risk with the Tox21 10k Library",
            "description": "This study represents the first report applying IVIVE approaches and exposure comparisons using the entirety of the Tox21 federal collaboration chemical screening data, incorporating assay response efficacy and quality of concentration-response fits, and providing quantitative anchoring to first address the likelihood of human in vivo interactions with Tox21 compounds. This likelihood was assessed using a maximum blood concentration to in vitro response ratio approach (Cmax/AC50), analogous to decision-making methods for clinical drug-drug interactions. Fraction unbound in plasma (fup) and intrinsic hepatic clearance (CLint) parameters were estimated in silico and incorporated in a 3-compartment toxicokinetic (TK) model to first predict Cmax for in vivo corroboration using therapeutic scenarios. \n\nThis dataset is associated with the following publication:\nSipes, N., J. Wambaugh, R. Pearce, S. Auerbach, B. Wetmore, J. Hsieh, A. Shapiro, D. Sboboda, M. DeVito, and S. Ferguson. (ENVIRONMENTAL SCIENCE and TECHNOLOGY) An Intuitive Approach for Predicting Human Risk with the Tox21 10k Library.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, issue}: 10786-10796, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1395143",
            "keyword": [
                "in vitro to in vivo extrapolation (IVIVE)",
                "high throughput toxicokinetics",
                "httk",
                "IVIVE",
                "Tox21",
                "High throughput screening",
                "HTS",
                "ExpoCast",
                "exposure"
            ],
            "contactPoint": {
                "fn": "John Wambaugh",
                "hasEmail": "mailto:wambaugh.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "Supporting Information_EST_FINAL_18JUL2017.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395143/Supporting%20Information_EST_FINAL_18JUL2017.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "Table S1.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395143/Table%20S1.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table S2.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395143/Table%20S2.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table S3.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395143/Table%20S3.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://ntp.niehs.nih.gov/sandbox/ivive/",
                    "accessURL": "https://ntp.niehs.nih.gov/sandbox/ivive/"
                }
            ],
            "modified": "2017-07-19",
            "references": [
                "https://doi.org/10.1021/acs.est.7b00650",
                "https://ntp.niehs.nih.gov/sandbox/ivive/"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Triclosan Hershberger H295 data",
            "description": "Triclosan data from Hershberger experiment using castrated male rats.  Data includes accessory sex tissue mean weights and thyroid gland weight following exposure to triclosan for 10 days both with and without testosterone stimulation.  Also included are the thyroxine hormone means in these males.  In addition, mean data on the in vitro adrenocortical cells for steroid hormone production (testosterone and estradiol) with a dose response of triclosan. \n\nThis dataset is associated with the following publication:\nFarmer, W., G. Louis, A. Buckalew, D. Hallinger, and T. Stoker. Evaluation of Triclosan in the Hershberger and H295R Steroidogenesis Assays.   TOXICOLOGY LETTERS. Elsevier Science Ltd, New York, NY, USA,  194-199, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407648",
            "keyword": [
                "Hershberger",
                "endocrine",
                "steroids",
                "thryoid hormone",
                "androgen",
                "estrogen",
                "Triclosan"
            ],
            "contactPoint": {
                "fn": "Tammy Stoker",
                "hasEmail": "mailto:stoker.tammy@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHubDataforTriclosan Hershberger Paper Final 1.29.18.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407648/ScienceHubDataforTriclosan%20Hershberger%20Paper%20Final%201.29.18.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-25",
            "references": [
                "https://doi.org/10.1016/j.toxlet.2018.03.001"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset for manuscript \"Mixed \u201canti-androgenic\u201d chemicals at low individual doses produces reproductive tract malformations in the male rat\"",
            "description": "Dataset contains summary data (mean, standard error, sample size (n)) for all measured endpoints reported and depicted in the corresponding manuscript. \n\nThis dataset is associated with the following publication:\nConley, J., C. Lambright, N. Evans, M. Cardon, J. Furr, V. Wilson, and E. Gray. Mixed \u201cantiandrogenic\u201d chemicals at low individual doses produce reproductive tract malformations in the male rat.   TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA,  164(1): 166-178, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1408091",
            "keyword": [
                "anti-androgens",
                "chemical mixtures",
                "Birth Defects",
                "in utero effects on reproductive development",
                "pesticides",
                "Phthalates"
            ],
            "contactPoint": {
                "fn": "Justin Conley",
                "hasEmail": "mailto:conley.justin@epa.gov"
            },
            "distribution": [
                {
                    "title": "ConleyJustin_Dataset_A-73ng_20171108.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1408091/ConleyJustin_Dataset_A-73ng_20171108.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-11-09",
            "references": [
                "https://doi.org/10.1093/toxsci/kfy069"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1408091/documents/ConleyJustin_A-73ng_Dataset_Dictionary_20171108.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Building downwash large eddy simulations",
            "description": "This data set is associated with the results found in the journal article: Foroutan et al, 2018. Numerical analysis of pollutant dispersion around elongated buildings: an embedded large eddy simulation approach. Atmospheric Environment, https://doi.org/10.1016/j.atmosenv.2018.05.053. \nThe objective of the paper is to employ a scale-resolving turbulence model, namely the embedded LES (ELES), to study near-field pollutant dispersion around elongated/rotated buildings. It includes the evaluation of the ELES performance against wind tunnel measurements, as well as the analysis of the computational results for various source-building geometries while emphasizing the aspects important for dispersion modeling. \n\nThis dataset is associated with the following publication:\nForoutan, H., W. Tang, D. Heist, S. Perry, L. Brouwer, and E. Monbureau. Numerical analysis of pollutant dispersion around elongated buildings: An embedded large eddy simulation approach.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 187: 117-130, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434501",
            "keyword": [
                "Pollutant dispersion",
                "building downwash",
                "Large Eddy Simulation",
                "CFD"
            ],
            "contactPoint": {
                "fn": "Hosein Foroutan",
                "hasEmail": "mailto:foroutan.hosein@epa.gov"
            },
            "distribution": [
                {
                    "title": "ForoutanHosein_A-f7md_DataFiles_20180605.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434501/ForoutanHosein_A-f7md_DataFiles_20180605.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-06-05",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2018.05.053"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1434501/documents/ForoutanHosein_A-f7md_DataDictionary_20180605.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "FL estuaries RESTORE",
            "description": "light attenuation data within NW Florida estuaries during 2009-2013. \n\nThis dataset is associated with the following publication:\nConmy, R., B. Schaeffer, J. Schubauer-Berigan, J. Aukamp, A. Duffy, J. Lehrter, and R. Greene. Characterizing light attenuation within Northwest Florida Estuaries: Implications for RESTORE Act water quality monitoring.  Charles Sheppard, Francois Galgani, Pat Hutchings, and Victor Quintino  MARINE POLLUTION BULLETIN. Elsevier Science Ltd, New York, NY, USA, 114(2): 995-1006, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407617",
            "keyword": [
                "light attenutation",
                "Florida estuaries",
                "water quality",
                "RESTORE Act"
            ],
            "contactPoint": {
                "fn": "Robyn Conmy",
                "hasEmail": "mailto:conmy.robyn@epa.gov"
            },
            "distribution": [
                {
                    "title": "FL optics master sheet for conmy et al_2015.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407617/FL%20optics%20master%20sheet%20for%20conmy%20et%20al_2015.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-12-12",
            "references": [
                "http://www.sciencedirect.com/science/journal/0025326X/114/2"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Great Lakes Proxies Project",
            "description": "This dataset includes five ESRI ArcMap shapefiles to provide metadata for those shapefiles. Additional, within the attribute table of  each shapefile is a data field titled \"SHP_Source\" that provides a brief description of the public data sources used to create the shapefile. These data include aquatic non-native species presence in waters of the Laurentian Great Lakes, US and Canadian population for urban areas around the Great Lakes, locations of marinas and ports in the Great Lakes, and data on maritime commerce within the Great Lakes. \n\nThis dataset is associated with the following publication:\nO'Malia, E., L. Johnson, and J. Hoffman. Pathways and places associated with nonindigenous aquatic species introductions in the Laurentian Great Lakes.   HYDROBIOLOGIA. Springer, New York, NY, USA, 817(1): 23-40, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1395247",
            "keyword": [
                "Great Lakes",
                "non-indigenous aquatic species",
                "biomonitoring",
                "early detection"
            ],
            "contactPoint": {
                "fn": "Joel Hoffman",
                "hasEmail": "mailto:hoffman.joel@epa.gov"
            },
            "distribution": [
                {
                    "title": "HoffmanJoel_A-4qrn_Dataset_20170927.Zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395247/HoffmanJoel_A-4qrn_Dataset_20170927.Zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Shapefile Metadata.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395247/Shapefile%20Metadata.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Maritime Commerce Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395247/Maritime%20Commerce%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-02-01",
            "references": [
                "https://doi.org/10.1007/s10750-018-3551-x"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "2017_Prediction_of_H295R_steroidogenesis_Pathway_Perturbation",
            "description": "The objectives of this work were to: 1) develop an integrated analysis of chemical-mediated effects on steroidogenesis in the HT-H295R assay; and, 2) evaluate whether the HT-H295R assay predicts estrogen and androgen production specifically via comparison with the OECD-validated H295R assay. \n\nThis dataset is associated with the following publication:\nHaggard, D., A. Karmaus, M. Martin, R. Judson, W. Setzer, and K. Paul-Friedman. (Toxicological Sciences) High-throughput H295R steroidogenesis assay: utility as an alternative and a statistical approach to characterize effects on steroidogenesis.   TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA,  162(2): 509-534, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407003",
            "keyword": [
                "EDSP21",
                "ToxCast",
                "steroidogenesi",
                "ACToR"
            ],
            "contactPoint": {
                "fn": "Richard Judson",
                "hasEmail": "mailto:judson.richard@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/Haggard/2017_Prediction_of_H295R_steroidogenesis_Pathway_Perturbation/",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/Haggard/2017_Prediction_of_H295R_steroidogenesis_Pathway_Perturbation/"
                },
                {
                    "title": "https://github.com/USEPA/CompTox-ToxCast-EDSPsteroidogenesis",
                    "accessURL": "https://github.com/USEPA/CompTox-ToxCast-EDSPsteroidogenesis"
                }
            ],
            "modified": "2017-09-08",
            "references": [
                "https://doi.org/10.1093/toxsci/kfx274"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Read_Across_Prediction_of_Estrogenicity_for_Hindered_Phenols_2017_Data",
            "description": "Read-across is an important data gap filling technique used within category and analog approaches for regulatory hazard identification and risk assessment. Although much technical guidance is available that describes how to develop category/analog approaches, practical principles to evaluate and substantiate analog validity (suitability) are still lacking. This case study uses hindered phenols as an example chemical class to determine: (1) the capability of three structure fingerprint/descriptor methods (PubChem, ToxPrints and MoSS MCSS) to identify analogs for read-across to predict Estrogen Receptor (ER) binding activity and, (2) the utility of data confidence measures, physicochemical properties, and chemical R-group properties as filters to improve ER binding predictions. The training dataset comprised 462 hindered phenols and 257 non- hindered phenols. For each chemical of interest (target), source analogs were identified from two datasets (hindered and non-hindered phenols) that had been characterized by a fingerprint/descriptor method and by two cut-offs: (1) minimum similarity distance (range: 0.1 - 0.9) and, (2) N closest analogs (range: 1 - 10). Analogs were then filtered using: (1) physicochemical properties of the phenol (termed global filtering) and, (2) physicochemical properties of the R-groups neighboring the active hydroxyl group (termed local filtering). A read-across prediction was made for each target chemical on the basis of a majority vote of the N closest analogs. The results demonstrate that: (1) concordance in ER activity increases with structural similarity, regardless of the structure fingerprint/descriptor method, (2) increased data confidence significantly improves read-across predictions, and (3) filtering analogs using global and local properties can help identify more suitable analogs. This case study illustrates that the quality of the underlying experimental data and use of endpoint relevant chemical descriptors to evaluate source analogs are critical to achieving robust read-across predictions. \n\nThis dataset is associated with the following publication:\nPradeep, P., K. Mansouri, G. Patlewicz, and R. Judson. (Computational Toxicology) A systematic evaluation of analogs and automated read-across prediction of estrogenicity: A case study using hindered phenols.   Computational Toxicology. Elsevier B.V., Amsterdam,  NETHERLANDS, 4: 22-30, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407005",
            "keyword": [
                "Read-across",
                "Estrogen Receptor binding",
                "analog identification",
                "ToxCast",
                "ACToR"
            ],
            "contactPoint": {
                "fn": "Richard Judson",
                "hasEmail": "mailto:judson.richard@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/Judson/Pradeep%20Hindered%20Phenols%202017/",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/Judson/Pradeep%20Hindered%20Phenols%202017/"
                }
            ],
            "modified": "2017-09-18",
            "references": [
                "https://doi.org/10.1016/j.comtox.2017.09.001"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Validation of an automated counting procedure for phthalate-induced testicular multinucleated germ cells",
            "description": "the dataset contains NHEERL collected data on fetal male rat gestational day 18 testicular testosterone production and related data. \n\nThis dataset is associated with the following publication:\nspade, d., C. Yue Bai , C. Lambright, J. Conley, K. Boekelheide , and E. Gray. Validation of an automated counting procedure for phthalate-induced testicular multinucleated germ cells.   TOXICOLOGY LETTERS. Elsevier Science Ltd, New York, NY, USA, 290: 55-61, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1408099",
            "keyword": [
                "Phthalates",
                "automated high throughput methods",
                "testis pathology",
                "androgen signaling AOP network"
            ],
            "contactPoint": {
                "fn": "Leon Gray",
                "hasEmail": "mailto:gray.earl@epa.gov"
            },
            "distribution": [
                {
                    "title": "119 105 MNG BLOCKS T PROD SAS ANALYSIS used in spade manuscript and added to Science Hub 12 11 2017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1408099/119%20105%20MNG%20BLOCKS%20T%20PROD%20SAS%20ANALYSIS%20used%20in%20spade%20manuscript%20and%20added%20to%20Science%20Hub%2012%2011%202017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-02-06",
            "references": [
                "https://doi.org/10.1016/j.toxlet.2018.03.018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Chromatographic_Retention_Time_Prediction_Models_TALANTA_Data",
            "description": "This paper compares the relative predictive ability and applicability to NTA workflows of three RT prediction models: (1) a logP (octanol-water partition coefficient)-based model using EPI SuiteTM logP predictions; (2) a commercially available ACD/ChromGenius model; and, (3) a newly developed Quantitative Structure Retention Relationship model called OPERA-RT. \n\nThis dataset is associated with the following publication:\nMcEachran, A., K. Mansouri, S. Newton, B. Beverly, J. Sobus, and A. Williams. (TALANTA) A comparison of three liquid chromatography (LC) retention time prediction models.   TALANTA. Elsevier Science Ltd, New York, NY, USA, 182: 371-379, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407009",
            "keyword": [
                "DSSTox",
                "non-targeted analysis (NTA)",
                "high-performance liquid chromatography (HPLC)",
                "retention time(RT)",
                "Quantitative Structure-Retention Relationship (QSRR)",
                "Chemistry Dashboard",
                "dashboards"
            ],
            "contactPoint": {
                "fn": "Antony Williams",
                "hasEmail": "mailto:williams.antony@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/McEachran_A/RT_Prediction_2018/",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/McEachran_A/RT_Prediction_2018/"
                }
            ],
            "modified": "2017-10-03",
            "references": [
                "https://doi.org/10.1016/j.talanta.2018.01.022"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Fitzpatrick_Jeremy_Skin_Sensitization_Data",
            "description": "Allergic contact dermatitis (ACD) is estimated to constitute about 10-15% of all occupational diseases. Predictive testing to characterise substances for their skin sensitisation potential has historically been based on animal models such as the Local Lymph Node Assay (LLNA) and the Guinea Pig Maximisation Test (GPMT). In recent years, EU regulations, have provided a strong incentive to develop non-animal alternatives.  Significant progress has been made in developing and evaluating non-animal test methods. There have been efforts to develop and evaluate the utility of in silico models for skin sensitisation including local and global (Q)SARs as well as expert systems. In this study, we selected three different types of expert systems: VEGA (statistical), Derek Nexus (knowledge based), TIMES-SS (hybrid) and evaluated their performance using 2 large datasets of substances that had been assessed for their skin sensitisation potential in animal models. We considered a model to be successful at predicting skin sensitisation potential if it had at least the same balanced accuracy as the LLNA and the GPMT had in predicting the outcomes of one another, which ranged from 79% to 86% depending on the dataset.  We found that none of the expert systems evaluated was able to achieve such a high balanced accuracy in their global predictions, with balanced accuracies ranging from 56% to 65%.  However, for substances within the domain of TIMES-SS, balanced accuracies were found to be 79% and 82%, for the two datasets, in line with the animal data. The expert systems evaluated could be extended in light of the additional data collected as part of this study. The incorrect predictions offer new insights for how the existing alerts within these expert systems could be refined. These datasets also offer exciting opportunities for the development of new models. \n\nThis dataset is associated with the following publication:\nFitzpatrick, J., D. Roberts, and G. Patlewicz. (SAR and QSAR in ENVIRONMENTAL RESEARCH) An evaluation of selected (Q)SARs/expert systems for predicting skin sensitisation potential.   SAR AND QSAR IN ENVIRONMENTAL RESEARCH. Taylor & Francis, Inc., Philadelphia, PA, USA, 29(6): 439-468, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1427471",
            "keyword": [
                "DSSTox"
            ],
            "contactPoint": {
                "fn": "Ann Richard",
                "hasEmail": "mailto:richard.ann@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/PatlewiczGrace/Fitzpatrick_Evaluation_Of_QSARs_for_Predicting_Skin_Sensitisation_Potential/",
                    "accessURL": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/PatlewiczGrace/Fitzpatrick_Evaluation_Of_QSARs_for_Predicting_Skin_Sensitisation_Potential/"
                }
            ],
            "modified": "2018-05-02",
            "references": [
                "https://doi.org/10.1080/1062936x.2018.1455223"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
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            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
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            "description": "These data are bacterial 16S rRNA sequences and a taxonomic summary table for biofilm samples from the bio-reactors. The data may provide background/supporting information for other researchers who have a similar experimental plan with a microbial electrochemical cell reactor. \n\nThis dataset is associated with the following publication:\nSantodomingo, J., H. Lee, B. Dhar, J. An, B. Rittmann, H. Ren, and J. Chae. The Roles of Biofilm Conductivity and Donor Substrate Kinetics in a Mixed-Culture Biofilm Anod.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(23): 12799-12807, (2016).",
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            ],
            "identifier": "https://doi.org/10.23719/1500924",
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                "biofilm conductivity",
                "Donor Substrate Kinetics",
                "Biofilm anode",
                "Illumina sequencing"
            ],
            "contactPoint": {
                "fn": "Hodon Ryu",
                "hasEmail": "mailto:ryu.hodon@epa.gov"
            },
            "distribution": [
                {
                    "title": "biofilm conductivity kinetics_fasta.docx",
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                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500924/biofilm%20conductivity%20kinetics_muthur%20analysis.xlsx",
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                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
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            "holdren": "Yes",
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            "sourcetitle": "ScienceHub",
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        {
            "title": "Clades of Candidatus Accumulibacter phosphatis enriched under cyclic anaerobic and microaerobic conditions",
            "description": "Rates of reactor performance, and relative abundance of the different molecular groups found. \n\nThis dataset is associated with the following publication:\nCamejo, P., B. Owen, J. Martirano, J. Ma, V. Kapoor, J. Santodomingo, K. McMahon, and D. Noguera. Clades of Candidatus Accumulibacter phosphatis enriched under cyclic anaerobic and microaerobic conditions simultaneously use different electron acceptors.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 102: 125-137, (2016).",
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                "low dissolve oxygen",
                "water and wastewater treatment"
            ],
            "contactPoint": {
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            },
            "distribution": [
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                {
                    "title": "OTU_abundance_PS-SBR.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502459/OTU_abundance_PS-SBR.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Camejo-et.al-2016-Fig. 5-RawData Accumulibacter.xlsx",
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                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
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            "holdren": "Yes",
            "ORG": "ORD",
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            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Analysis of mitochondrail DNA sequences",
            "description": "Data for all the tables and figures on the frequency of haplotypes found in a tropical watershed contaminated with human fecal pollution. \n\nThis dataset is associated with the following publication:\nKapoor, V., M. Elk, C. Toledo-Hernandez, and J. Santodomingo. Analysis of human mitochondrial DNA sequences from fecally polluted environmental waters as a tool to study population diversity.   AIMS Environmental Science. AIMS Press, Springfield, MO, USA, 4(3): 443-455, (2017).",
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            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1502462",
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                "Microbial Source Tracking",
                "Mitochondria"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [
                {
                    "title": "20samples_0.05_Haplotypes.xlsx",
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            "modified": "2018-06-18",
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                "https://doi.org/10.3934/environsci.2017.3.443"
            ],
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                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
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            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Copper Silver Ionization at a hospital dataset",
            "description": "Temperature, pH, chlorine, copper and silver levels at a hospital employing copper-silver ionization to control Legionella bacteria. \n\nThis dataset is associated with the following publication:\nTriantafyllidou, S., D. Lytle, C. Muhlen, and J. Swertfeger. Copper-silver ionization at a US hospital: interaction of treated drinking water with plumbing materials, aesthetics and other considerations.   WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 102: 1-10, (2016).",
            "accessLevel": "public",
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                "020:00"
            ],
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                "020:096"
            ],
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                "copper silver ionization",
                "cold water",
                "hot water",
                "reduced silver",
                "copper pipe",
                "porcelain staining"
            ],
            "contactPoint": {
                "fn": "Simoni Triantafyllidou",
                "hasEmail": "mailto:triantafyllidou.simoni@epa.gov"
            },
            "distribution": [
                {
                    "title": "SciHub CSI Upload.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502466/SciHub%20CSI%20Upload.xlsx",
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                }
            ],
            "modified": "2018-07-03",
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                "http://www.sciencedirect.com/science/article/pii/S0043135416304468"
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                "name": "U.S. EPA Office of Research and Development (ORD)",
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                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Transport of carbon nanotube-magnetite nanohybrids in water-saturated porous media",
            "description": "Our data can be used by modeler to develop mathematical models to simulate and predict the fate and transport of the next-generation multifunctional carbon-based metal oxide nanohybrids in the subsurface environments. Furthermore, the data can also be employed to assess the potential environmental impacts and risks associated with the release and transport of carbon-based metal oxide nanohybrids in the subsurface under environmentally relevant physicochemical conditions. \n\nThis dataset is associated with the following publication:\nWang, D., C. Park, A. Masud, N. Aich, and C. Su. Carboxymethylcellulose Mediates the Transport of Carbon Nanotube-Magnetite Nanohybrid Aggregates in Water-Saturated Porous Media.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51: 12405-12415, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1414830",
            "keyword": [
                "Carbon\u2014metal oxide nanohybrids",
                "fate and transport",
                "In situ nanoremediation"
            ],
            "contactPoint": {
                "fn": "Chunming Su",
                "hasEmail": "mailto:su.chunming@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data_Wang Su ES&T Paper_2017.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1414830/Data_Wang%20Su%20ES%26T%20Paper_2017.pdf",
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                }
            ],
            "modified": "2017-12-26",
            "references": [
                "https://doi.org/10.1021/acs.est.7b04037"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Utilization of water utility lime sludge for flue gas desulfurization in coal-fired power plants: Part I. Supply-demand evaluation and life cycle assessment",
            "description": "The dataset contains all Tables and Figures in Excel spreadsheets. \n\nThis dataset is associated with the following publication:\nSalih, H., C. Patterson, J. Li, J. Mock, and S. Dastgheib. Utilization of water utility lime sludge for flue gas desulfurization in coal-fired power plants: Part I. Supply-demand evaluation and life cycle assessment.   ENERGY AND FUELS. American Chemical Society, Washington, DC, USA, 32(6): 6627-6633, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1435433",
            "keyword": [
                "Flue Gas Desulfurization",
                "limestone",
                "lime sludge",
                "life cycle assessment",
                "environmental impact assessment",
                "mercury re-emission"
            ],
            "contactPoint": {
                "fn": "Craig Patterson",
                "hasEmail": "mailto:patterson.craig@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data of Tables and Figures - Part 1 .xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435433/Data%20of%20Tables%20and%20Figures%20-%20Part%201%20.xlsx",
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            "modified": "2018-05-02",
            "references": [
                "https://doi.org/10.1021/acs.energyfuels.8b00823"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Reuse of water utility lime sludge for flue gas desulfurization in coal-fired power plants: Part II. Lime sludge characterization and mercury reemission",
            "description": "The dataset contains all Tables and Figures in Excel spreadsheets. \n\nThis dataset is associated with the following publication:\nDastgheib, S., H. Salih, J. Li, and C. Patterson. Utilization of Water Utility Lime Sludge for Flue Gas Desulfurization in Coal-Fired Power Plants: Part II. Lime Sludge Characterization and Mercury Re-emission.   ENERGY AND FUELS. American Chemical Society, Washington, DC, USA, 32(6): 6634-6640, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1435434",
            "keyword": [
                "Flue Gas Desulfurization",
                "limestone",
                "lime sludge",
                "life cycle assessment",
                "environmental impact assessment",
                "mercury re-emission"
            ],
            "contactPoint": {
                "fn": "Craig Patterson",
                "hasEmail": "mailto:patterson.craig@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data of Tables and Figures - Part 2.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435434/Data%20of%20Tables%20and%20Figures%20-%20Part%202.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
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            ],
            "modified": "2018-05-02",
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                "https://doi.org/10.1021/acs.energyfuels.8b00824"
            ],
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                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
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            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Three-dimensional Free Chlorine and Monochloramine Biofilm Penetration Correlating Penetration with Biofilm Activity and Viability",
            "description": "Data for manuscript figures. \n\nThis dataset is associated with the following publication:\nLee, W.H., J. Pressman, and D. Wahman. Three-dimensional Free Chlorine and Monochloramine Biofilm Penetration: Correlating Penetration with Biofilm Activity and Viability.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(4): 1889-1898, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1402417",
            "keyword": [
                "microelectrode"
            ],
            "contactPoint": {
                "fn": "David Wahman",
                "hasEmail": "mailto:wahman.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "Three-dimensional Free Chlorine and Monochloramine Biofilm Penetration Correlating Penetration with Biofilm Activity and Viability.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1402417/Three-dimensional%20Free%20Chlorine%20and%20Monochloramine%20Biofilm%20Penetration%20Correlating%20Penetration%20with%20Biofilm%20Activity%20and%20Viability.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-10-07",
            "references": [
                "https://doi.org/10.1021/acs.est.7b05215"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Adult FHM liver gene expression - treated with EE2",
            "description": "Male adult FHM liver treated with EE2 - gene expresssion - Agilent-036574 FHM_8x60K_V2 array design. \n\nThis dataset is associated with the following publication:\nFeswick, A., M. Isaacs, A. Biales, R. Flick, D. Bencic, R. Wang, C. Vulpe, M. Brown-Augustine, A. Loguinov, F. Falciani, P. Antczak, J. Herbert, L. Brown, N. Denslow, K. Kroll, C. Lavelle, V. Dang, L. Escalon, N. Garcia-Reyero, C. Martyniuk, and K. Munkittrick. How consistent are we? Interlaboratory comparison study in fathead minnows using the model estrogen 17\u03b1\u2010ethinylestradiol to develop recommendations for environmental transcriptomics.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 36(10): 2614-2623, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407570",
            "keyword": [
                "microarray",
                "fathead minnow",
                "gene expression"
            ],
            "contactPoint": {
                "fn": "Adam Biales",
                "hasEmail": "mailto:biales.adam@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.ncbi.nlm.nih.gov/gds/?term=GSE70807%5BAccession%5D",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/gds/?term=GSE70807%5BAccession%5D"
                }
            ],
            "modified": "2015-07-07",
            "references": [
                "https://doi.org/10.1002/etc.3799"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Anaerobic biodegradation",
            "description": "Data in these tables appear in the manuscript and were used to produce the published figures. \n\nThis dataset is associated with the following publication:\nWu, S., M. Yassine, M. Suidan, and A. Venosa. Anaerobic Biodegradation of soybean biodiesel and diesel blends under sulfate-reducing conditions.  Jacob de Boer, Shane Snyder  CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 161: 382-389, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407618",
            "keyword": [
                "anaerobic biodegradation",
                "biodiesel",
                "diesel"
            ],
            "contactPoint": {
                "fn": "David Kozlowski",
                "hasEmail": "mailto:kozlowski.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "Wu et al 2016 soybean dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407618/Wu%20et%20al%202016%20soybean%20dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-06-04",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2016.06.078"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "ozone hourly data at four monitoring sites",
            "description": "contains hourly ozone and meteorological data. \n\nThis dataset is associated with the following publication:\nSchliep, E., A. Gelfand, and D. Holland. Alternating Gaussian process modulated renewal processes for modeling threshold exceedances and durations.   Stochastic Environmental Research and Risk Assessment. Springer-Verlag, BERLIN-HEIDELBERG,  GERMANY, 32(2): 401-417, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1390106",
            "keyword": [
                "Ozone",
                "ozone exceedances",
                "frequency and duration of exceedances",
                "NAAQS"
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            "contactPoint": {
                "fn": "David Holland",
                "hasEmail": "mailto:holland.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "EPAdataCSV.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390106/EPAdataCSV.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2015-11-04",
            "references": [
                "https://doi.org/10.1007/s00477-017-1417-9"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Sediment accretion and accumulation of P, N and organic C in depressional wetlands of three ecoregions of the United States",
            "description": "Data used in the paper, Nitrogen Removal in Select Palustrine Isolated Wetlands of Three Ecoregions of the United States: Mid-Atlantic Coastal Plains, Erie Drift Plain, and Southern Coastal Plain: Marine and Freshwater Research http://dx.doi.org/10.1071/MF16372. \n\nThis dataset is associated with the following publication:\nLane, C., and B. Autrey. Sediment accretion and accumulation of P, N and organic C in depressional wetlands of three ecoregions of the United States.   Marine & Freshwater Research. CSIRO Publishing, Collingwood Victoria,  AUSTRALIA, 68(12): 2253-2265, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1389608",
            "keyword": [
                "assimilation",
                "cesium/caesium"
            ],
            "contactPoint": {
                "fn": "Charles Lane",
                "hasEmail": "mailto:lane.charles@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cesium_ResearchEffort_Data_A-x96p_08302017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1389608/Cesium_ResearchEffort_Data_A-x96p_08302017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-30",
            "references": [
                "https://doi.org/10.1071/mf16372"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "In Vivo PK Library for IVIVE Evaluation",
            "description": "We report on new, in vivo TK experiments in rats for 26 chemicals more commonly associated with non-therapeutic and/or unintentional exposure. These chemicals, and an additional 19 chemicals from previously published in vivo rat studies, were systematically analyzed to estimate relevant TK parameters (e.g., volume of distribution, elimination rate). Our analysis created a library of TK parameters for 38 chemicals for which rat-specific in vitro HTTK data were also available. \n\nThis dataset is associated with the following publication:\nWambaugh, J., M. Hughes, C. Ring, D. MacMillan, J. Ford, T. Fennell, S. Black, R. Snyder, N. Sipes, B. Wetmore, J. Westerhout, W. Setzer, R. Pearce, J. Simmons, and R. Thomas. Evaluating In Vitro-In Vivo Extrapolation of Toxicokinetics.   TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA,  163(1): 152-169, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1390274",
            "keyword": [
                "toxicokinetics",
                "in vitro to in vivo extrapolation (IVIVE)",
                "Analytical chemistry",
                "ExpoCast",
                "exposure"
            ],
            "contactPoint": {
                "fn": "John Wambaugh",
                "hasEmail": "mailto:wambaugh.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "SupplementalTables1-8.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390274/SupplementalTables1-8.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "TableS9-InVivoData-2017-08-10.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390274/TableS9-InVivoData-2017-08-10.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "TableS10-PropertiesandEstimates-2017-08-30.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390274/TableS10-PropertiesandEstimates-2017-08-30.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "TableS11-TKSummaryStats-2017-08-30.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390274/TableS11-TKSummaryStats-2017-08-30.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "FiguresS1-1compartment-Fittedgeometricmean-2017-08-29.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390274/FiguresS1-1compartment-Fittedgeometricmean-2017-08-29.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "FiguresS2-2compartment-Fittedgeometricmean-2017-08-29.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390274/FiguresS2-2compartment-Fittedgeometricmean-2017-08-29.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2017-09-08",
            "references": [
                "https://doi.org/10.1093/toxsci/kfy020"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "High-throughput in-silico prediction of ionization equilibria for pharmacokinetic modeling",
            "description": "Estimates of ionization equilibrium constants (i.e., pKa) were analyzed for 8,132 pharmaceuticals and 24,281 other compounds to which humans might be exposed in the environment. Results revealed broad differences in the ionization of pharmaceutical chemicals and chemicals with either near-field (in the home) or far-field sources. Probability distributions corresponding to ionizable atom types (IATs) were then used to analyze the sensitivity of predicted Vdss on predicted pKa using Monte Carlo methods. 8 of the 22 compounds were predicted to be ionizable. For 5 of the 8 the predictions based upon ionization are significantly different from what would be predicted for a neutral compound. For all but one (foramsulfuron), the probability distribution of predicted Vdss generated by IAT sensitivity analysis spans both the neutral prediction and the prediction using ionization. \n\nThis dataset is associated with the following publication:\nStrope, C., K. Mansouri, H. Clewell, J. Rabinowitz, C. Stevens, and J. Wambaugh. High-Throughput in-silico prediction of ionization equilibria for pharmacokinetic modeling.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 615: 150-160, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1391808",
            "keyword": [
                "ionization",
                "pKa",
                "physiologically-based pharmacokinetic model",
                "PBPK model",
                "ExpoCast",
                "exposure"
            ],
            "contactPoint": {
                "fn": "John Wambaugh",
                "hasEmail": "mailto:wambaugh.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "32k_fingerprints.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1391808/32k_fingerprints.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "32k_pKa_prediction-20150414.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1391808/32k_pKa_prediction-20150414.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "PBPKxIon-20170918T145752Z-001-small.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1391808/PBPKxIon-20170918T145752Z-001-small.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-09-18",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2017.09.033"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Raw Measurements and Predicted Concentrations for Water Samples from Cape Fear Watershed (May - July 2017)",
            "description": "Measured and estimated concentrations of HFPO-DA and related perfluoroether compounds in the Cape Fear River as measured at multiple water treatment facilities in the watershed by QqQ LC-MS quantification. \n\nThis dataset is associated with the following publication:\nMcCord, J., S. Newton, and M. Strynar. Validation of quantitative measurements and semi-quantitative estimates of emerging perfluoroethercarboxylic acids (PFECAs) and hexfluoroprolyene oxide acids (HFPOAs).   JOURNAL OF CHROMATOGRAPHY A. Elsevier Science Ltd, New York, NY, USA, 1551: 52-58, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1408902",
            "keyword": [
                "GenX",
                "HFPO-DA",
                "Cape Fear River",
                "perfluorinated ether",
                "LC-MS"
            ],
            "contactPoint": {
                "fn": "James McCord",
                "hasEmail": "mailto:mccord.james@epa.gov"
            },
            "distribution": [
                {
                    "title": "Raw Measurements and Predicted Concentrations for LC-MSMS of PFECAs.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1408902/Raw%20Measurements%20and%20Predicted%20Concentrations%20for%20LC-MSMS%20of%20PFECAs.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "https://deq.nc.gov/news/hot-topics/genx-investigation/genx-sampling-sites",
                    "accessURL": "https://deq.nc.gov/news/hot-topics/genx-investigation/genx-sampling-sites"
                }
            ],
            "modified": "2017-11-16",
            "references": [
                "https://doi.org/10.1016/j.chroma.2018.03.047"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1408902/documents/Data%20Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Microcystin Congener octanol-water phase concentration measurements for pH dependent partitioning",
            "description": "Measured concentrations in octanol-water phase partitioning of microcystin congeners. \n\nThis dataset is associated with the following publication:\nMcCord, J., J. Lang, D. Hill, M. Strynar, and N. Chernoff. pH dependent octanol\u2013water partitioning coefficients of microcystin congeners.   JOURNAL OF WATER AND HEALTH. IWA Publishing, London,  UK, 16(3): 340-345, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407664",
            "keyword": [
                "microcystin",
                "cyanobacterial toxin",
                "octanol-water partition coefficient"
            ],
            "contactPoint": {
                "fn": "James McCord",
                "hasEmail": "mailto:mccord.james@epa.gov"
            },
            "distribution": [
                {
                    "title": "Log Kow Raws.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407664/Log%20Kow%20Raws.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-05-04",
            "references": [
                "https://doi.org/10.2166/wh.2018.257"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Characterization of Aerosol Nitro Aromatic Compounds Validation of an Experimental Method",
            "description": "The analytical capabilities associated with the use of silylation reactions have been extended to a new class of organic molecules, nitroaromatic compounds (NACs). These compounds are a possible contributor to urban particulate matter of secondary origin which would make them important analytes due to their (1) detrimental health effects, (2) potential to affect aerosol optical properties, (3) and usefulness for identifying PM2.5 from biomass burning. The technique is based on derivatization of the parent NACs using N,O-bis-(trimethylsilyl)-trifluoro acetamide, one of the most prevalent derivatization reagent for analyzing hydroxylated molecules, followed by GC-MS using electron ionization (EI) and methane chemical ionization (CI). This method is evaluated for 32 NACs including nitrophenols, methyl-/methoxy-nitrophenols, nitrobenzoic acids, and nitrobenzyl alcohols. EI spectra were characterized by a high abundance of ions corresponding to [M+.], or [M+ - 15]. CI spectra exhibited high abundance for [M+ + 1], [M+ - 15], and [M+ + 29] ions. Both EI and CI spectra exhibit ions specific to nitro group(s) for [M+. - 31], [M+. - 45], and [M+. - 60]. The strong abundance observed for [M+.] (EI), [M+ - 15] (EI/CI), or [M+ + 1] (CI) ions is consistent with the high charge stabilizing ability associated with aromatic compounds. The combination of EI and CI ionization offers strong capabilities for detection and identification of NACs. Spectra associated with NACs, containing hydrogen, carbon, oxygen, and nitrogen atoms only, as silylated derivatives show fragment/adduct ions at either (a) odd or (b) even masses that indicate either (a) odd or (b) even number of nitro groups, respectively. Mass spectra associated with silylated NACs exhibited three distinct regions where characteristic fragmentation with a specific pattern associated with: (1) -OH, and/or -COOH groups, (2) -NO2 group(s), and (3) benzene ring(s). These findings were confirmed with applications to chamber aerosol and ambient PM2.5. \n\nThis dataset is associated with the following publication:\nJaoui, M., M. Lewandowski, J. Offenberg, M. Colon, K. Docherty, and T. Kleindienst. Characterization of aerosol nitroaromatic compounds: Validation of an experimental method.   Journal of Mass Spectrometry. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 53(8): 680-692, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1416545",
            "keyword": [
                "Nitroaromatics",
                "air quality",
                "Secondary Organic Aerosol",
                "air toxics",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Michael Lewandowski",
                "hasEmail": "mailto:lewandowski.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Jaoui et al NACs Figure Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1416545/Jaoui%20et%20al%20NACs%20Figure%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-05-01",
            "references": [
                "https://doi.org/10.1002/jms.4199"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data contributed by EPA/ORD/NERL/CED researchers to the manuscript \"Influence of anthropogenic emissions and boundary conditions on multi-model simulations of major air pollutants over Europe and North America in the framework of AQMEII3\"",
            "description": "This dataset contains the data contributed by EPA/ORD/NERL/CED researchers to the manuscript \"Influence of anthropogenic emissions and boundary conditions on multi-model simulations of major air pollutants over Europe and North America in the framework of AQMEII3\" led by Dr. Ulas Im of Aarhus University in Denmark. \n\nThis dataset is associated with the following publication:\nIm, U., J. Christensen, C. Geels, K. Hansen, J. Brandt, E. Solazzo, U. Alyuz, A. Balzarini, R. Baro, R. Bellasio, R. Bianconi, J. Bieser, A. Colette, G. Curci, A. Farrow, J. Flemming, A. Fraser, P. Jimenez-Guerrero, N. Kitwiroon, P. Liu, U. Nopmongcol, L. Palacios-Pe\u00f1a, G. Pirovano, L. Pozolli, M. Prank, R. Rose, R. Sokhi, P. Tuccella, A. Unal, M. Garcia Vivanco, G. Yarwood, C. Hogrefe, and S. Galmarini. Influence of anthropogenic emissions and boundary conditions on multi-model simulations of major air pollutants over Europe and North America in the framework of AQMEII3.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 18: 8929-8952, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434306",
            "keyword": [
                "model evaluation",
                "ensemble modeling",
                "emission sensitivity",
                "long-range transport"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/exposure/A-d25k/",
                    "accessURL": "https://gaftp.epa.gov/exposure/A-d25k/"
                }
            ],
            "modified": "2017-01-01",
            "references": [
                "https://doi.org/10.5194/acp-18-8929-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1434306/documents/HogrefeChristian_A-d25k_DataDescription_ImEtAl.zip",
            "describedByType": "application/zip",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data contributed by EPA/ORD/NERL/CED researchers to the manuscript \"Two-scale multi-model ensemble: Is a hybrid ensemble of opportunity telling us more?\"",
            "description": "This dataset contains the data contributed by EPA/ORD/NERL/CED researchers to the manuscript \"Two-scale multi-model ensemble: Is a hybrid ensemble of opportunity telling us more?\" led by Dr. Stefano Galmarini of the European Commission's Joint Research Center. \n\nThis dataset is associated with the following publication:\nGalmarini, S., I. Kioutsioukis, E. Solazzo, U. Alyuz, A. Balzarini, R. Bellasio, A. Benedictow, R. Bianconi, J. Bieser, J. Brandt, J. Christensen, A. Colette, G. Curci, Y. Davila, X. Dong, J. Flemming, X. Francis, A. Fraser, J. Fu, D. Henze, C. Hogrefe, U. Im, M. Garcia Vivanco, P. Jimenez-Guerrero, J. Jonson, N. Kitwiroon, A. Manders, R. Mathur, L. Palacios-Pena, G. Pirovano, L. Pozzoli, M. Prank, M. Schultz, R. Sokhi, K. Sudo, P. Tuccella, T. Takemura, T. Sekiya, and A. Unal. Two-scale multi-model ensemble: is a hybrid ensemble of opportunity telling us more?.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 18: 8727-8744, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434299",
            "keyword": [
                "ensemble modeling",
                "global ozone modeling",
                "regional ozone modeling",
                "categorical evaluation"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "HogrefeChristian_A-pnwj_DataSet.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434299/HogrefeChristian_A-pnwj_DataSet.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-09-01",
            "references": [
                "https://doi.org/10.5194/acp-18-8727-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Citizen Science sensor measurements to support frequently asked questions (FAQ)",
            "description": "This file has two sheets. Data are measurements by Citizen Science Air Monitors (CSAM) and Federal Monitors, which sampled particulate matter (PM), nitrogen dioxide (NO2), relative humidity (RH), and temperature (T). Variables for each sheet are described in more detail below\nThe sheet \u201cSnorkel No-Snorkel Comparison\u201d includes data from two CSAM units, CSAM-2 and CSAM-3. CSAM-2 used a snorkel tube to sample outdoor air, and CSAM-3 did not use a snorkel tube. CSAM-2 and CSAM-3 were not in the same sampling location, but did sample contemporaneous measurements. These data were used to perform a snorkel and no-snorkel comparison. \nThe sheet \u201cCSAM-1 and Federal Monitor\u201d includes data from a CSAM unit (CSAM-1) and a Federal Monitor (which is used for regulatory measurements of air pollution). CSAM-1 and the Federal Monitor were installed in the same sampling location and recorded contemporaneous measurements. For CSAM-1, original recorded measurements are included, as well as measurements that were corrected (using regression equations) to better reflect the Federal Monitor values. \n\nThis dataset is associated with the following publication:\nBarzyk, T., H. Huang, R. Williams, A. Kaufman, and J. Essoka. Advice and Frequently Asked Questions (FAQs) for Citizen-Science Environmental Health Assessments.   International Journal of Environmental Research and Public Health. Molecular Diversity Preservation International, Basel,  SWITZERLAND, 15(5): 960, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1433814",
            "keyword": [
                "Environmental health assessment",
                "Decision analysis",
                "Local stakeholders",
                "Cumulative impacts"
            ],
            "contactPoint": {
                "fn": "Timothy Barzyk",
                "hasEmail": "mailto:barzyk.timothy@epa.gov"
            },
            "distribution": [
                {
                    "title": "BarzykTimothy_A-msc0_Datasets_20180419.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1433814/BarzykTimothy_A-msc0_Datasets_20180419.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-04-01",
            "references": [
                "https://doi.org/10.3390/ijerph15050960"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1433814/documents/BarzykTimothy_A-msc0_DataDictionary_20180419.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data file field studies aerosolized endotoxins biosolids application 2010 and 2012",
            "description": "The dataset consists of columns of values and labels of data collected by air samplers for endotoxin monitoring during the full scale/commercial scale land application of Class B biosolids. The biosolids came from different anaerobic treatment facilities and some material was later treated with lime 24 hours prior to application. \n\nThis dataset is associated with the following publication:\nHerrmann , R., R. Grosser, D. Farrar , and B. Brobst. Field studies measuring the aerosolization of endotoxin during the land application of Class B biosolids.  Carmen Galan  AEROBIOLOGIA. Springer, New York, NY, USA, 0(0): 1-18, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1500910",
            "keyword": [
                "aerosolized endotoxin",
                "endotoxin",
                "biosolids",
                "Class B biosolids",
                "land application",
                "limulus amebocyte lysate"
            ],
            "contactPoint": {
                "fn": "Ronald Herrmann",
                "hasEmail": "mailto:herrmann.ronald@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data file field studies aerosolized endotoxins biosolids app.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500910/Data%20file%20field%20studies%20aerosolized%20endotoxins%20biosolids%20app.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-08-27",
            "references": [
                "https://doi.org/10.1007/s10453-017-9480-8"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data used in the research titled, \"Quantifying the visual-sensory landscapes qualities that contribute to cultural ecosystem services using social media and LiDAR\"",
            "description": "Sample1m are the data used to estimate the Negative Binomial models. The validation dataset compares classified photographs with viewshed estimates of visible land use/cover. \n\nThis dataset is associated with the following publication:\nVanBerkel, D., P. Tabrizian, M.A. Dorning, L. Smart, D. Newcomb, M. Mehaffey, A. Neale, and R.K. Meentemeyer. Quantifying the visual-sensory landscape qualities that contribute to cultural ecosystem services using social media and LiDAR.   Ecosystem Services. Elsevier Online, New York, NY, USA, 31: 326-335, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1433620",
            "keyword": [
                "Cultural Ecosystem Services",
                "Spatial Analysis",
                "Coastal Scenery",
                "social media"
            ],
            "contactPoint": {
                "fn": "Derek Van Berkel",
                "hasEmail": "mailto:van-berkel.derek@epa.gov"
            },
            "distribution": [
                {
                    "title": "SampleNB.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1433620/SampleNB.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "ValidationViewshed.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1433620/ValidationViewshed.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2018-04-19",
            "references": [
                "https://doi.org/10.1016/j.ecoser.2018.03.022"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1433620/documents/VariableDescription.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "amphibian_dehydration_uptake_data",
            "description": "Bioconcentration data for Glinski DA, Henderson WM, Van Meter RJ, Purucker ST 2017. Effect of hydration status on pesticide uptake in anurans following exposure to contaminated soils. \n\nThis dataset is associated with the following publication:\nGlinski, D., M. Henderson, R. Van Meter, and T. Purucker. Effect of hydration status on pesticide uptake in anurans following exposure to contaminated soils.   ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH. Ecomed Verlagsgesellschaft AG, Landsberg,  GERMANY, 25(16): 16192-16201, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407571",
            "keyword": [
                "amphibians",
                "dehydration",
                "pesticides",
                "body burden",
                "uptake"
            ],
            "contactPoint": {
                "fn": "Steven Purucker",
                "hasEmail": "mailto:purucker.tom@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://github.com/puruckertom/glinski_dehydration/tree/master/csv_in",
                    "accessURL": "https://github.com/puruckertom/glinski_dehydration/tree/master/csv_in"
                }
            ],
            "modified": "2017-05-17",
            "references": [
                "https://doi.org/10.1007/s11356-018-1830-8"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Gerties Creek Proper Functioning Condition Data Forms",
            "description": "These are Proper Functioning Condition Reach Information Forms filled out during our assessment at Georgina Island.  The forms are from the Technical Reference 1737-15 Second Edition 2015 from BLM, Forest Service and NRCS.  Dickard et al., 2015. \n\nThis dataset is associated with the following publication:\nHall, R., J. Lin, B. Schumacher, K. Charles, and D. Heggem. Ecological risk based assessment used to restore riparian physical functions to a fresh water Creek.   JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 221: 63-75, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1407681",
            "keyword": [
                "Lotic Reach Assessment",
                "Lentic Reach Assessment",
                "Tribal Sustainability",
                "proper functioning condition",
                "ecological condition assessment",
                "Environmenal health",
                "Ecological Health",
                "Vulnerable Groups"
            ],
            "contactPoint": {
                "fn": "Daniel Heggem",
                "hasEmail": "mailto:heggem.daniel@epa.gov"
            },
            "distribution": [
                {
                    "title": "Gerties Creek Data_ScienceHub.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407681/Gerties%20Creek%20Data_ScienceHub.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "Gerties Creek Data_ScienceHub2.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407681/Gerties%20Creek%20Data_ScienceHub2.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-10-24",
            "references": [
                "https://doi.org/10.1016/j.jenvman.2018.03.117"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Electrolyte Selection for Electrochemical Oxidative Water Treatment Using a Boron-Doped Diamond Anode to Support Site Specific Contamination Incident Response",
            "description": "The dataset contains the raw data for the graphs in the paper. \n\nThis dataset is associated with the following publication:\nPhillips, R., R. James, and M. Magnuson. Electrolyte Selection and Microbial Toxicity for Electrochemical Oxidative Water Treatment Using a Boron-doped Diamond Anode to Support Site Specific Contamination Incident Response.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 197: 135-141, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1407534",
            "keyword": [
                "water security",
                "wastewater",
                "treatment",
                "advanced oxidation process",
                "boron doped diamond electrode",
                "pesticide",
                "PFAS",
                "perfluorinated"
            ],
            "contactPoint": {
                "fn": "Matthew Magnuson",
                "hasEmail": "mailto:magnuson.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "MagnusonMatthew_A-7wmb_data_20170410.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407534/MagnusonMatthew_A-7wmb_data_20170410.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-03",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2018.01.007"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cesium Emissions from Laboratory Fires",
            "description": "The data sets contain the raw and reduced data from the instrument measurements including continuous emission monitoring and stack sampling procedure. \n\nThis dataset is associated with the following publication:\nHao, W.M., S. Baker, E. Lincoln, S. Hudson, S. Lee, and P. Lemieux. Cesium Emissions from Laboratory Fires Article.   JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION. Air & Waste Management Association, Pittsburgh, PA, USA,  49, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1377064",
            "keyword": [
                "continuous emission monitoring",
                "stack sampling",
                "Radiological contamination",
                "forest",
                "wildfire",
                "nuclear power plant accident",
                "radiological dispersal device",
                "RDD",
                "improvised nuclear device",
                "IND",
                "air emissions",
                "cesium partitioning",
                "PM10",
                "pm2.5",
                "radionuclides"
            ],
            "contactPoint": {
                "fn": "Sangdon Lee",
                "hasEmail": "mailto:lee.sangdon@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cs_CEM_data_06152017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377064/Cs_CEM_data_06152017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Missoula Cs Mass Calculations w ICPMS 041717.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1377064/Missoula%20Cs%20Mass%20Calculations%20w%20ICPMS%20041717.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-15",
            "references": [
                "https://doi.org/10.1080/10962247.2018.1493001"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "National Aquatic Resources Survey datasets",
            "description": "The 4 resource surveys (coastal, rivers and streams, lakes and reservoirs, and wetlands) each have datasets covering the biological, chemical, physical habitat, hydrologic and watershed data. \n\nThis dataset is associated with the following publications:\nStoddard , J., J. Van Sickle, A. Herlihy, J. Brahney, S. Paulsen , D. Peck , R. Mitchell , and A. Pollard. Continental-scale increase in stream and lake phosphorus: Are oligotrophic systems disappearing in the U.S.?.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(7): 3409-3415, (2016).\nHerlihy, A., M. Kentula, T. Magee, G. Lomnicky, A. Nahlik, and G. Serenbetz. Striving for consistency in the National Wetland Condition Assessment: developing a reference condition approach for assessing wetlands at a continental scale.   ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 191: 327, (2019).\nMagee, T., K. Blocksom, and S. Fennessy. A national-scale vegetation multimetric index (VMMI) as an indicator of wetland condition across the conterminous United States..   ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 191: 322, (2019).\nHerlihy, A., J. Sifneos, G. Lomnicky, A. Nahlik, M. Kentula, T. Magee, M. Weber, and A. Trebitz. The response of wetland quality indicators to human disturbance indicators across the United States.   ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 191: 296, (2019).\nHerlihy, A., S. Paulsen, M. Kentula, T. Magee, A. Nahlik, and G. Lomnicky. Assessing the relative and attributable risk of stressors to wetland condition across the conterminous United States.   ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 191: 320, (2019).\nLomnicky, G., A.T. Herlihy, and P. Kaufmann. Quantifying the extent of human disturbance activities and anthropogenic stressors in wetlands across the conterminous United States: results from the National Wetland Condition Assessment.   ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 191: 324, (2019).\nBowen, G., A. Putman, J.R. Brooks, D. Bowling, E. Oerter, and S. Good. Inferring the source of evaporated waters using stable H and O isotopes..   OECOLOGIA. Springer, New York, NY, USA, 187(4): 1025-1039, (2018).\nFox, E., J. Ver Hoef, and T. Olsen. Comparing Spatial Regression to Random Forests for Large Environmental Data Sets..   PLoS ONE. Public Library of Science, San Francisco, CA, USA, 15(3): e0229509, (2020).\nNahlik, A., K. Blocksom, A. Herlihy, M. Kentula, T. Magee, and S. Paulsen. Use of national-scale data to examine human-mediated additions of heavy metals to wetland soils of the US.   ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 191: 336, (2019).\nKentula, M., and S. Paulsen. The 2011 National Wetland Condition Assessment: Overview and an Invitation.   ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA,  325, (2019).\nMagee, T., K. Blocksom, A. Herlihy, and A. Nahlik. Characterizing nonnative plants in wetlands across the conterminous United States.   ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 191: 344, (2019).\nFeio, M., R. Hughes, M. Callisto, S.J. Nichols, O.N. Odume, B.R. Quintella, M. Kuemmerlen, F.C. Aguiar, S.F.P. Almeida, P. Alonso-Egu\u00edaLis , F.O. Arimoro, F.J. Dyer , J.S. Harding , S. Jang , P. Kaufmann, S. Lee, J. Li, D.R. Macedo, A. Mendes, N. Mercado-Silva , W. Monk, K. Nakamura, G.G. Ndiritu , R. Ogden , M. Peat , T.B. Reynoldson , B. Rios-Touma , P. Segurado , and A.G. Yates. The biological assessment and rehabilitation of the world\u2019s rivers: an overview.   WATER. MDPI AG, Basel,  SWITZERLAND, 13(3): 371, (2021).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407622",
            "keyword": [
                "wetlands",
                "assessment",
                "coastal",
                "aquatic monitoring",
                "rivers and streams",
                "lakes and reservoirs"
            ],
            "contactPoint": {
                "fn": "Steven Paulsen",
                "hasEmail": "mailto:paulsen.steve@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys"
                }
            ],
            "modified": "2017-09-01",
            "references": [
                "https://doi.org/10.1021/acs.est.5b05950",
                "https://doi.org/10.1007/s10661-019-7325-3",
                "https://doi.org/10.1007/s10661-019-7324-4",
                "https://doi.org/10.1007/s10661-019-7323-5",
                "https://doi.org/10.1007/s10661-019-7313-7",
                "https://doi.org/10.1007/s10661-019-7314-6",
                "https://doi.org/10.1007/s00442-018-4192-5",
                "https://doi.org/10.1371/journal.pone.0229509",
                "https://doi.org/10.1007/s10661-019-7315-5",
                "https://doi.org/10.1007/s10661-019-7316-4",
                "https://doi.org/10.1007/s10661-019-7317-3",
                "https://doi.org/10.3390/w13030371"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Domain and HWBI Scores for CWBI",
            "description": "Geo-located county-level domain and HWBI results calculated based on HWBI framework adaptations for the development of a U.S. Children's Well-Being Index. The file contains 3143 entries. Scores are standardized between 0 and 1. \n\nThis dataset is associated with the following publication:\nBuck, K., K. Summers, L. Smith, and L. Harwell. Application of the Human Well-Being Index to Sensitive Population Divisions: A Children's Well-Being Index Development.   Child Indicators Research. Springer Netherlands,   NETHERLANDS, 11(4): 1249-1280, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1394635",
            "keyword": [
                "children's well-being",
                "HWBI",
                "sustainability",
                "indicators"
            ],
            "contactPoint": {
                "fn": "Kyle Buck",
                "hasEmail": "mailto:buck.kyle@epa.gov"
            },
            "distribution": [
                {
                    "title": "CWBI-ScienceHubEntry.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394635/CWBI-ScienceHubEntry.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-25",
            "references": [
                "https://doi.org/10.1007/s12187-017-9469-4"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Boyes et al., Figure 1A",
            "description": "Data support each of the figures in Boyes et al., Moderate Perinatal Thyroid Hormone Insufficiency Alters Visual System Function in Adult Rats (to be submitted for publication). \n\nThis dataset is associated with the following publication:\nBoyes, W., L. Degn, B. George, and M. Gilbert. Moderate Perinatal Thyroid Hormone Insufficiency Alters Visual System Function in Adult Rats.   NEUROTOXICOLOGY. Elsevier B.V., Amsterdam,  NETHERLANDS, 67: 73-83, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1410657",
            "keyword": [
                "electroretinograms",
                "visual evoked potentials",
                "propylthiouracil",
                "endocrine disruptor",
                "developmental hypothyroidism",
                "visual impairment"
            ],
            "contactPoint": {
                "fn": "William Boyes",
                "hasEmail": "mailto:boyes.william@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure 1A.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1410657/Figure%201A.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 1B.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1410657/Figure%201B.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 1E.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1410657/Figure%201E.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 1D.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1410657/Figure%201D.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 1F.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1410657/Figure%201F.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 1C.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1410657/Figure%201C.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 2C.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1410657/Figure%202C.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 3.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1410657/Figure%203.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 4.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1410657/Figure%204.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 2A and 2B spectra.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1410657/Figure%202A%20and%202B%20spectra.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figure 2A and 2B waveforms.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1410657/Figure%202A%20and%202B%20waveforms.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-11-30",
            "references": [
                "https://doi.org/10.1016/j.neuro.2018.04.013"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Method 1615 Quantal Data",
            "description": "Groundwater samples and reageant grade water samples. \n\nThis dataset is associated with the following publication:\nFout , S., and J. Cashdollar. EPA Method 1615. Measurement of Enterovirus and Norovirus Occurrence in Water by Culture and RT-qPCR. II. Total Culturable Virus Assay.   Journal of Visualized Experiments. JoVE, Somerville, MA, USA, 115: e52437, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407572",
            "keyword": [
                "occurrence",
                "total culturable virus assay",
                "virus",
                "waterborne"
            ],
            "contactPoint": {
                "fn": "Jennifer Cashdollar",
                "hasEmail": "mailto:cashdollar.jennifer@epa.gov"
            },
            "distribution": [
                {
                    "title": "Final Corrected quantal data for JoVE II 29Jun17.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407572/Final%20Corrected%20quantal%20data%20for%20JoVE%20II%2029Jun17.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-09-17",
            "references": [
                "https://doi.org/10.3791/52437"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cookstove data",
            "description": "No dataset available. This dataset is not publicly accessible because: The dataset was never touched by EPA employees. Data was collected, analyzed, and maintained solely by non-EPA collaborators. It can be accessed through the following means: Dataset can be accessed by contacting the senior PI on the research effort, Kristina Whitworth (Kristina.W.Whitworth@uth.tmc.edu). Format: Dataset was handled solely by non-EPA collaborators on this research effort. EPA employee role on this research effort was purely advisory. \n\nThis dataset is associated with the following publication:\nMisra, A., M. Longnecker, K. Dionisio, R. Bornman, G. Travlos, S. Brar, and K. Whitworth. Household fuel use and biomarkers of inflammation and respiratory illness among rural South African Women.   ENVIRONMENTAL RESEARCH. Academic Press Incorporated, Orlando, FL, USA, 166: 112-116, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390130",
            "keyword": [
                "biomass",
                "household fuel",
                "Wood",
                "inflammation",
                "biomarkers",
                "respiratory"
            ],
            "contactPoint": {
                "fn": "Kathie Dionisio",
                "hasEmail": "mailto:dionisio.kathie@epa.gov"
            },
            "distribution": [],
            "modified": "2017-03-15",
            "references": [
                "https://doi.org/10.1016/j.envres.2018.05.016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A summary and detailed description of research elements and results that are the building block for the journal article",
            "description": "The PPT file describes the results of research that serve as the basis for the journal article. \n\nThis dataset is associated with the following publication:\nWei, H., T. Zuo, H. Liu, and J. Yang. Integrating Land Use and Socioeconomic Factors into Scenario-Based Travel Demand and Carbon Emission Impact Study.   Urban Rail Transit. Springer International Publishing AG, Cham (ZG),  SWITZERLAND, 3(1): 3-14, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1502494",
            "keyword": [
                "Integration",
                "land use",
                "Socioeconomic factor",
                "Travel demand",
                "Transportation environmental",
                "Carbon emission"
            ],
            "contactPoint": {
                "fn": "Yingping Yang",
                "hasEmail": "mailto:yang.jeff@epa.gov"
            },
            "distribution": [
                {
                    "title": "WA4-45_Task2_Presentation_10_19_2015.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502494/WA4-45_Task2_Presentation_10_19_2015.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2018-07-20",
            "references": [
                "https://doi.org/10.1007/s40864-017-0056-2"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Final QCd Ricin Attenuation Data",
            "description": "Unzip the file to find a spreadsheet for each test.  Each spreadsheet contains the amt of ricin recovered from both positive and test coupons, for both crude and pure ricin forms. \n\nThis dataset is associated with the following publication:\nWood, J., W. Richter, A. Smiley, and J. Rogers. Influence of environmental conditions on the attenuation of ricin toxin on surfaces.   PLoS ONE. Public Library of Science, San Francisco, CA, USA,  9, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1432984",
            "keyword": [
                "Ricin",
                "attenuation"
            ],
            "contactPoint": {
                "fn": "Joseph Wood",
                "hasEmail": "mailto:wood.joe@epa.gov"
            },
            "distribution": [
                {
                    "title": "TO17 Final Datav2.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1432984/TO17%20Final%20Datav2.zip",
                    "mediaType": "application/zip"
                }
            ],
            "modified": "2018-04-13",
            "references": [
                "https://doi.org/10.1371/journal.pone.0201857"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Links to USGS NWIS repositories of monitoring data",
            "description": "These are quality-assured time series datasets from weather stations and runoff volume monitoring infrastructure, Cleveland OH. \n\nThis dataset is associated with the following publication:\nShuster, W., and R. Darner. Hydrologic Performance of Retrofit Rain Gardens in a Residential Neighborhood (Cleveland Ohio USA) with a Focus on Monitoring Methods. U.S. Environmental Protection Agency, Washington, DC, USA, 2018.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1502452",
            "keyword": [
                "Green Infrastructure",
                "stormwater management",
                "wastewater management",
                "combined sewers",
                "sewershed",
                "rain gardens",
                "bioretention"
            ],
            "contactPoint": {
                "fn": "William Shuster",
                "hasEmail": "mailto:shuster.william@epa.gov"
            },
            "distribution": [
                {
                    "title": "Links to monitoring data _Slavic Village Rain Garden Study 2012-2016.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502452/Links%20to%20monitoring%20data%20_Slavic%20Village%20Rain%20Garden%20Study%202012-2016.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2018-07-06",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "GoldenHeather_A-f7mb_Data_20170619",
            "description": "Output from model simulation runs and used for figures in the manuscript. An index for header terms can be found in the dataset. \n\nThis dataset is associated with the following publication:\nEvenson, G., H. Golden, C. Lane, D. McLaughlin, and E. D'Amico. Depressional wetlands affect watershed hydrological, biogeochemical, and ecological functions.   ECOLOGICAL APPLICATIONS. Ecological Society of America, Ithaca, NY, USA, 28(4): 953-966, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1366490",
            "keyword": [
                "wetlands",
                "watersheds",
                "hydrology",
                "watershed models",
                "Watershed"
            ],
            "contactPoint": {
                "fn": "Heather Golden",
                "hasEmail": "mailto:golden.heather@epa.gov"
            },
            "distribution": [
                {
                    "title": "GoldenHeather_A-f7mb_Data_20170619.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1366490/GoldenHeather_A-f7mb_Data_20170619.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-16",
            "references": [
                "https://doi.org/10.1002/eap.1701"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Depressed Roadways",
            "description": "This data set is associated with the results found in the journal article: Amini et al, 2018. Modeling Dispersion of Emissions from Depressed Roadways. Authors: Seyedmorteza Amini, Faraz Enayati Ahangar, David K. Heist, Steven G. Perry, Akula Venkatram. \nThis paper presents an analysis of data from a wind tunnel study of dispersion of emissions from three depressed roadway configurations; a 6 m deep depressed roadway with vertical sidewalls, a 6 m deep depressed roadway with 30\u00b0 sloping sidewalls, and a 9 m deep depressed roadway with vertical sidewalls. All these configurations induce complex flow fields, increase turbulence levels, and decrease surface concentrations downwind of the depressed road compared to those of the at-grade configuration. The parameters of flat terrain dispersion models are modified to describe concentrations measured downwind of the depressed roadways. In the first part of the paper, a flat terrain model proposed by van Ulden (1978) is adapted. It turns out that this model with increased initial vertical dispersion and friction velocity is able to explain the observed concentration field. The results also suggest that the vertical concentration profiles of all cases under neutral conditions are best explained by a vertical distribution function with an exponent of 1.3. In the second part of the paper, these modifications are incorporated into a model based on the RLINE  line-source dispersion model. While this model can be adapted to yield acceptable estimates of near-surface concentrations (z< 6m) measured in the wind tunnel, the Gaussian vertical distribution in RLINE, with an exponent of 2, cannot describe the concentration at higher elevations. Our findings suggest a simple method to account for depressed highways in models such as RLINE and AERMOD through two parameters that modify vertical plume spread. \n\nThis dataset is associated with the following publication:\nAmini, S., F. Ahangar, D. Heist, S. Perry, and A. Venkatram. Modeling Dispersion of Emissions from Depressed Roadways.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 186: 189-197, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434500",
            "keyword": [
                "near-road",
                "dispersion modeling",
                "wind tunnel"
            ],
            "contactPoint": {
                "fn": "David Heist",
                "hasEmail": "mailto:heist.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "HeistDavid_A-j9kw_Data-DepressedRoadways.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434500/HeistDavid_A-j9kw_Data-DepressedRoadways.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-05-11",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2018.04.058"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1434500/documents/HeistDavid_A-j9kw_DataDictionary_DepressedRoadways.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Fourier Transformed Infrared (FTIR) Spectroscopy Data for Soil Carbon, Extractable Carbon, Changes in Soil FTIR Spectra, FTIR Data Clustering & Discriminant Analysis ",
            "description": "Here we report on a rapid, high throughput approach using fingerprint Fourier transformed infrared (FTIR) spectroscopy and chemometric modeling. Fingerprint FTIR incorporates all information embedded within the FTIR spectrum, thus producing a biogeochemical or ecological \u201cfingerprint\u201d of the soil. This methodology was applied in a highly disturbed forest ecosystem over a 19-year sampling period to detect, via spectral analysis, changes in dynamic soil properties (e.g., soil organic matter and reactive mineralogy) that can indicate changes in soil quality. Two chemometric statistical techniques (i.e., hierarchical clustering analysis [HCA] and discriminate analysis of principal components [DAPC]) were evaluated for interpreting and quantifying similarities/dissimilarities between samples utilizing the entire FTIR spectra from each sample. \n\nThis dataset is associated with the following publication:\nMaynard, J., and M. Johnson. Applying fingerprint Fourier transformed infrared spectroscopy and chemometrics to assess soil ecosystem disturbance and recovery.   JOURNAL OF SOIL AND WATER CONSERVATION. Soil and Water Conservation Society,    73(4): 443-451, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1502535",
            "keyword": [
                "Soil carbon",
                "FTIR",
                "Discriminant analysis",
                "system recovery",
                "Forest soil",
                "remote sensing",
                "Terrain analysis",
                "spatial variability",
                "redundancy analysis",
                "variation partitioning"
            ],
            "contactPoint": {
                "fn": "Mark Johnson",
                "hasEmail": "mailto:johnson.markg@epa.gov"
            },
            "distribution": [
                {
                    "title": "Maynard and Johnson 2018_JSWC_Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502535/Maynard%20and%20Johnson%202018_JSWC_Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-06-08",
            "references": [
                "https://doi.org/10.2489/jswc.73.4.443"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "1990-2010 atmospheric deposition of Sulfur and nitrogen",
            "description": "These data files associated with the Tables and Figures presented in the following manuscript:\nZhang, Y., Mathur, R., Bash, J. O., Hogrefe, C., Xing, J., and Roselle, S. J.: Long-term trends in total inorganic nitrogen and sulfur deposition in the US from 1990 to 2010, Atmos. Chem. Phys., 18, 9091-9106, https://doi.org/10.5194/acp-18-9091-2018, 2018. \n\nThis dataset is associated with the following publication:\nZhang, Y., R. Mathur, J. Bash, C. Hogrefe, J. Xing, and S. Roselle. Long-term trends in total inorganic nitrogen and sulfur deposition in the US from 1990 to 2010.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 18: 9091-9106, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434279",
            "keyword": [
                "atmospheric deosition",
                "long term trends",
                "nitrogen",
                "sulfur"
            ],
            "contactPoint": {
                "fn": "Rohit Mathur",
                "hasEmail": "mailto:mathur.rohit@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figs_1_3_Tables_1_stations.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Figs_1_3_Tables_1_stations.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figs_4_TSO4_def.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Figs_4_TSO4_def.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figs_4_TIN_abc.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Figs_4_TIN_abc.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figs_6_def_DDEP_TIN.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Figs_6_def_DDEP_TIN.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figs_7_abc_WDEP_S.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Figs_7_abc_WDEP_S.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figs_7_def_DDEP_S.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Figs_7_def_DDEP_S.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figs_8_Total Deposition & Emissions trend.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Figs_8_Total%20Deposition%20%26%20Emissions%20trend.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Figs_5_NHx_trend.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Figs_5_NHx_trend.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Table_2_Ecoregions_Evaluation_TNO3_Obs.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Table_2_Ecoregions_Evaluation_TNO3_Obs.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Table_3_Ecoregions_Evaluation_NHX_Obs.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Table_3_Ecoregions_Evaluation_NHX_Obs.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figs_5_TNO3_trend.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Figs_5_TNO3_trend.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figs_6_abc_WDEP_TIN.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Figs_6_abc_WDEP_TIN.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Table_4_Ecoregions_Evaluation_TSO4_Obs.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Table_4_Ecoregions_Evaluation_TSO4_Obs.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Tables_5_6_Deposition_Trends_Ecoregions_NHX.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Tables_5_6_Deposition_Trends_Ecoregions_NHX.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Tables_5_6_Deposition_Trends_Ecoregions_TIN.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Tables_5_6_Deposition_Trends_Ecoregions_TIN.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Tables_5_6_Deposition_Trends_Ecoregions_TNO3.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Tables_5_6_Deposition_Trends_Ecoregions_TNO3.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figs_9_TDEP_NHx_Ratio.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Figs_9_TDEP_NHx_Ratio.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Tables_5_6_Deposition_Trends_Ecoregions_TSO4.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434279/Tables_5_6_Deposition_Trends_Ecoregions_TSO4.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2018-06-15",
            "references": [
                "https://doi.org/10.5194/acp-18-9091-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1434279/documents/Data_Dictionary_acp-2018-116.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset for Identification of Biomarkers of Exposure to FTOHs  and PAPs in Humans Using a Targeted and Non-targeted Analysis Approach",
            "description": "Dataset for Identification of Biomarkers of Exposure to FTOHs  and PAPs in Humans Using a Targeted and Non-targeted Analysis Approach. \n\nThis dataset is associated with the following publication:\nDagnino, A., M. Strynar, R. McMahen, C. Lau, C. Ball, S. Garantziosis, T. Webster, M. McClean, and A. Lindstrom. Identification of Biomarkers of Exposure to FTOHs  and PAPs in Humans Using a Targeted and Non-targeted Analysis Approach.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(0): 10216-10225, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407650",
            "keyword": [
                "flurorotelomer alcohol",
                "biomarkers",
                "human",
                "Metabolism",
                "per and poly-fluorinated"
            ],
            "contactPoint": {
                "fn": "Mark Strynar",
                "hasEmail": "mailto:strynar.mark@epa.gov"
            },
            "distribution": [
                {
                    "title": "Dagnino Dataset Information Document.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407650/Dagnino%20Dataset%20Information%20Document.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2012-01-01",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "EWRI World Water Congress 2018 Presentation Dataset",
            "description": "Data and Tables and Figures in EWRI 2018 presentation. \n\nThis dataset is associated with the following publication:\nBlaisi, N., J. Roessler, W. Cheng, T. Townsend, and S. Al-Abed. Evaluation of the impact of lime softening waste disposal in natural environments.  R. Cossu  WASTE MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 43: 524-532, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1502476",
            "keyword": [
                "Flue Gas Desulfurization",
                "limestone",
                "lime sludge",
                "life cycle assessment",
                "environmental impact assessment",
                "mercury re-emission"
            ],
            "contactPoint": {
                "fn": "Craig Patterson",
                "hasEmail": "mailto:patterson.craig@epa.gov"
            },
            "distribution": [
                {
                    "title": "EWRI2018PresentationDataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502476/EWRI2018PresentationDataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-07-11",
            "references": [
                "https://doi.org/10.1016/j.wasman.2015.06.015"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Intergenerational responses of wheat to CeO2 nanoparticles, growth and nutrient contents",
            "description": "The intergenerational impact of engineered nanomaterials in plants is a key knowledge gap in the literature. A soil microcosm study was performed to assess the effects of multi-generational exposure of wheat (Triticum aestivum L.) to cerium oxide nanoparticles (CeO2-NPs). Seeds from plants that were exposed to 0, 125, and 500 mg CeO2-NPs/kg soil (Ce-0, Ce-125 or Ce-500, respectively) in first generation (S1) were cultivated in factorial combinations of Ce-0, Ce-125 or Ce-500 to produce second generation (S2) plants. The factorial combinations for first/second generation treatments in Ce-125 were S1-Ce-0/S2-Ce-0, S1-Ce-0/S2-Ce-125, S1-Ce-125/S2-Ce-0 and S1-Ce-125/S2-Ce-125, and in Ce-500 were S1-Ce-0/S2-Ce-0, S1-Ce-0/S2-Ce-500, S1-Ce-500/S2-Ce-0 and S1-Ce-500/S2-Ce-500. Agronomic, elemental, isotopic, and synchrotron X-ray fluorescence (XRF) and X-ray absorption near-edge spectroscopy (XANES) data were collected on second generation plants. Results showed that plants treated during the first generation only with either Ce-125 or Ce-500 (e.g. S1-Ce-125/S2-Ce-0 or S1-Ce-500/S2-Ce-0) had reduced accumulation of Ce (61 or 50%), Fe (49 or 58%) and Mn (34 or 41%) in roots, and \u03b415N (11 or 8%) in grains compared to the plants not treated in both generations (i.e. S1-Ce-0/S2-Ce-0). Plants treated in both generations with Ce-125 (i.e. S1-Ce-125/S2-Ce-125) produced grains that had lower Mn, Ca, K, Mg and P relative to plants treated in the second generation only (i.e. S1-Ce-0/S2-Ce-125). In addition, synchrotron XRF elemental chemistry maps of soil/plant thin-sections revealed limited transformation of CeO2-NPs with no evidence of plant uptake or accumulation. The findings demonstrated that first generation exposure of wheat to CeO2-NPs affects the physiology and nutrient profile of the second generation plants. However, the lack of concentration-dependent responses indicate that complex physiological processes are involved which alter uptake and metabolism of CeO2-NPs in wheat. \n\nThis dataset is associated with the following publication:\nRico, C., M. Johnson, M. Marcus, and C. Andersen. Intergenerational responses of wheat (Triticum aestivum L.) to cerium oxide nanoparticles exposure.   Environmental Science: Nano. RSC Publishing, Cambridge,  UK, 4: 700-711, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1502592",
            "keyword": [
                "ammonium nitrate",
                "intergenerational effects",
                "isotope",
                "isotopic discrimination",
                "nitrogen",
                "engineered nanomaterials (ENMs)"
            ],
            "contactPoint": {
                "fn": "Christian Andersen",
                "hasEmail": "mailto:andersen.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "CeO2 Wheat Intergenerational Data Repository for 8-24-18.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502592/CeO2%20Wheat%20Intergenerational%20Data%20Repository%20for%208-24-18.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-08-27",
            "references": [
                "https://doi.org/10.1039/c7en00057j"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Changes in gene expression in Arabidopsis in response to nano CeO2 and nano TiO2",
            "description": "- Changes in tissue transcriptomes and productivity of Arabidopsis thaliana were investigated during exposure of plants to two widely used engineered metal oxide nanoparticles, titanium dioxide (nano-titanium) and cerium dioxide (nano-cerium). Microarray analyses confirmed that exposure to either nanoparticle altered the transcriptomes of rosette leaves and roots, with comparatively larger numbers of differentially expressed genes (DEGs) found under nano-titania exposure. Nano-titania induced more DEGs in rosette leaves, whereas roots had more DEGs under nano-ceria exposure.  MapMan analyses indicated that while nano-titania up-regulated overall metabolism metabolism in both tissues, metabolic processes under nano-ceria remained mostly unchanged. Gene enrichment analysis indicated that both nanoparticles mainly enriched ontology groups such as responses to stress (abiotic and biotic), and defense responses (pathogens), and responses to endogenous stimuli (hormones). Nano-titania specifically induced genes associated with photosynthesis, whereas nano-ceria induced expression of genes related to activating transcription factors, most notably those belonging to the ethylene responsive element binding protein family.  Interestingly, there were also increased numbers of rosette leaves and plant biomass under nano-ceria exposure, but not under nano-titania. Other transcriptomic responses did not clearly relate to responses observed at the organism level. This may be due to functional and genomic redundancy in Arabidopsis, which may mask expression of morphological changes, despite discernable responses at the transcriptome level. Additionally, transcriptomic changes often relate with transgenerational phenotypic development, hence it may be productive to direct further experimental work to integrate high-throughput genomic results with longer-term changes in subsequent generations. \n\nThis dataset is associated with the following publication:\nTumburu, L., C. Andersen, P.T. Rygiewicz, and J. Reichman. Molecular and physiological responses to titanium dioxide and cerium oxide nanoparticles in arabidopsis.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 36(1): 71-82, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1502593",
            "keyword": [
                "ammonium nitrate",
                "intergenerational effects",
                "isotope",
                "isotopic discrimination",
                "nitrogen",
                "engineered nanomaterials (ENMs)"
            ],
            "contactPoint": {
                "fn": "Christian Andersen",
                "hasEmail": "mailto:andersen.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE80461",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE80461"
                }
            ],
            "modified": "2018-08-27",
            "references": [
                "https://doi.org/10.1002/etc.3500"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset for modeling spatial and temporal variation in natural background specific conductivity",
            "description": "This file contains the data set used to develop a random forest model predict background specific conductivity for stream segments in the contiguous United States. This Excel readable file contains 56 columns of parameters evaluated during development.  The data dictionary provides the definition of the abbreviations and the measurement units.  Each row is a unique sample described as R** which indicates the NHD Hydrologic Unit (underscore), up to a 7-digit COMID, (underscore) sequential sample month.\nTo develop models that make stream-specific predictions across the contiguous United States, we used StreamCat data set and process (Hill et al. 2016; https://github.com/USEPA/StreamCat). The StreamCat data set is based on a network of stream segments from NHD+ (McKay et al. 2012). These stream segments drain an average area of 3.1 km2 and thus define the spatial grain size of this data set. \nThe data set consists of minimally disturbed sites representing the natural variation in environmental conditions that occur in the contiguous 48 United States. More than 2.4 million SC observations were obtained from STORET (USEPA 2016b), state natural resource agencies, the U.S. Geological Survey (USGS) National Water Information System (NWIS) system (USGS 2016), and data used in Olson and Hawkins (2012) (Table S1). Data include observations made between 1 January 2001 and 31 December 2015 thus coincident with Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data (https://modis.gsfc.nasa.gov/data/). Each observation was related to the nearest stream segment in the NHD+. Data were limited to one observation per stream segment per month. SC observations with ambiguous locations and repeat measurements along a stream segment in the same month were discarded. Using estimates of anthropogenic stress derived from the StreamCat database (Hill et al. 2016), segments were selected with minimal amounts of human activity (Stoddard et al. 2006) using criteria developed for each Level II Ecoregion (Omernik and Griffith 2014).  Segments were considered as potentially minimally stressed where watersheds had 0 - 0.5% impervious surface, 0 \u2013 5% urban, 0 \u2013 10% agriculture, and population densities from 0.8 \u2013 30 people/km2 (Table S3). Watersheds with observations with large residuals in initial models were identified and inspected for evidence of other human activities not represented in StreamCat (e.g., mining, logging, grazing, or oil/gas extraction). Observations were removed from disturbed watersheds, with a tidal influence or unusual geologic conditions such as hot springs. About 5% of SC observations in each National Rivers and Stream Assessment (NRSA) region were then randomly selected as independent validation data. The remaining observations became the large training data set for model calibration. \n\nThis dataset is associated with the following publication:\nOlson, J., and S. Cormier. Modeling spatial and temporal variation in natural background specific conductivity.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 53(8): 4316-4325, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1500945",
            "keyword": [
                "drought",
                "StreamCat",
                "conductivity",
                "Carbonate Salts",
                "modeled conductivity"
            ],
            "contactPoint": {
                "fn": "Susan Cormier",
                "hasEmail": "mailto:cormier.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "RefModelData_508.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500945/RefModelData_508.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-06-14",
            "references": [
                "https://doi.org/10.1021/acs.est.8b06777"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1500945/documents/Data_Dictionary_RefModelData_20180611_508.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "2009 USVI",
            "description": "EPA conducted a small regional coral reef assessment at 13 stations selected to represent a range of human influence around Charlotte Amalie (CA) Port in St. Thomas.  Sites were selected to represent an east-west gradient of human disturbance with CA at its center. In order to minimize habitat differences, all locations were selected in close proximity to land and at a similar depth (5-9 m). Multiple biological assemblages were measured, including stony corals, sponges and gorgonians, fish, and invertebrates. \n\nThis dataset is associated with the following publication:\nOliver, L., W. Fisher, L. Fore, A. Smith, and P. Bradley. Assessing Land Use, Sedimentation and Water Quality Stressors as Predictors of Coral Reef Condition in St. Thomas, U.S. Virgin Islands.   ENVIRONMENTAL MONITORING AND ASSESSMENT. Springer, New York, NY, USA, 190: 213, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1425905",
            "keyword": [
                "coral reef condition",
                "stony coral",
                "biocriteria",
                "probability based sampling",
                "reef assessments",
                "Puerto Rico",
                "USVI"
            ],
            "contactPoint": {
                "fn": "William Fisher",
                "hasEmail": "mailto:fisher.william@epa.gov"
            },
            "distribution": [
                {
                    "title": "Fish_USVI2009CA_FMay062016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1425905/Fish_USVI2009CA_FMay062016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Inverts_USVI2009CA_FMay062016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1425905/Inverts_USVI2009CA_FMay062016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Rugosity_USVI2009CA_FMay062016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1425905/Rugosity_USVI2009CA_FMay062016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "SpGorg_USVI2009CA_FMay062016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1425905/SpGorg_USVI2009CA_FMay062016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Stonycoral_USVI2009CA_FMay062016.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1425905/Stonycoral_USVI2009CA_FMay062016.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Metric Table_Surveys.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1425905/Metric%20Table_Surveys.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "StationInfo_USVI2009CA_FMar2018.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1425905/StationInfo_USVI2009CA_FMar2018.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "FORAM Data StThomas-USVI 2009.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1425905/FORAM%20Data%20StThomas-USVI%202009.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-05-01",
            "references": [
                "https://doi.org/10.1007/s10661-018-6562-1"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Differentiating Pathway-Specific From Nonspecific Effects in High-Throughput Toxicity Data: A Foundation for Prioritizing Adverse Outcome Pathway Development",
            "description": "Previous work identified a \u2018cytotoxic burst\u2019 (CTB) phenomenon wherein large numbers of the ToxCast assays begin to respond at or near test chemical concentrations that elicit cytotoxicity, and a statistical approach to defining the bounds of the CTB was developed. To focus AOP development on the molecular targets corresponding to ToxCast assays indicating pathway-specific effects, we conducted a meta-analysis to identify which assays most frequently respond at concentrations below the CTB.  A preliminary list of potentially important, target-specific assays was determined by ranking assays by the fraction of chemical hits below the CTB compared to the number of chemicals tested.  Additional priority assays were identified using a diagnostic-odds-ratio approach which gives greater ranking to assays with high specificity but low responsivity. Combined, the two prioritization methods identified several novel targets (e.g., peripheral benzodiazepine and progesterone receptors) to prioritize for AOP development, and affirmed the importance of a number of existing AOPs aligned with ToxCast targets (e.g., thyroperoxidase, estrogen receptor, aromatase). \n\nThis dataset is associated with the following publication:\nFay, K., J. Swintek, D. Villeneuve, S. Edwards, M. Nelms, B. Blackwell, and G. Ankley. Differentiating pathway-specific from non-specific effects in high-throughput toxicity data: A foundation for prioritizing adverse outcome pathway development.   TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA,  163(2): 500-515, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1434917",
            "keyword": [
                "computational toxicology",
                "ToxCast",
                "adverse outcome pathway",
                "ecotoxicology",
                "endocrine disruption",
                "screening and prioritization",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434917/data.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "cytoburst code.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434917/cytoburst%20code.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Science hub_Cytotoxic burst_2.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434917/Science%20hub_Cytotoxic%20burst_2.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-04-30",
            "references": [
                "https://doi.org/10.1093/toxsci/kfy049"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "HTTK R Package v1.7 - Evaluation and Calibration of High-Throughput Predictions of Chemical Distribution to Tissues",
            "description": "httk: High-Throughput Toxicokinetics\n\nFunctions and data tables for simulation and statistical analysis of chemical toxicokinetics (\"TK\") using data obtained from relatively high throughput, in vitro studies. Both physiologically-based (\"PBTK\") and empirical (e.g., one compartment) \"TK\" models can be parameterized for several hundred chemicals and multiple species. These models are solved efficiently, often using compiled (C-based) code. A Monte Carlo sampler is included for simulating biological variability and measurement limitations. Functions are also provided for exporting \"PBTK\" models to \"SBML\" and \"JARNAC\" for use with other simulation software. These functions and data provide a set of tools for in vitro-in vivo extrapolation (\"IVIVE\") of high throughput screening data (e.g., ToxCast) to real-world exposures via reverse dosimetry (also known as \"RTK\"). \n\nThis dataset is associated with the following publication:\nPearce, R., W. Setzer, J. Davis, and J. Wambaugh. Evaluation and Calibration of High-Throughput Predictions of Chemical Distribution to Tissues.   JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS. Springer, New York, NY, USA, 44(6): 549-565, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1390262",
            "keyword": [
                "r package",
                "ToxCast",
                "PBPK-reverse dosimetry",
                "in vitro to in vivo extrapolation (IVIVE)",
                "httk",
                "high throughput toxicokinetics",
                "ExpoCast",
                "exposure"
            ],
            "contactPoint": {
                "fn": "John Wambaugh",
                "hasEmail": "mailto:wambaugh.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://cran.r-project.org/web/packages/httk/index.html",
                    "accessURL": "https://cran.r-project.org/web/packages/httk/index.html"
                }
            ],
            "modified": "2017-07-15",
            "references": [
                "https://doi.org/10.1007/s10928-017-9548-7"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Simmons_DeGroot_Metabolism_mRNA_transfection_ApplInVitroTox_Data",
            "description": "The US EPA\u2019s ToxCast program is designed to assess chemical perturbations of molecular and cellular endpoints using a variety of high-throughput screening (HTS) assays. However, existing HTS assays have limited or no xenobiotic metabolism which could lead to false positive (chemical is detoxified in vivo) as well as false negative results (chemical is bioactivated in vivo) and thus potential mischaracterization of chemical hazard. We have addressed this challenge by introducing the ten most prevalent human liver cytochrome P450 (CYP) enzymes into a human cell line (HEK293T) with low endogenous metabolic capacity. The CYP enzymes were introduced via transfection of modified mRNAs as singlets or as a mixture in relative proportions expressed in the liver. Initial experiments using luminogenic CYP450 substrates demonstrate that cell models express metabolic enzymes from the transfected mRNAs and activities are significantly increased when co-transfected with a CYP accessory protein, P450 oxidoreductase (POR). Transfected HEK293T cells demonstrate the ability to produce predicted metabolites following treatment with well-studied CYP substrates, with metabolite formation occurring through 18 hours post-treatment. As a demonstration of how this method can be used to retrofit existing HTS assays, a proof-of-concept screen for cytotoxicity in HEK293T cells was conducted using 56 test compounds. The results demonstrate that the xenobiotic metabolism conferred by transfection of CYP-encoding mRNAs shifts the dose-response relationship for certain test chemicals such as aflatoxin B1 (bioactivation) and fenazaquin (detoxification). Overall, transfection of CYP-encoding mRNAs is an effective and portable solution for retrofitting metabolic competence to existing cell-based HTS assays. \n\nThis dataset is associated with the following publication:\nDeGroot, D., A. Swank, R. Thomas, M. Strynar, M. Lee, P. Carmichael, and S. Simmons. mRNA transfection retrofits cell-based assays with xenobiotic metabolism.   JOURNAL OF PHARMACOLOGICAL & TOXICOLOGICAL METHODS. Elsevier Science Ltd, New York, NY, USA, 92: 77-94, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407700",
            "keyword": [
                "Metabolism",
                "biotransformation",
                "cell-based assay",
                "ToxCast",
                "High throughput screening"
            ],
            "contactPoint": {
                "fn": "Steven Simmons",
                "hasEmail": "mailto:simmons.steve@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/Simmons_Steve/Metabolism_mRNA_transfection/",
                    "accessURL": "https://gaftp.epa.gov/comptox/NCCT_Publication_Data/Simmons_Steve/Metabolism_mRNA_transfection/"
                }
            ],
            "modified": "2017-10-16",
            "references": [
                "https://doi.org/10.1016/j.vascn.2018.03.002"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Rapid Experimental Estimates of Physicochemical Properties",
            "description": "We have performed high-throughput experimental estimates of five physicochemical properties for a set of 200 chemicals to evaluate the consistency with previous measurements, factors impacting consistency and experimental success, and the applicability domain of the new data in relation to previously measured data and predictive models. \n\nThis dataset is associated with the following publication:\nNicolas, C., K. Mansouri, K. Phillips, C. Grulke, A. Richard, A. Williams, J. Rabinowitz, K. Isaacs, A. Yau, and J. Wambaugh. (ENVIRONMENTAL SCIENCE and TECHNOLOGY) Rapid Experimental Estimates of Physicochemical Properties to Inform Models and Testing.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 636: 901-909, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1395223",
            "keyword": [
                "physicochemical properties",
                "QSAR modeling",
                "quantitative structure activity relationship (QSAR)",
                "ExpoCast",
                "exposure"
            ],
            "contactPoint": {
                "fn": "John Wambaugh",
                "hasEmail": "mailto:wambaugh.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "SI_tables.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395223/SI_tables.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Supplemental_PhysChem_Submitted.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395223/Supplemental_PhysChem_Submitted.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-09-27",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.04.266"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Suspect Screening Analysis of Chemicals in Consumer Products",
            "description": "A suspect screening analysis method is presented to rapidly characterize chemicals in 100 consumer products -- whether they be formulations (shampoos, paints), articles (upholsteries, shower curtains), or foods (cereals) \u2013 and therefore supports broader efforts to prioritize chemicals based on potential human health risks. A two-dimensional gas chromatography-time of flight/mass spectrometry method was used to screen for chemicals in selected products. Analysis yielded 4270 unique chemical signatures across the products, with 1602 signatures tentatively identified using the National Institute of Standards and Technology 2008 spectral database. Chemical standards confirmed the presence of 119 compounds. Of the 1602 chemicals, 1404 were not present in a public database of known consumer product chemicals. \n\nThis dataset is associated with the following publication:\nPhillips, K., A. Yau, K. Favela, K. Isaacs, A. McEachran, C. Grulke, A. Richard, A. Williams, J. Sobus, R. Thomas, and J. Wambaugh. Suspect Screening Analysis of Chemicals in Consumer Products.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(5): 3125-3135, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1391810",
            "keyword": [
                "consumer products",
                "Gas chromatography-mass spectrometry (GC/MS)",
                "ExpoCast",
                "exposure"
            ],
            "contactPoint": {
                "fn": "John Wambaugh",
                "hasEmail": "mailto:wambaugh.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "suspect_screening_of_chemicals_in_consumer_products_SI_tables_v4_0.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1391810/suspect_screening_of_chemicals_in_consumer_products_SI_tables_v4_0.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "supporting_information_product_deformulation_v4_2.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1391810/supporting_information_product_deformulation_v4_2.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-09-15",
            "references": [
                "https://doi.org/10.1021/acs.est.7b04781"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset of Measurements of parameters controlling the emissions of organophoshpate flame retardants in indoor environments",
            "description": "The data presented in this data file is a product of a journal publication. The dataset contains measurements of mass transfer, material/air, and surface/air partition coefficients and emission concentrations of OPFRs in chambers and diffusion tubes. It also contains modeling data. \n\nThis dataset is associated with the following publication:\nLiang, Y., X. Liu, and M. Allen. Measurements of Parameters Controlling the Emissions of Organophosphate Flame Retardants in Indoor Environments.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA,  5821-5829, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1413225",
            "keyword": [
                "Semivolatile Organic Compounds (SVOCs)",
                "Organophosphorus Flame Retardants (OPFRs)",
                "Chamber testing",
                "Surface/air partition",
                "Material/air partition",
                "Material-phase diffusion"
            ],
            "contactPoint": {
                "fn": "Xiaoyu Liu",
                "hasEmail": "mailto:liu.xiaoyu@epa.gov"
            },
            "distribution": [
                {
                    "title": "XiaoyuLiu_A-zs87_Data Tables&Dictionary-20180427.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413225/XiaoyuLiu_A-zs87_Data%20Tables%26Dictionary-20180427.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-12-14",
            "references": [
                "https://doi.org/10.1021/acs.est.8b00224"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Model codes and run scripts developed for the addition of Four-Dimensional Data Assimilation (FDDA) to the Model for Prediction Across Scales - Atmosphere (MPAS-A)",
            "description": "Web link to a Zenodo repository containing Model codes, run scripts, the computational mesh definition file, and user instructions for the addition of Four-Dimensional Data Assimilation (FDDA) to the Model for Prediction Across Scales - Atmosphere (MPAS-A). \n\nThis dataset is associated with the following publication:\nBullock, R., H. Foroutan, R. Gilliam, and J. Herwehe. Adding four-dimensional data assimilation by analysis nudging to the Model for Prediction Across Scales \u2013 Atmosphere (version 4.0).   Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 11: 2897-2922, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434298",
            "keyword": [
                "data assimilation",
                "meteorological model",
                "air quality",
                "global"
            ],
            "contactPoint": {
                "fn": "Orren Bullock",
                "hasEmail": "mailto:bullock.russell@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://doi.org/10.5281/zenodo.1101204",
                    "accessURL": "https://doi.org/10.5281/zenodo.1101204"
                }
            ],
            "modified": "2017-12-11",
            "references": [
                "https://doi.org/10.5194/gmd-11-2897-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Clarksburg green infrastructure data",
            "description": "This data set includes 5-minute time series runoff and precipitation data of neighborhood catchments with a variety of stormwater control measures, and definition of individual precipitation-runoff events and associated runoff metrics. Also included are geospatial data that delineates the neighborhood catchments with their land use/land cover and stormwater infrastructure. \n\nThis dataset is associated with the following publication:\nWoznicki, S., K. Hondula, and T. Jarnagin. Effectiveness of landscape\u2010based green infrastructure for stormwater management in suburban catchments.   Hydrological Processes. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 32(15): 2346-2361, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1435427",
            "keyword": [
                "Green Infrastructure",
                "Stormwater control measures",
                "best management practices",
                "urbanization",
                "stormwater management",
                "Maryland",
                "USA"
            ],
            "contactPoint": {
                "fn": "S Jarnagin",
                "hasEmail": "mailto:jarnagin.taylor@epa.gov"
            },
            "distribution": [
                {
                    "title": "Readme_ClarksburgGeospatialData.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435427/Readme_ClarksburgGeospatialData.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "ClarksburgGeospatialData.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435427/ClarksburgGeospatialData.zip",
                    "mediaType": "application/zip"
                },
                {
                    "title": "Readme_ClarksburgMonitoringData.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435427/Readme_ClarksburgMonitoringData.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "ClarksburgMonitoringData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435427/ClarksburgMonitoringData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Readme_ClarksburgEventData.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435427/Readme_ClarksburgEventData.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "ClarksburgEventData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435427/ClarksburgEventData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-05-14",
            "references": [
                "https://doi.org/10.1002/hyp.13144"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Placeholder",
            "description": "Placeholder. This dataset is not publicly accessible because: This manuscript is based on literature review. No analysis was performed and there is no data associated with this product. It can be accessed through the following means: This manuscript is based on literature review. No analysis was performed and there is no data associated with this product. Format: This manuscript is based on literature review. No analysis was performed and there is no data associated with this product. \n\nThis dataset is associated with the following publication:\nBriski, E., F. Chan, J. Darling, V. Lauringson, H. MacIsaac, A. Zhan, and S. Bailey. Beyond propagule pressure: importance of selection during the transport stage of biological invasions.   FRONTIERS IN ECOLOGY AND THE ENVIRONMENT. Ecological Society of America, Ithaca, NY, USA, 16(6): 345-353, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1369042",
            "keyword": [
                "genetic diversity",
                "invasion process",
                "selection",
                "transport"
            ],
            "contactPoint": {
                "fn": "John Darling",
                "hasEmail": "mailto:darling.john@epa.gov"
            },
            "distribution": [],
            "modified": "2017-06-14",
            "references": [
                "https://doi.org/10.1002/fee.1820"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Human health impact of non-potable reuse of distributed wastewater and greywater treated by membrane bioreactors",
            "description": "This dataset contains simulated annual probabilities of infection for non-potable indoor use of greywater or wastewater treated by membrane bioreactors and chlorine disinfection.  The .zip file contains .csv files for each combination of source water and pathogen; see readme file (read me file.txt) for data dictionary and file naming convention. \n\nThis dataset is associated with the following publication:\nSchoen, M., M. Jahne, and J. Garland. Human health impact of non-potable reuse of distributed wastewater and greywater treated by membrane bioreactors (Microbial Risk Analysis).   Microbial Risk Analysis. Elsevier B.V., Amsterdam,  NETHERLANDS, 9: 72-81, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1420321",
            "keyword": [
                "greywater",
                "wastewater",
                "decentralized systems",
                "water reuse",
                "waterborne pathogens",
                "microbial risk assessment",
                "non-potable",
                "potable",
                "log reduction target",
                "QMRA",
                "pathogens"
            ],
            "contactPoint": {
                "fn": "Michael Jahne",
                "hasEmail": "mailto:jahne.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "csv files.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1420321/csv%20files.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-02-08",
            "references": [
                "https://doi.org/10.1016/j.mran.2018.01.003"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CAIRSENSE-Denver",
            "description": "The databases contain continuous sensor information as well as time stamped equivalent reference data. \n\nThis dataset is associated with the following publication:\nFeinberg, S., R. Williams, G. Hagler, J. Rickard, R. Brown, D. Garver, G. Harshfield, P. Stauffer, E. Mattson, R. Judge, and S. Garvey. Long-term evaluation of air sensor technology under ambient conditions in Denver, Colorado.   Atmospheric Measurement Techniques. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 11(8): 4605-4615, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1411532",
            "keyword": [
                "CAIRSENSE",
                "Sensors",
                "performance evaluations"
            ],
            "contactPoint": {
                "fn": "Ronald Williams",
                "hasEmail": "mailto:williams.ronald@epa.gov"
            },
            "distribution": [
                {
                    "title": "CAIRSENSE_DataFiles.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1411532/CAIRSENSE_DataFiles.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-11-01",
            "references": [
                "https://doi.org/10.5194/amt-11-4605-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1411532/documents/CAIRSENSE_DataDictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Evaluation of Formaldehyde Column Observations by Pandora Spectrometers",
            "description": "Data collected for this research provides information on mixing heights, surface and column formaldehyde during the KORUS-AQ field campaign and over two research sites in South Korea. \n\nThis dataset is associated with the following publication:\nSpinei, E., A. Whitehill, A. Fried, M. Tiefengraber, T. Knepp, S. Herndon, J. Herman, M. Muller, N. Abuhassan, A. Cede, D. Richter, J. Walega, J. Crawford, J. Szykman, L. Valin, D. Williams, R. Long, R. Swap, Y. Lee, N. Nowak, and B. Poche. The first evaluation of formaldehyde column observations by improved Pandora spectrometers during the KORUS-AQ field study.   Atmospheric Measurement Techniques. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 11(9): 4943-4961, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1431211",
            "keyword": [
                "formaldehyde columns",
                "satellite validation",
                "pandora",
                "KORUS-AQ",
                "surface formaldehyde",
                "mixing heights",
                "column formaldehyde"
            ],
            "contactPoint": {
                "fn": "James Szykman",
                "hasEmail": "mailto:szykman.jim@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www-air.larc.nasa.gov/missions/korus-aq/",
                    "accessURL": "https://www-air.larc.nasa.gov/missions/korus-aq/"
                }
            ],
            "modified": "2017-12-21",
            "references": [
                "https://doi.org/10.5194/amt-11-4943-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://www-air.larc.nasa.gov/missions/korus-aq/",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Metals removal from mine influenced water",
            "description": "The primary objective of this study was to evaluate the long-term effectiveness of a chitin (crushed crab shells) substrate compared to traditional ligneous (wood chips, hay, and manure) substrates on Zn, other metals (Al, Cu, Fe, Cd, Mn), and sulfate removal in MIW under anaerobic column bioreactor conditions. The secondary objective includes the evaluation of aeration and neutralization water pretreatment on the removal of the mentioned contaminants. \n\nThis dataset is associated with the following publication:\nPinto, P., S. Al-Abed, and J. McKernan. Comparison of the efficiency of chitinous and ligneous substrates in metal and sulfate removal from mining-influenced water.   JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 227(1): 321-328, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/10001",
            "keyword": [
                "acid mine drainage",
                "zinc",
                "manganese",
                "sulfate reducing bacteria",
                "anaerobic bioreactors",
                "sulfate reduction rate"
            ],
            "contactPoint": {
                "fn": "Souhail Al-Abed",
                "hasEmail": "mailto:al-abed.souhail@epa.gov"
            },
            "distribution": [
                {
                    "title": "Key metals mass balance.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/10001/Key%20metals%20mass%20balance.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Sulfur Mass Balance.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/10001/Sulfur%20Mass%20Balance.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Target metals in mol per liter Formosa Columns.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/10001/Target%20metals%20in%20mol%20per%20liter%20Formosa%20Columns.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-01-16",
            "references": [
                "https://doi.org/10.1016/j.jenvman.2018.08.113"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/10001/documents/Data%20dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Additional benefits of federal air quality rules: model estimates of controllable biogenic secondary organic aerosol",
            "description": "Dataset is a link to the publically available CMAQ v5.1 model code. The following update was also implemented: \nhttps://github.com/USEPA/CMAQ/blob/5.2/CCTM/docs/Release_Notes/AH3OPJ_IEPOX_update.md. \n\nThis dataset is associated with the following publication:\nCarlton, A., H. Pye, K. Baker, and C. Hennigan. Additional Benefits of Federal Air-Quality Rules: Model Estimates of Controllable Biogenic Secondary Organic Aerosol.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(16): 9254\u20139265, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1502526",
            "keyword": [
                "CMAQ",
                "SOA",
                "pm2.5",
                "PM2.5 air quality modeling",
                "Semivolatile Organic Compounds (SVOCs)",
                "Biogenic VOC"
            ],
            "contactPoint": {
                "fn": "Havala Pye",
                "hasEmail": "mailto:pye.havala@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://dx.doi.org/10.5281/zenodo.1079909",
                    "accessURL": "https://dx.doi.org/10.5281/zenodo.1079909"
                }
            ],
            "modified": "2017-01-01",
            "references": [
                "https://doi.org/10.1021/acs.est.8b01869"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Ballast water exchange and invasion risk posed by intra-coastal vessel traffic: An evaluation using high throughput sequencing  ",
            "description": "Dataset including all data for samples analyzed in Darling et al. 2018 Environmental Science & Technology. Includes OTU counts for all samples, taxonomic assignments for all OTUs, variables associated with vessels, and family-level counts across all vessels (used for indicator analysis). File also includes metadata describing all variables. \n\nThis dataset is associated with the following publication:\nDarling, J., J. Martinson, Y. Gong, S. Okum, E. Pilgrim, K. Pagenkopp Lohan, J. Carney, and G. Ruiz. Ballast Water Exchange and Invasion Risk Posed by Intracoastal Vessel Traffic: An Evaluation Using High Throughput Sequencing.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(17): 9926-9936, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1435417",
            "keyword": [
                "ballast water",
                "invasive species",
                "ballast water exchange",
                "high throughput sequencing",
                "metabarcoding"
            ],
            "contactPoint": {
                "fn": "John Darling",
                "hasEmail": "mailto:darling.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "ES&Tdata.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435417/ES%26Tdata.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-08-21",
            "references": [
                "https://doi.org/10.1021/acs.est.8b02108"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Plasma Standards",
            "description": "Digital droplet PCR fluorsence amplitude values from which plasmid copy concentrations of DNA standards were determined as described in D-EMMD-MEB-018-SOP-01and Journal article. Summary of  stability testing results also provided. \n\nThis dataset is associated with the following publication:\nSivaganesan, M., M. Varma, S. Siefring, and R. Haugland. Quantification of plasmid DNA standards for U.S. EPA fecal indicator bacteria qPCR methods by droplet digital PCR analysis.   JOURNAL OF MICROBIOLOGICAL METHODS. Elsevier Science Ltd, New York, NY, USA, 152: 135-142, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1500439",
            "keyword": [
                "digital droplet pcr",
                "dna standards",
                "draft method c",
                "epa methods 1609.1",
                "epa methods 1611.1",
                "qPCR"
            ],
            "contactPoint": {
                "fn": "Richard Haugland",
                "hasEmail": "mailto:haugland.rich@epa.gov"
            },
            "distribution": [
                {
                    "title": "Batch2_Data_Dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500439/Batch2_Data_Dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Batch2_stability_summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500439/Batch2_stability_summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Batch2_Tube1-5_Data_Dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500439/Batch2_Tube1-5_Data_Dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Batch2_Tube4_plasmid_amplitudes_summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500439/Batch2_Tube4_plasmid_amplitudes_summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Batch2_Tube3_plasmid_amplitudes_summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500439/Batch2_Tube3_plasmid_amplitudes_summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Batch2_Tube2_plasmid_amplitudes_summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500439/Batch2_Tube2_plasmid_amplitudes_summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Batch2_Tube1_plasmid_amplitudes_summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500439/Batch2_Tube1_plasmid_amplitudes_summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Batch2_Tube5_plasmid_amplitudes_summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500439/Batch2_Tube5_plasmid_amplitudes_summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-09-22",
            "references": [
                "https://doi.org/10.1016/j.mimet.2018.07.005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Evolution of the US energy system and related emissions under varying social and technological development paradigms Dataset",
            "description": "This data is associated with the manuscript \"Evolution of the US energy system and related emissions under varying social and technological development paradigms: Plausible scenarios for use in robust decision making\" which will be submitted to Environmental Science & Technology (ES&T). The research considers how the US energy system might evolve under four possible scenarios, including different technologies and different emission outcomes. \n\nThis dataset is associated with the following publication:\nBrown, K., T. Hottle, R. Bandyopadhyay, S. Babaee, R. Dodder, O. Kaplan, C. Lenox, and D. Loughlin. Evolution of the US energy system and related emissions under varying social and technological development paradigms: Plausible scenarios for use in robust decision making.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA,  8027-8038, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1411860",
            "keyword": [
                "scenarios",
                "scenario planning",
                "air quality",
                "MARKAL",
                "energy",
                "externality",
                "energy modeling"
            ],
            "contactPoint": {
                "fn": "Kristen Brown",
                "hasEmail": "mailto:brown.kristen@epa.gov"
            },
            "distribution": [
                {
                    "title": "PathwaysFutureScenarios_ScienceHubData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1411860/PathwaysFutureScenarios_ScienceHubData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-12-08",
            "references": [
                "https://doi.org/10.1021/acs.est.8b00575"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dry Dep Comp_Wu et al_2018",
            "description": "Datasets present results of comparisons of five commonly dry deposition algorithms for ozone and sulfur dioxide, including diurnal patterns in deposition velocities, leaf-level processes such as stomatal conductance, and sensitivity to use of modeled versus measured meteorology. \n\nThis dataset is associated with the following publication:\nWu, Z., D. Schwede, R. Vet, J. Walker, M. Shaw, R. Staebler, and L. Zhang. Evaluation and Intercomparison of Five North American Dry Deposition Algorithms at a Mixed Forest Site.   Journal of Advances in Modeling Earth Systems. John Wiley & Sons, Inc., Hoboken, NJ, USA, 10(7): 1571-1586, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1422888",
            "keyword": [
                "Dry Deposition",
                "model evaluation",
                "sulfur",
                "Ozone",
                "air-surface exchange",
                "nitrogen",
                "deposition",
                "bidirectional flux",
                "micrometeorology"
            ],
            "contactPoint": {
                "fn": "John Walker",
                "hasEmail": "mailto:walker.johnt@epa.gov"
            },
            "distribution": [
                {
                    "title": "Wu et al_DryDepModComp_2017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1422888/Wu%20et%20al_DryDepModComp_2017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-02-28",
            "references": [
                "https://doi.org/10.1029/2017ms001231"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "ScienceHub Supplement",
            "description": "The study created 45 3-year regional climate simulations by downscaling historical reanalysis data using the WRF model.  The simulations are not an ensemble, but rather are explorations of various nudging strategies to elucidate and recommend best practices.  The data available with this research effort are a suite of 2D fields of hourly data in WRF I/O API (built upon netCDF) for each simulation and for the full 3-year study period.  There are additional post-processed and statistical data that were generated and archived for this effort.  Metadata associated with each simulation are in standard netCDF format. \n\nThis dataset is associated with the following publication:\nSpero, T., C. Nolte, M. Mallard, and J. Bowden. A Maieutic Exploration of Nudging Strategies for Regional Climate Applications Using the WRF Model.   JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY. American Meteorological Society, Boston, MA, USA, 57: 1883-1906, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1500862",
            "keyword": [
                "WRF",
                "nudging",
                "regional climate modeling",
                "dynamical downscaling"
            ],
            "contactPoint": {
                "fn": "Tanya Spero",
                "hasEmail": "mailto:spero.tanya@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHub supplement.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500862/ScienceHub%20supplement.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2018-05-16",
            "references": [
                "https://doi.org/10.1175/jamc-d-17-0360.1"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CADETS Results by Site 050918",
            "description": "Measured, continuous, and intermittent Allegheny River conductivity by site. \n\nThis dataset is associated with the following publication:\nBrown, K., G. Norris, K. Kovalcik, A. Kamal, K. Patnode, and M. Landis. Signal Decomposition of Conductivity Sensor Measurements on the Allegheny River, Pennsylvania.   JOURNAL OF ENVIRONMENTAL ENGINEERING. American Society of Civil Engineers  (ASCE), Reston, VA, USA, 144(10): 04018103, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1500033",
            "keyword": [
                "Allegheny River",
                "conductivity",
                "Frequency",
                "water sensor"
            ],
            "contactPoint": {
                "fn": "Gary Norris",
                "hasEmail": "mailto:norris.gary@epa.gov"
            },
            "distribution": [
                {
                    "title": "CADETS Results by Site 050918.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500033/CADETS%20Results%20by%20Site%20050918.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-05-09",
            "references": [
                "https://doi.org/10.1061/(asce)ee.1943-7870.0001423"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Defining the Taxonomic Domain of Applicability for Mammalian-Based High-Throughput Screening Assays",
            "description": "Final Data SeqAPASS v3.0.zip contains datasets from Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool versions 3.0 for all 497 proteins evaluated using Level 1 (primary amino acid sequence comparisons) and Level 2 (functional domain(s) sequence comparisons) to understand conservation of HTS targets across species. Each folder is labeled by the protein accession (identification number and SeqAPASS version), with subfolders containing Level 1 and Level 2 output from the SeqAPASS tool.\nSeqAPASS v3.0 Data in Assay Groups.zip Contains all SeqAPASS data sorted by ToxCast Assay Group (as described in manuscript materials and methods). The original SeqAPASS data for each assay group are found in the folders titled Cell Adhesion, Cytochrome P450, Cytokine, DNA Binding, Esterase, G protein-coupled receptor, Growth Factor, Hydrolase, Ion Channel, Kinase, Lyase, Methyltransferase, Nuclear Receptor, Oxidoreductase, Phophatase, Protease, Protease Inhibitor, and Transporter. The Data_L1_Output folders and Data_L2_Output folders provide summaries of the Level 1 and Level 2 data comparing across datasets (See manuscript Supplemental Data, Legend for further details). \n\nThis dataset is associated with the following publication:\nLaLone, C., D. Villeneuve, J. Doering, B. Blackwell, T. Transue, C. Simmons, J. Swintek, S. Degitz, A. Williams, and G. Ankley. Defining the taxonomic domain of applicability for mammalian-based high-throughput screening assays..   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(23): 13960-13971, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1432209",
            "keyword": [
                "high-throughput screening",
                "Endocrine Disruptor Screening Program",
                "Thyroid axis",
                "steroidogenesis",
                "adverse outcome pathway",
                "ecotoxicology",
                "honey bee",
                "cross-species extrapolation",
                "screening and prioritization",
                "networks"
            ],
            "contactPoint": {
                "fn": "Carlie Lalone",
                "hasEmail": "mailto:lalone.carlie@epa.gov"
            },
            "distribution": [
                {
                    "title": "Final Data SeqAPASS v3.0.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1432209/Final%20Data%20SeqAPASS%20v3.0.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "SeqAPASS v3.0 Data in Assay Groups.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1432209/SeqAPASS%20v3.0%20Data%20in%20Assay%20Groups.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-04-09",
            "references": [
                "https://doi.org/10.23719/1432209"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1432209/documents/Data%20Dictionary%232.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Comparative Toxicity of Smoldering Versus Flaming Emissions from Various Biomass Fuels",
            "description": "This dataset includes physico-chemical characteristics of biomass smoke of five different fuels (red oak, peat, pine needles, pine, and eucalyptus) generated from a tube furnace system at two different combustion phases (smoldering and flaming) and also provides two toxicological outcomes (lung toxicity in mice and mutagenicity in Salmonella) associated with exposures to the biomass smoke PM collected by a cryo-trap system. \n\nThis dataset is associated with the following publication:\nKim, Y.H., S. Warren, T. Krantz, C. King, R. Jaskot, W.T. Preston, B. George, M. Hays, M. Landis, M. Higuchi, D. DeMarini, and I. Gilmour. Mutagenicity and Lung Toxicity of Smoldering Versus Flaming Emissions from Various Biomass Fuels: Implications for Health Effects from Wildland Fires.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 126(1): 1, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1374721",
            "keyword": [
                "Mutagenicity",
                "particulate matter (PM)",
                "Biomass smoke",
                "emission factor",
                "Lung toxicity",
                "Wildfires",
                "particulate matter"
            ],
            "contactPoint": {
                "fn": "Matthew Gilmour",
                "hasEmail": "mailto:gilmour.ian@epa.gov"
            },
            "distribution": [
                {
                    "title": "Research Data_A-tb3d.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374721/Research%20Data_A-tb3d.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-10",
            "references": [
                "https://doi.org/10.1289/ehp2200"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1374721/documents/Dictionary_A-tb3d.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Nitrogen and nitrogen isotope data for wheat and barley exposed to CeO2 nanoparticles",
            "description": "The effects of cerium oxide nanoparticles (CeO2-NPs) on 15N/14N ratio (\u03b415N) in wheat and barley were investigated.  Seedlings were exposed to 0 and 500 mg CeO2-NPs/L (Ce-0 and Ce-500, respectively) in hydroponic suspension supplied with NH4NO3, NH4+, or NO3-.  N uptake and \u03b415N discrimination (i.e. differences in \u03b415N of plant and \u03b415N of N source) were measured.  Results showed that N content and 15N abundance decreased in wheat but increased in barley.  Ce-500 only induced whole-plant \u03b415N discrimination (-1.48\u2030, P \u2264 0.10) with a simultaneous decrease (P \u2264 0.05) in whole-plant \u03b415N (-3.24\u2030) compared to Ce-0 (-2.74\u2030) in wheat in NH4+.  Ce-500 decreased (P \u2264 0.01) root \u03b415N of wheat in NH4NO3 and NH4+ (3.23 and -2.25\u2030, respectively) compared to Ce-0 (4.96 and -1.27\u2030, respectively), but increased (P \u2264 0.05) root \u03b415N of wheat in NO3- (3.27\u2030) compared to Ce-0 (2.60\u2030).  Synchrotron micro-XRF revealed the presence of CeO2-NPs in shoots of wheat and barley regardless of N source.  Although the longer-term consequences of CeO2-NP exposure on N uptake and metabolism are unknown, the results clearly show the potential for ENMs to interfere with plant metabolism of critical plant nutrients such as N even when toxicity is not observed. \n\nThis dataset is associated with the following publication:\nRico, C.M., M. Johnson, M.A. Marcus, and C.P. Andersen. Shifts in N and \u03b415N in wheat and barley exposed to cerium oxide nanoparticles.   NanoImpact. Elsevier B.V., Amsterdam,  NETHERLANDS, 11: 156-163, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1411219",
            "keyword": [
                "Synchrotron micro XRF",
                "ammonium nitrate",
                "intergenerational effects",
                "isotope",
                "isotopic discrimination",
                "nitrogen",
                "engineered nanomaterials (ENMs)"
            ],
            "contactPoint": {
                "fn": "Christian Andersen",
                "hasEmail": "mailto:andersen.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "hydroponics NHNO barley Isotope - data repository for Chris.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1411219/hydroponics%20NHNO%20barley%20Isotope%20-%20data%20repository%20for%20Chris.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "hydroponics NO wheat Isotope - data repository for Chris.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1411219/hydroponics%20NO%20wheat%20Isotope%20-%20data%20repository%20for%20Chris.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "hydroponics NHNO wheat Isotope - data repository for Chris.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1411219/hydroponics%20NHNO%20wheat%20Isotope%20-%20data%20repository%20for%20Chris.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "hydroponics NO barley Isotope - data repository for Chris.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1411219/hydroponics%20NO%20barley%20Isotope%20-%20data%20repository%20for%20Chris.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "hydroponics NH barley Isotope - data repository for Chris.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1411219/hydroponics%20NH%20barley%20Isotope%20-%20data%20repository%20for%20Chris.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "hydroponics NH wheat Isotope - data repository for Chris.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1411219/hydroponics%20NH%20wheat%20Isotope%20-%20data%20repository%20for%20Chris.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-03-15",
            "references": [
                "https://doi.org/10.1016/j.impact.2018.08.003"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Mass-spectrometric identification of cyclic phenone metabolites produced by rainbow trout liver slices ",
            "description": "Dataset  consists of 2 main files as follows: \n1. All main and Supplemental MS final figures used for manuscript preparation for better viewing (pdf file). Figures are copies of raw or analyzed data directly from the mass spectrometers experimental files generated during research.   Explanation of figures is provided in manuscript's text \n2. Xcel file (Mass calculator CPK metabolites original), containing a significant amount of  MS raw data obtained during the research for parent chemicals and metabolites. Emphasis was provided to the analyses of CPK metabolites. The file contains an Index page stating the content of each sheet. Because CPK metabolites were labelled differently as the research progressed, a Legend with the different labeling of each metabolite is presented on each sheet. \n\nThis dataset is associated with the following publication:\nKolanczyk, R., J. Serrano, M. Tapper, and P. Schmieder. A comparison of fish pesticide metabolic pathways with those of the rat and goat.   REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 94: 124-143, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1502623",
            "keyword": [
                "cyclic phenones",
                "in vitro assays",
                "endocrine disruption",
                "fish liver slices",
                "estrogen receptor",
                "Vtg gene expression",
                "Metabolism",
                "GC-MS",
                "LC-MS/MS",
                "LC-ToF-MS"
            ],
            "contactPoint": {
                "fn": "Jose Serrano",
                "hasEmail": "mailto:serrano.jose@epa.gov"
            },
            "distribution": [
                {
                    "title": "Publication Metabolite Identification  Figures.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502623/Publication%20Metabolite%20Identification%20%20Figures.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "mass calculator cpk metabolites Original.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502623/mass%20calculator%20cpk%20metabolites%20Original.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-09-12",
            "references": [
                "https://doi.org/10.1016/j.yrtph.2018.01.019"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "NWCA Enzyme Decomposition Model",
            "description": "Dataset contains wetland site information, microbial respiration and ecoenzyme data, enzyme decomposition model, and the program file to run the data analyses. \n\nThis dataset is associated with the following publication:\nHill , B., C. Elonen , L. Seifert, A. May, and E. Tarquinio. Microbial ecoenzyme stoichiometry, nutrient limitation, and organic matter decomposition in wetlands of the conterminous United States.   Wetlands Ecology and Management. Springer Science and Business Media B.V;Formerly Kluwer Academic Publishers B.V.,   GERMANY, 26: 425-439, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1390085",
            "keyword": [
                "climate",
                "decomposition",
                "ecoenzymes",
                "land cover",
                "soil",
                "stoichiometry",
                "wetlands"
            ],
            "contactPoint": {
                "fn": "Brian Hill",
                "hasEmail": "mailto:hill.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "NWCA_EDM.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390085/NWCA_EDM.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "NWCA EDM Program File.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390085/NWCA%20EDM%20Program%20File.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-02-29",
            "references": [
                "https://doi.org/10.1007/s11273-017-9584-5"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1390085/documents/NWCA%20EDM%20Data%20Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Adrenergic and glucocorticoid receptor antagonists reduce ozone-induced lung injury and inflammation",
            "description": "This data set contains one Excel file. In this file are all the data pertaining to the effects of propranolol and mifepristone on ozone induced lung injury and inflammation . The different tabs of the spreadsheet pertain to each figure found in the manuscript. \n\nThis dataset is associated with the following publication:\nHenriquez, A., S. Snow, M. Schladweiler, C. Miller, J. Dye, A. Ledbetter, J. Richards, K. Mauge-Lewis, M. McGee, and U. Kodavanti. Adrenergic and glucocorticoid receptor antagonists reduce ozone-induced lung injury and inflammation.   TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 339: 161-171, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1375329",
            "keyword": [
                "Stress hormones",
                "glucocorticoid receptor agonist",
                "adrenergic receptor agonist",
                "Ozone",
                "lung injury",
                "lung inflammation"
            ],
            "contactPoint": {
                "fn": "Urmila Kodavanti",
                "hasEmail": "mailto:kodavanti.urmila@epa.gov"
            },
            "distribution": [
                {
                    "title": "Henriquez 2017 Manuscript for AJP - Data for ScienceHub - Kodavanti.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375329/Henriquez%202017%20Manuscript%20for%20AJP%20-%20Data%20for%20ScienceHub%20-%20Kodavanti.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-14",
            "references": [
                "https://doi.org/10.1016/j.taap.2017.12.006"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "DEPS sulfate measurements",
            "description": "data consist of measurements of outdoor and personal sulfate measurements. \n\nThis dataset is associated with the following publication:\nBreen, M., Y. Xu, A. Schneider, R. Williams, and R. Devlin. Modeling individual exposures to ambient PM2.5 in the diabetes and the environment panel study (DEPS).   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 626: 807-816, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407621",
            "keyword": [
                "Building infiltration of air pollutants",
                "Fine Particulate Matter",
                "Exposure modeling",
                "health study"
            ],
            "contactPoint": {
                "fn": "Michael Breen",
                "hasEmail": "mailto:breen.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "specialxrfSulfur-feb-20-08_data_dic.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407621/specialxrfSulfur-feb-20-08_data_dic.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-09-07",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.01.139"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Three-dimensional WRF and CMAQ 2-km simulation output for California for January/February 2013",
            "description": "These data include three-dimensional meteorological (WRF) and air quality (CMAQ) model output for a 2-km domain covering the San Joaquin Valley (SJV) of California for January and February of 2013. The WRF and CMAQ parameters used in the analysis presented in the research effort are listed in the attached spreadsheet. The WRF/CMAQ data themselves are located on EPA's asm tape archive in the directories below. These data are available upon request from the authors, specifically K. Wyat Appel (appel.wyat@epa.gov).\n\n/asm/MOD3EVAL/DISCOVERAQ/SJV/2km_Meso/WRF\n/asm/MOD3EVAL/DISCOVERAQ/SJV/2km_Meso/CMAQ. \n\nThis dataset is associated with the following publication:\nFriberg, M., R. Kahn, J. Limbacher, W. Appel, and J. Mulholland. Constraining chemical transport PM2.5 modeling outputs using surface monitor measurements and satellite retrievals: application over the San Joaquin Valley.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 18: 12891-12913, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1502511",
            "keyword": [
                "model evaluation",
                "PM2.5 air quality modeling",
                "air quality modeling",
                "Satellite Air Quality"
            ],
            "contactPoint": {
                "fn": "Keith Appel",
                "hasEmail": "mailto:appel.wyat@epa.gov"
            },
            "distribution": [
                {
                    "title": "WRFCMAQ_v502_DISCOVER-AQ_CA_2km_variable_list_used_MFRIBERG.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502511/WRFCMAQ_v502_DISCOVER-AQ_CA_2km_variable_list_used_MFRIBERG.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-05-16",
            "references": [
                "https://doi.org/10.5194/acp-18-12891-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1502511/documents/WyatAppel_A-f7mf_Data_Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Great Sippewissett Marsh 2016 Data",
            "description": "Data in this spreadsheet include methane, carbon dioxide, and nitrous oxide fluxes; soil pH; surface and subsurface soil temperature; and surface elevation relative to mean high water for study plots at Great Sippewissett Marsh collected in July, August, September and October 2016. \n\nThis dataset is associated with the following publication:\nMartin, R., C. Wigand, E. Elmstrom, J. Lloret, and I. Valiela. Long-term nutrient addition increases respiration and nitrous oxide emissions in a New England salt marsh.   Ecology and Evolution. Wiley-Blackwell Publishing, Hoboken, NJ, USA, 8(10): 4958\u20134966, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1369029",
            "keyword": [
                "carbon dioxide",
                "Methane",
                "nitrous oxide",
                "nitrogen",
                "Salt marsh",
                "cape cod"
            ],
            "contactPoint": {
                "fn": "Rose Martin",
                "hasEmail": "mailto:martin.rose@epa.gov"
            },
            "distribution": [
                {
                    "title": "SippewissettSciHub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1369029/SippewissettSciHub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-10",
            "references": [
                "https://doi.org/10.1002/ece3.3955"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Soil organic matter and amphibian exposure dataset",
            "description": "Dataset containing experimental data and R scripts used for data analyses. \n\nThis dataset is associated with the following publication:\nVan Meter, R., D. Glinski, M. Henderson , and T. Purucker. Soil organic matter content effects on dermal pesticide bioconcentration in American toads (Bufo americanus)..   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 35(11): 2734\u20132741, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1500922",
            "keyword": [
                "amphibians",
                "dermal exposure",
                "soil organic matter",
                "pesticides"
            ],
            "contactPoint": {
                "fn": "Steven Purucker",
                "hasEmail": "mailto:purucker.tom@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://github.com/puruckertom/vanmeteretal2016_etc_amphibian_exposure_som",
                    "accessURL": "https://github.com/puruckertom/vanmeteretal2016_etc_amphibian_exposure_som"
                }
            ],
            "modified": "2018-06-04",
            "references": [
                "https://doi.org/10.1002/etc.3439"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Effect of contolled and spontaneous breathing on exhaled breath condensate characteristics",
            "description": "The datasets provide physicochemical endpoint values (volumes, pH) for exhaled breath condensate collected with spontaneous breathing and \"controlled\" breathing patterns. The controlled breathing was enabled with audiovisual signals with a new instrument. The variability of the endpoint values was analyzed. \n\nThis dataset is associated with the following publication:\nWinters, B., J. Pleil, M. Angrish, M. Stiegel, T. Risby, and M. Madden. Standardization of the collection of exhaled breath condensate and exhaled breath aerosol using a feedback regulated sampling device.   Journal of Breath Research. Institute of Physics Publishing, Bristol,  UK, 11(4): 1, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1503038",
            "keyword": [
                "cellular volatiles",
                "high-throughput in vitro screening assay",
                "cytochromeP450"
            ],
            "contactPoint": {
                "fn": "Michael Madden",
                "hasEmail": "mailto:madden.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Winters 2017 SciHub data figs 3_4_5.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503038/Winters%202017%20SciHub%20data%20figs%203_4_5.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-18",
            "references": [
                "https://doi.org/10.1088/1752-7163/aa8bbc"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Ozone and IUGR CMiller",
            "description": "Data related to the effects of peri-implantation ozone exposure on maternal and fetal health outcomes at the end of gestation. \n\nThis dataset is associated with the following publication:\nMiller, C., J. Dye, A. Ledbetter, M. Schladweiler, J. Richards, S. Snow, C. Wood, A. Henriquez, L. Thompson, A. Farraj, M. Hazari, and U. Kodavanti. Uterine Artery Flow and Offspring Growth in Long-Evans Rats following Maternal Exposure to Ozone during Implantation.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 125(12): 127005, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1375338",
            "keyword": [
                "Ozone",
                "pregnancy",
                "fetal growth assessment",
                "preeclampsia"
            ],
            "contactPoint": {
                "fn": "Colette Miller",
                "hasEmail": "mailto:miller.colette@epa.gov"
            },
            "distribution": [
                {
                    "title": "O3 and IUGR CMiller.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375338/O3%20and%20IUGR%20CMiller.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-14",
            "references": [
                "https://doi.org/10.1289/ehp2019"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Wetland Model Nitrogen and Carbon Data (Kent Island, MD, May 1995 - May 1997)",
            "description": "This data are composed of precipitation, wetland water depth, volumetric soil moisture, nitrogen and carbon concentrations measured into and out of a wetland, and model computed soil moisture content as well as nitrogen and carbon loading from the wetland. The wetland is a restored treatment wetland, located in Kent Island, MD. \n\nThis dataset is associated with the following publication:\nSharifi, A., M. Hantush, and L. Kalin. Modeling Nitrogen and Carbon Dynamics in Wetland Soils and Water Using Mechanistic Wetland Model.  Rao S. Govindaraju  Journal of Hydrologic Engineering. American Society of Civil Engineers  (ASCE), Reston, VA, USA, 22(1): 1-18, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1502641",
            "keyword": [
                "wetlands",
                "process-based model",
                "nitrogen",
                "carbon",
                "phosphorus",
                "wetland hydrology",
                "Richards Equation",
                "unsaturated soil",
                "Aerobic",
                "anaerobic",
                "Uncertainty Estimation",
                "Bayesian statistics",
                "sensitivity analysis",
                "GLUE",
                "Monte Carlo method"
            ],
            "contactPoint": {
                "fn": "Mohamed Hantush",
                "hasEmail": "mailto:hantush.mohamed@epa.gov"
            },
            "distribution": [
                {
                    "title": "Mechansitic Wetland Model_unsaturated condition.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502641/Mechansitic%20Wetland%20Model_unsaturated%20condition.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-02-01",
            "references": [
                "https://doi.org/10.1061/(asce)he.1943-5584.0001441"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Seasonal patterns of bole water content in old growth Douglas-fir",
            "description": "Supporting data for figures and tables in publication. See Readme file. \n\nThis dataset is associated with the following publication:\nBeedlow, P., R. Waschmann, E. Lee, and D.T. Tingey. Seasonal patterns of bole water content in old growth Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco).   AGRICULTURAL AND FOREST METEOROLOGY. Elsevier Science Ltd, New York, NY, USA, 242: 109-119, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1503045",
            "keyword": [
                "climate change",
                "dendrochronology",
                "Douglas-fir",
                "Pacific Decadal Oscillation",
                "Pacific Northwest",
                "Swiss needle cast"
            ],
            "contactPoint": {
                "fn": "E. Lee",
                "hasEmail": "mailto:lee.ehenry@epa.gov"
            },
            "distribution": [
                {
                    "title": "Readme.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503045/Readme.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "2004 - 2014 SGF(O) & SGF(Y) rBAI, RWC Bole and ASW Data.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503045/2004%20-%202014%20SGF%28O%29%20%26%20SGF%28Y%29%20rBAI%2C%20RWC%20Bole%20and%20ASW%20Data.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "2004 - YTD SGF(O) & SGF(Y) Theta Probe Hourly Data, w_ Climate Data.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503045/2004%20-%20YTD%20SGF%28O%29%20%26%20SGF%28Y%29%20Theta%20Probe%20Hourly%20Data%2C%20w_%20Climate%20Data.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Coefficient Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503045/Coefficient%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Smoothed RWC, rBAI, Climate.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503045/Smoothed%20RWC%2C%20rBAI%2C%20Climate.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Tissue Moisture, THETA_PROBE_TREES_SG_2004 - 2015.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503045/Tissue%20Moisture%2C%20THETA_PROBE_TREES_SG_2004%20-%202015.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-09-24",
            "references": [
                "https://doi.org/10.1016/j.agrformet.2017.04.017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Varroapop sensitivity analysis scripts and output",
            "description": "Code repository for scripts and model output associated with sensitivity analysis of the VarroaPop honeybee hive simulation model. \n\nThis dataset is associated with the following publication:\nKuan, C., G. DeGrandi-Hoffman, R. Curry, K. Garber, A. Kanarek, M. Snyder, K. Wolfe, and T. Purucker. Sensitivity analyses for simulating pesticide impacts on honey bee colonies.   ENVIRONMENTAL MODELLING AND SOFTWARE. Elsevier Science Ltd, New York, NY, USA, 376: 15-27, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1500920",
            "keyword": [
                "pollinator",
                "honey bee",
                "sensitivity analysis",
                "colony population model",
                "pesticides"
            ],
            "contactPoint": {
                "fn": "Steven Purucker",
                "hasEmail": "mailto:purucker.tom@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://github.com/puruckertom/kuanetal_varroapop_wrapper",
                    "accessURL": "https://github.com/puruckertom/kuanetal_varroapop_wrapper"
                }
            ],
            "modified": "2018-06-04",
            "references": [
                "https://doi.org/10.1016/j.ecolmodel.2018.02.010"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "HTAP_v2.2: a mosaic of regional and global emission gridmaps for 2008 and 2010 to study hemispheric transport of air pollution.",
            "description": "This dataset provides the EPA portion of a compilation of different regional gridded inventories, including  data from Environment Canada for Canada, the European Monitoring and Evaluation Programme (EMEP) and Netherlands Organisation for Applied Scientific Research (TNO) for Europe, and the Model Inter-comparison Study in Asia (MICS-Asia)\u2019s for China, India and other Asian countries, and  gap-filled emission gridmaps of the Emissions Database for Global Atmospheric Research (EDGARv4.3) for the rest of the world (mainly South-America, Africa, Russia and Oceania).\nThe EPA data is included as netCDF formatted datasets at 0.1\u00ba \u00d7 0.1\u00ba resolution for 2010. This was the \u201craw\u201d data that was incorporated into the global mosaics.\nEmissions from seven main categories of human activities (power, industry, residential, agriculture, ground transport, aviation and shipping) were estimated and spatially distributed on a common grid of 0.1\u00ba \u00d7 0.1\u00ba longitude-latitude, to yield monthly, global, sector-specific gridmaps for each substance and year.\nEmission summaries from the supplemental information in the published journal article are also included. \n\nThis dataset is associated with the following publication:\nJanssens-Maenhout, G., M. Crippa, D. Guizzardi, F. Dentener, M. Muntean, G. Pouliot, T. Keating, Q. Zhang, J. Kurokawa, R. Wankmuller, H. Denier van der Gon, J.J.P. Kuenen, Z. Klimont, G. Frost, S. Darras, B. Koffi, and M. Li. HTAP_v2.2: a mosaic of regional and global emission grid maps for 2008 and 2010 to study hemispheric transport of air pollution.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 15(19): 11411-11432, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1502632",
            "keyword": [
                "HTAP",
                "Global Emission Inventory",
                "CMAQ",
                "air quality modeling",
                "model evaluation"
            ],
            "contactPoint": {
                "fn": "Keith Appel",
                "hasEmail": "mailto:appel.wyat@epa.gov"
            },
            "distribution": [
                {
                    "title": "Pouliot_A-k0pp_Dataset_20180829.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502632/Pouliot_A-k0pp_Dataset_20180829.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Pouliot_A-k0pp_Dataset_20180910.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502632/Pouliot_A-k0pp_Dataset_20180910.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2013-08-06",
            "references": [
                "https://doi.org/10.5194/acp-15-11411-2015"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Role of TRPA1 in acrolein cardiac effects in mice",
            "description": "Cardiac and ventilatory physiological data for mice exposed to acrolein. \n\nThis dataset is associated with the following publication:\nKurhanewicz, N., A. Ledbetter, A. Farraj, and M. Hazari. TRPA1 mediates the cardiac effects of acrolein through parasympathetic dominance but also sympathetic modulation in mice.   TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 347: 104-114, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407607",
            "keyword": [
                "heart rate variability",
                "ventilatory function",
                "autonomic",
                "air pollution",
                "MICE",
                "reflex",
                "TRPA1",
                "cardiovascular"
            ],
            "contactPoint": {
                "fn": "Mehdi Hazari",
                "hasEmail": "mailto:hazari.mehdi@epa.gov"
            },
            "distribution": [
                {
                    "title": "Autonomic redo HRV.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407607/Autonomic%20redo%20HRV.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Autonomic redo HRV_KO.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407607/Autonomic%20redo%20HRV_KO.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Autonomic Redo Ventilatory Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407607/Autonomic%20Redo%20Ventilatory%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Autonomic Redo_effective dose.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407607/Autonomic%20Redo_effective%20dose.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "HRV_compiled_first drug administration.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407607/HRV_compiled_first%20drug%20administration.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "HRV Redo BAL and GPX data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407607/HRV%20Redo%20BAL%20and%20GPX%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-01-31",
            "references": [
                "https://doi.org/10.1016/j.taap.2018.03.027"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Methane Transect Dataset",
            "description": "This project area \u201cOTM 33 Mobile Emission Measurements\u201d covers research on remote emissions quantification with the various forms of mobile monitoring approaches. There will be multiple data sets included in this project. The metadata and data dictionaries are included with each data set. The data sets with metadata and data dictionaries are as follows:\r\n\r\nMethane Transect data Set:   The dataset contains mobile methane concentration measurements acquired at 10 samples per second data acquisition rate, collected while driving along transects downwind of a methane source.  The data consists of GPS coordinates, methane concetrion data and transect indicators.  The controlled methane release experiment was conducted on May 15, 2010 in Durham, North Carolina, where three passes were made for the one CR experiment and the point-source release rate was controlled at S = 0.6 g/s. Additionally, the dataset contains four field studies conducted in Colorado on four separate days in July 2010, with the number of passes for each study ranging from two to five. \n\nThis dataset is associated with the following publication:\nAlbertson, J., T. Foster-Wittig, A. Swingler, G. Foderaro, S. Ferrari, S. Amin, M. Modrak, H. Brantley , and E. Thoma. A Mobile Sensing Approach for Regional Surveillance of Fugitive Methane Emissions in Oil and Gas Production.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(5): 2487-2497, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1390071",
            "keyword": [
                "OTM 33",
                "Mobile Measurements",
                "GMAP",
                "Methane",
                "Fugitive Emissions"
            ],
            "contactPoint": {
                "fn": "Eben Thoma",
                "hasEmail": "mailto:thoma.eben@epa.gov"
            },
            "distribution": [
                {
                    "title": "Methane Transect Data Set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390071/Methane%20Transect%20Data%20Set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-04-27",
            "references": [
                "https://doi.org/10.1021/acs.est.5b05059"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Li et al nitrification inhibition review",
            "description": "Li et al nitrification inhibition review. \n\nThis dataset is associated with the following publication:\nKapoor, V., X. Li, C. Impellitteri , K. Chandran, and J. Santodomingo. Use of Functional Gene Expression and Respirometry to Study Wastewater Nitrification Activity after Exposure to Low Doses of Copper.   ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH. Ecomed Verlagsgesellschaft AG, Landsberg,  GERMANY, 23(7): 6443-6450, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390094",
            "keyword": [
                "nitrification",
                "RNA"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [
                {
                    "title": "qPCR_results Ni Cd Zn Pb.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390094/qPCR_results%20Ni%20Cd%20Zn%20Pb.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Nitrification_Inhibition-10_Inorganics.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390094/Nitrification_Inhibition-10_Inorganics.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-09-01",
            "references": [
                "https://doi.org/10.1007/s11356-015-5843-2"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The First Acid Ionization Constant of Cyanuric Acid from 5 to 35 \u00b0C",
            "description": "No data set is provided. This dataset is not publicly accessible because: All the data is contained in the manuscript and supplementary information. It can be accessed through the following means: All the data is contained in the manuscript and supplementary information. Format: All the data is contained in the manuscript and supplementary information. \n\nThis dataset is associated with the following publication:\nWahman, D. First Acid Ionization Constant of the Drinking Water Relevant Chemical Cyanuric Acid from 5 to 35 \u00b0C.   Environmental Science: Water Research & Technology. Royal Society of Chemistry, Cambridge,  UK, 4: 1522-1530, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1412697",
            "keyword": [
                "cyanuric acid"
            ],
            "contactPoint": {
                "fn": "David Wahman",
                "hasEmail": "mailto:wahman.david@epa.gov"
            },
            "distribution": [],
            "modified": "2017-12-12",
            "references": [
                "https://doi.org/10.1039/c8ew00431e"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "PM and levoglucosan data",
            "description": "These are GC-MS data for producing the levoglucosan plot, black carbon data from an aethalometer, time series data of wind speed and normalized PM concentrations. As well as certain particle number and CO concentration data deltas. \n\nThis dataset is associated with the following publication:\nKimbrough , S., M. Hays , B. Preston, D. Vallero , and G. Hagler. Episodic Impacts from California Wildfires Identified in Las Vegas Near-Road Air Quality Monitoring.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(1): 18-24, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390103",
            "keyword": [
                "levoglucosan",
                "PM",
                "BC",
                "CO",
                "wildfire",
                "near-road",
                "ambient air",
                "air quality"
            ],
            "contactPoint": {
                "fn": "Evelyn Kimbrough",
                "hasEmail": "mailto:kimbrough.sue@epa.gov"
            },
            "distribution": [
                {
                    "title": "PM10_data_matlab_stepplot1.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390103/PM10_data_matlab_stepplot1.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Lg_data_matlab_stepplot2.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390103/Lg_data_matlab_stepplot2.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2015-08-20",
            "references": [
                "https://doi.org/10.1021/acs.est.5b05038"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data used and links to data and metadata",
            "description": "The provided link will take users to all the data and metadata used in this project. \n\nThis dataset is associated with the following publication:\nAngradi, T., P. Ringold, and K. Hall. Water clarity measures as indicators of recreational benefits provided by U.S. lakes: Swimming and aesthetics.   ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 93: 1005-1019, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1434903",
            "keyword": [
                "EPA National Lake Assessment"
            ],
            "contactPoint": {
                "fn": "Theodore Angradi",
                "hasEmail": "mailto:angradi.theodore@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys",
                    "accessURL": "https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys"
                }
            ],
            "modified": "2018-04-27",
            "references": [
                "https://doi.org/10.1016/j.ecolind.2018.06.001"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Results for calcification and ingestion and retention rates of microbeads and microplastics. ",
            "description": "Data is for three experiments. The first experiment examined calcification effects of ingested microbeads. The second experiment observed ingestion rates of four size classes of microbeads and how long they were retained. The third experiment observed and compared ingestion rates of one microbead size class and microfibers 3-5mm in length. \n\nThis dataset is associated with the following publication:\nHankins, C., A. Duffy, and K. Drisco. Scleractinian coral microplastic ingestion: Potential calcification effects, size limits, and retention.   MARINE POLLUTION BULLETIN. Elsevier Science Ltd, New York, NY, USA, 135: 587-593, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1435612",
            "keyword": [
                "coral",
                "microplastic",
                "ingestion",
                "Retention"
            ],
            "contactPoint": {
                "fn": "Cheryl Hankins",
                "hasEmail": "mailto:hankins.cheryl@epa.gov"
            },
            "distribution": [
                {
                    "title": "AllData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435612/AllData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-05-02",
            "references": [
                "https://doi.org/10.1016/j.marpolbul.2018.07.067"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1435612/documents/DataDictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Assessing the Social and Environmental Costs of Institutions Nitrogen Footprints",
            "description": "This dataset allowed estimates the damage costs associated with the institutional nitrogen (N) footprint and explores how this information could be used to create more sustainable institutions. Potential damages associated with the release of nitrogen oxides (NOx), ammonia (NH3), and nitrous oxide (N2O) to air and release of nitrogen to water were estimated\nusing existing values and a cost per unit of nitrogen approach. These damage cost values were then applied to two universities. Annual potential damage costs to human health, agriculture, and natural ecosystems associated with the N footprint of institutions were $11.0 million (2014) at the University of Virginia (UVA) and $3.04 million at the University of New Hampshire (UNH). Costs associated with the release of nitrogen oxides to human health, in particular the use of coal-derived energy, were the largest component of damage at UVA. At UNH the energy N footprint is much lower because of a landfill cogeneration source, and thus the majority of damages were associated with food production. Annual damages associated with release of nitrogen from food production were very similar\nat the two universities ($1.80 million vs. $1.66 million at UVA and UNH, respectively). These damages also have implications for the extent and scale at which the damages are felt. For example, impacts to human health from energy and transportation are generally larger near the power plants and roads, while impacts from food production can be distant from the campus. Making this information available to institutions and communities can improve their understanding of the damages associated with the different nitrogen forms and sources, and inform decisions about\nnitrogen reduction strategies. \n\nThis dataset is associated with the following publication:\nCompton, J., A. Leach, E. Castner, and J. Galloway. Assessing the Social and Environmental Costs of Institutional Nitrogen Footprints.   Sustainability: The Journal of Record. Mary Ann Liebert, Inc., New Rochelle, NY, USA, 10(2): 114-122, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1407639",
            "keyword": [
                "benefit-cost analysis",
                "nitrogen",
                "nutrients",
                "ecosystem services",
                "atmospheric deposition",
                "fertilizer",
                "point sources",
                "N-fixation"
            ],
            "contactPoint": {
                "fn": "Jana Compton",
                "hasEmail": "mailto:compton.jana@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://online.liebertpub.com/doi/pdfplus/10.1089/sus.2017.29099.jec",
                    "accessURL": "https://online.liebertpub.com/doi/pdfplus/10.1089/sus.2017.29099.jec"
                },
                {
                    "title": "SciHub data ORD-019271.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407639/SciHub%20data%20ORD-019271.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-09-27",
            "references": [
                "https://doi.org/10.1089/sus.2017.29099.jec"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Mineralogical Evidence of Galvanic Corrosion in Drinking Water Lead Pipe Joints",
            "description": "The importance of galvanic corrosion as a mechanism of toxic lead release into drinking water has been under scientific debate in the U.S. for over 30 years. Visual and mineralogical analysis of 28 lead pipe joints, excavated after 60+ years by 8 U.S water utilities, provided the first direct view of galvanic corrosion presence/extent in practice. Three patterns were observed: (1) no galvanic corrosion; (2) galvanic corrosion with lead pipe cathodic relative to anodic copper/brass; (3) galvanic corrosion with lead pipe anodic relative to cathodic copper/brass. Pattern 3 is consistent with the order of increasing nobility found in empirical galvanic series (lead, brass, copper). Pattern 2 is consistent with galvanic battery reversion, possibly depending on certain water quality and/or flow conditions. A variety of copper-sulfate minerals (Pattern 2), and lead-sulfate and lead -chloride minerals (Pattern 3) were identified to form in the galvanic zones, with geochemical modeling confirming the required pH drop from the bulk water level to pH 3.0-4.0 (Pattern 2) and pH<5.5 (Pattern 3), as well as the migration of chloride and sulfate ions toward the sacrificial anode. Despite joints being over 60 years old, galvanic zones in Pattern 3 were active and possibly posed an important source of lead to drinking water. This dataset is not publicly accessible because: Overall, due to the nature of this observational research, no additional datasets would be useful to provide to the public. Most raw datasets in this research effort are not meaningful in x-y format and are not even readable by the public unless they own specialized software licenses, know how to use all of the software, and can interpret the data in its various formats as they relate to the project. The remainder of the information is photographs and tables with the raw data already included. It can be accessed through the following means: The data are generally very specific to the research topics explored, but could be shared with other researchers if requested. Interested parties who own and know how to use the specialized software involved in this research effort, may request the datasets by contacting the authors (our approved SDMP explains where all these records are located). Format: There is no single dataset and dataset format. The information is comprised of different files and electronic formats, mostly associated with specialized proprietary software that cannot be converted to x-y datasets in any meaningful way. The remainder of the information is photographs and tables with the raw data already included, so no additional raw data are needed for those. Our approved SDMP explains the data format for all figures and tables in this research effort. \n\nThis dataset is associated with the following publication:\nDeSantis, M., S. Triantafyllidou, M. Schock, and D. Lytle. Mineralogical Evidence of Galvanic Corrosion in Drinking Water Lead Pipe Joints.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(6): 3365-3374, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1404938",
            "keyword": [
                "drinking water",
                "lead",
                "galvanic corrosion",
                "mineralogy",
                "geochemical modeling",
                "brass",
                "Copper"
            ],
            "contactPoint": {
                "fn": "Michael Desantis",
                "hasEmail": "mailto:desantis.mike@epa.gov"
            },
            "distribution": [],
            "modified": "2017-10-11",
            "references": [
                "https://doi.org/10.1021/acs.est.7b06010"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data Set for A Call for an Aloft Air Quality Monitoring Network: Need and Feasibility",
            "description": "This data set contains all relevant data used in the creation of the 4 illustrations in the manuscript. In all cases the data have been processed (averaged/aggregated over space and/or time) from the original data which was at finer spatial or temporal resolution. The observational data sets are publicly available from the CASTNET site. Raw model outputs can be made available by contacting the corresponding author. \n\nThis dataset is associated with the following publication:\nMathur, R., C. Hogrefe, A. Hakami, S. Zhao, J. Szykman, and G. Hagler. A Call for an Aloft Air Quality Monitoring Network: Need, Feasibility, and Potential Value.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(19): 10903\u201310908, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1408773",
            "keyword": [
                "long-range transport",
                "background pollution",
                "boundary layer",
                "vertical profile",
                "atmospheric mixing"
            ],
            "contactPoint": {
                "fn": "Rohit Mathur",
                "hasEmail": "mailto:mathur.rohit@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure1_ptile_diurnal_pa_new.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1408773/Figure1_ptile_diurnal_pa_new.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "Figure1_InsetA_July2010_mod_obs_average_diurnal.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1408773/Figure1_InsetA_July2010_mod_obs_average_diurnal.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "Figure3_data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1408773/Figure3_data.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Figure4_data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1408773/Figure4_data.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Figure2_data_rate_8am9am_trends_21years_castnet_2seasons.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1408773/Figure2_data_rate_8am9am_trends_21years_castnet_2seasons.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-11-15",
            "references": [
                "https://doi.org/10.1021/acs.est.8b02496"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1408773/documents/DataDictionary_AloftNetwork.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Life Cycle Impact Assessment and Life Cycle Cost of both Legacy and Upgraded Systems",
            "description": "LCIA and LCC data for legacy and updated systems under various scenarios. \n\nThis dataset is associated with the following publication:\nMorelli, B., S. Cashman, C. Ma, J. Garland, J. Turgeon, L. Fillmore, D. Bless, and M. Nye. Effect of Nutrient Removal and Resource Recovery on Life Cycle Cost and Environmental Impacts of a Small Scale Water Resource Recovery Facility.   Sustainability. MDPI AG, Basel,  SWITZERLAND, 10(10): 1-19, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407683",
            "keyword": [
                "biogas",
                "chp",
                "biological nutrient removal",
                "resource recovery",
                "energy recovery"
            ],
            "contactPoint": {
                "fn": "Xin Ma",
                "hasEmail": "mailto:ma.cissy@epa.gov"
            },
            "distribution": [
                {
                    "title": "Bath AD & Compost Model_v2_5.8.17.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407683/Bath%20AD%20%26%20Compost%20Model_v2_5.8.17.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Bath LCI_Legacy_v2_5.8.17.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407683/Bath%20LCI_Legacy_v2_5.8.17.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Bath_LCIA Results_v3_5.30.17.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407683/Bath_LCIA%20Results_v3_5.30.17.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-06",
            "references": [
                "https://doi.org/10.3390/su10103546"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supplementary material for Lee et al. in review: Harmonization and Revision of a National Diatom Dataset for Use in the Development of Water Quality Indicators",
            "description": "ABSTRACT\nDiatom data have been collected in large-scale biological assessments in the United States, such as the U.S. Environmental Protection Agency\u2019s National Rivers and Streams Assessment (NRSA). However, the effectiveness of diatoms as indicators may suffer if inconsistent taxon identifications across different analysts obscure the relationships between assemblage composition and environmental variables. To reduce these inconsistencies, we harmonized the 2008-2009 NRSA data from nine analysts by updating names to current synonyms and by statistically identifying taxa with high analyst signal (taxa with more variation in relative abundance explained by the analyst factor, relative to environmental variables). We then screened a subset of samples with QA/QC data and combined taxa with mismatching identifications by the primary and secondary analysts. When these combined \u201cslash groups\u201d did not reduce analyst signal, we elevated taxa to the genus level or omitted taxa in difficult species complexes. We examined the variability explained by analyst in the original and revised datasets. Further, we examined how revising the datasets to reduce analyst signal can reduce inconsistency, thereby uncovering the variation in assemblage composition explained by total phosphorus (TP), an environmental variable of high priority for water managers. To produce a revised dataset with the greatest taxonomic consistency, we ultimately made 124 slash groups, omitted 7 taxa in the small naviculoid (e.g., Sellaphora atomoides) species complex, and elevated Nitzschia, Diploneis, and Tryblionella taxa to the genus level. Relative to the original dataset, the revised dataset had more overlap among samples grouped by analyst in ordination space, less variation explained by the analyst factor, and more than double the variation in assemblage composition explained by TP. Elevating all taxa to the genus level did not eliminate analyst signal completely, and analyst remained the most important predictor for the genera Sellaphora, Mayamaea, and Psammodictyon, indicating that these taxa present the greatest obstacle to consistent identification in this dataset. Although our process did not completely remove the analyst signal, this work clarifies the extent of the problem and provides a method to minimize analyst signal. Resolution of these taxonomic issues makes large datasets such as the NRSA more suitable for the development of diatom-based water quality indicators. This dataset is associated with the following publication:\nLee, S., I. Bishop, S. Spaulding, R. Mitchell, and L. Yuan. Taxonomic harmonization may reveal a stronger association between diatom assemblages and total phosphorus in large datasets..   ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 102: 166-174, (2019). NOTE: This dataset has been removed from public access due to revocation. Please refer inquiries regarding this dataset to the listed contact person.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1502631",
            "keyword": [
                "taxonomy",
                "data harmonization",
                "diatoms",
                "rivers and streams"
            ],
            "contactPoint": {
                "fn": "Sylvia Lee",
                "hasEmail": "mailto:lee.sylvia@epa.gov"
            },
            "distribution": [],
            "modified": "2018-10-09",
            "references": null,
            "publisher": {
                "name": "U.S. Environmental Protection Agency",
                "subOrganizationOf": {
                    "name": "U.S. Government"
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Meta data ",
            "description": "the data that was used to populate the tables and figures in the document. \n\nThis dataset is associated with the following publication:\nHuang, X., and T. Tolaymat. Gas Quantity and Composition from the Hydrolysis of Salt Cake from Secondary Aluminum Processing.  Majid Abbaspour  International Journal of Environmental Science and Technology. Springer, Heidelburg,  GERMANY,  1-12, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1435606",
            "keyword": [
                "reactive waste",
                "aluminum dross",
                "landfills"
            ],
            "contactPoint": {
                "fn": "Thabet Tolaymat",
                "hasEmail": "mailto:tolaymat.thabet@epa.gov"
            },
            "distribution": [
                {
                    "title": "Tolaymat SC hydrolysis.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435606/Tolaymat%20SC%20hydrolysis.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-12-25",
            "references": [
                "https://doi.org/10.1007/s13762-018-1820-x"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Estimated floodplain map for the conterminous United States",
            "description": "Understanding the relationship between flood inundation and floodplains is critical for ecosystem and community health and well-being, as well as targeting floodplain and riparian restoration. Many communities in the United States, particularly those in rural areas, lack inundation maps due to the high cost of flood modeling. Only 60% of the conterminous United States has Flood Insurance Rate Maps (FIRMs) through the U.S. Federal Emergency Management Agency (FEMA). This EnviroAtlas dataset provides an estimate of the 100-year floodplain for the conterminous United States at 30-meter resolution to fill the gaps in the FIRM. The model hit rate for the CONUS was 0.79 compared to the FIRM, indicating that the model captured 79% of the 100-year floodplain identified by FEMA. This product provides complete coverage for the CONUS by identifying floodplains in areas without FIRMs, while also identifying floodplains in tributaries sometimes excluded by FEMA. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets) or journal article (https://doi.org/10.1016/j.scitotenv.2018.07.353). This dataset is useful for evaluating the potential value of ecosystem services provided by floodplains. The overall goal of EnviroAtlas is to employ and develop the best available science to map indicators of ecosystem services production, demand, and drivers for the nation. These data are not meant to replace or supplement FEMA Flood Insurance Rate Maps. \n\nThis dataset is associated with the following publication:\nWoznicki, S., J. Baynes, S. Panlasigui, M. Mehaffey, and A. Neale. Development of a spatially complete floodplain map of the conterminous United States using random forest.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 647: 942-953, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1503085",
            "keyword": [
                "Floodplain",
                "random forest",
                "EnviroAtlas",
                "GIS",
                "machine learning",
                "ecosystem services"
            ],
            "contactPoint": {
                "fn": "Sean Woznicki",
                "hasEmail": "mailto:woznicki.sean@epa.gov"
            },
            "distribution": [
                {
                    "title": "EnviroAtlas - Estimated floodplain map for CONUS - Random Forest Model Performance by HUC-4.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503085/EnviroAtlas%20-%20Estimated%20floodplain%20map%20for%20CONUS%20-%20Random%20Forest%20Model%20Performance%20by%20HUC-4.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "EnviroAtlas - Estimated floodplain map for CONUS - Random Forest Model Performance by landscape classifications.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503085/EnviroAtlas%20-%20Estimated%20floodplain%20map%20for%20CONUS%20-%20Random%20Forest%20Model%20Performance%20by%20landscape%20classifications.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "EnviroAtlas - Estimated floodplain map for CONUS - Random Forest Scaled Variable Importance by HUC-4.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503085/EnviroAtlas%20-%20Estimated%20floodplain%20map%20for%20CONUS%20-%20Random%20Forest%20Scaled%20Variable%20Importance%20by%20HUC-4.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://gaftp.epa.gov/epadatacommons/ORD/EnviroAtlas/Estimated_floodplain_CONUS.zip",
                    "accessURL": "https://gaftp.epa.gov/epadatacommons/ORD/EnviroAtlas/Estimated_floodplain_CONUS.zip"
                }
            ],
            "modified": "2018-06-04",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.07.353"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "NEEAR Water Study-human markers",
            "description": "Data set consists of survey data containing PII, water quality sample test results for fecal indicator bacteria and additional supporting information. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Upon request to Tim Wade (wade.tim@epa.gov). Format: Data are stored in SAS datasets with codebooks in MS Word  documenting variables. \n\nThis dataset is associated with the following publication:\nNapier, M., R. Haugland, C. Poole, A. Dufour, J. Stewart, D. Weber, M. Varma, J. Lavender, and T. Wade. Exposure to human-associated fecal indicators and self-reported illness among swimmers at recreational beaches: A cohort study.   ENVIRONMENTAL HEALTH. Academic Press Incorporated, Orlando, FL, USA, 16(1): 103, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1503031",
            "keyword": [
                "beach water quality",
                "swimming",
                "diarrhea"
            ],
            "contactPoint": {
                "fn": "Timothy Wade",
                "hasEmail": "mailto:wade.tim@epa.gov"
            },
            "distribution": [],
            "modified": "2017-10-01",
            "references": [
                "https://doi.org/10.1186/s12940-017-0308-3"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "NEEAR Water Study-Chemicals",
            "description": "data includes human health survey data, linked records of chemical measures and measures of water quality. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Upon request to Tim Wade (wade.tim@epa.gov). Format: Data are stored in SAS datasets with documented codebooks. \n\nThis dataset is associated with the following publication:\nNapier, M., C. Poole, J. Stewart, D. Weber, S. Glassmeyer, D. Kolpin, E. Furlong, A. Dufour, and T. Wade. Exposure to human-associated chemical markers of fecal contamination and self-reported illness among swimmers at recreational beaches.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(13): 7513-7523, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1408779",
            "keyword": [
                "beach water quality",
                "swimming",
                "diarrhea"
            ],
            "contactPoint": {
                "fn": "Timothy Wade",
                "hasEmail": "mailto:wade.tim@epa.gov"
            },
            "distribution": [],
            "modified": "2017-11-15",
            "references": [
                "https://doi.org/10.1021/acs.est.8b00639"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Adaptation and application of multivariate AMBI (M-AMBI) in US coastal waters data",
            "description": "extensively in Europe, but not in the United States. In a previous study, we adapted AMBI for use in US coastal waters (US AMBI), but saw biases in salinity and score distribution when compared to locally calibrated indices.\nIn this study we modified M-AMBI for US waters and compared its performance to that of US AMBI. Index performance was evaluated in three ways: 1) concordance with local indices presently being used as management\ntools in three geographic regions of US coastal waters, 2) classification accuracy for sites defined a priori as good or bad and 3) insensitivity to natural environmental gradients. US M-AMBI was highly correlated with all three local indices and removed the compression in response seen in moderately disturbed sites with US AMBI.  This data set provides the data used to conduct these analyses and produce the tables and figures in the paper. \n\nThis dataset is associated with the following publication:\nPelletier, P., D. Gillett, A. Hamilton, T. Grayson, V. Hansen, E. Leppo, S. Weisberg, and A. Borja. Adaptation and application of multivariate AMBI (M-AMBI) in US coastal waters.   ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 89: 818-827, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1427171",
            "keyword": [
                "Benthos",
                "Marine benthic invertebrates",
                "benthic index"
            ],
            "contactPoint": {
                "fn": "Marguerite Pelletier",
                "hasEmail": "mailto:pelletier.peg@epa.gov"
            },
            "distribution": [
                {
                    "title": "M-AMBI_ScienceHub_data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1427171/M-AMBI_ScienceHub_data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-24",
            "references": [
                "https://doi.org/10.1016/j.ecolind.2017.08.067"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Coliphages and gastrointestinal illness in recreational waters: pooled analysis of six coastal beach cohorts",
            "description": "Data consists of health and survey data from epidemiological studies at beach sites and water quality measurements. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Data can be accessed by request to Tim Wade: wade.tim@epa.gov. Format: Data are stored in comma delimited text files with codebooks in MS Word. \n\nThis dataset is associated with the following publication:\nBenjamin-Chung, J., B. Arnold, T. Wade, K. Schiff, J. Griffith, A. Dufour, S. Weisberg, and J. Colford. Coliphages and gastrointestinal illness in recreational waters: pooled analysis of six coastal beach cohorts.   EPIDEMIOLOGY. Lippincott Williams & Wilkins, Philadelphia, PA, USA, 28(5): 644-652, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1503101",
            "keyword": [
                "beach water quality",
                "swimming",
                "diarrhea"
            ],
            "contactPoint": {
                "fn": "Timothy Wade",
                "hasEmail": "mailto:wade.tim@epa.gov"
            },
            "distribution": [],
            "modified": "2017-01-16",
            "references": [
                "https://doi.org/10.1097/ede.0000000000000681"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for figures in Assessing the Value Added of Population Modeling for Aquatic Exposures to Time-Varying Exposures.",
            "description": "Data used to create Figure 2 through 9 in the paper. Where appropriate raw data are also included. Each figure is in a separate worksheet. Also included are the daily and running averages of the three 30-year exposure time-series. \n\nThis dataset is associated with the following publication:\nThursby, G., K. Sappington, and M. Etterson. Coupling Toxicokinetic-Toxicodynamic and Population Models for Assessing Aquatic Ecological Risks to Time-Varying Pesticide Exposures.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(10): 2633-2644, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407633",
            "keyword": [
                "Americamysis bahia",
                "matrix modeling",
                "population level risk assessment",
                "time-varying exposures"
            ],
            "contactPoint": {
                "fn": "Glen Thursby",
                "hasEmail": "mailto:thursby.glen@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHub for ORD-023077.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407633/ScienceHub%20for%20ORD-023077.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-14",
            "references": [
                "https://doi.org/10.1002/etc.4224"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Tipping Point determinations",
            "description": "The attached zip file contains all of the source data, intermediate outputs and R-scripts used to calculate the tipping points reported in the Frank et al manuscript. \n\nThis dataset is associated with the following publication:\nChristopher, F., J. Brown, K. Wallace, J. Wambaugh, I. Shah, and T. Shafer. Defining toxicological tipping points in neuronal network development.   TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 354: 81-93, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407690",
            "keyword": [
                "developmental neurotoxicity",
                "Microelectrode array",
                "In vitro assay",
                "network development",
                "Chemical Screening"
            ],
            "contactPoint": {
                "fn": "Timothy Shafer",
                "hasEmail": "mailto:shafer.tim@epa.gov"
            },
            "distribution": [
                {
                    "title": "TippingPointData.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407690/TippingPointData.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-11-06",
            "references": [
                "https://doi.org/10.1016/j.taap.2018.01.017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The Association between Dust Storms and Daily Non-Accidental Mortality in the United States, 1993-2005.",
            "description": "records of mortality, dust storms and demographic/census data for the United States. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Data contained PII and were obtained under a licensing agreement with CDC. Data may be obtained from CDC/NCHS.  Contact Tim Wade (wade.tim@epa.gov) for other access options. Format: Raw data consist of fixed delimited text files from the CDC/NCHS with data documentation provided. Data are processed and analyzed in R and stored as R data files and/or comma delimited text files. R programs fully document the processing and variable naming conventions. \n\nThis dataset is associated with the following publication:\nCrooks , J., W. Cascio , M. Percy, J. Reyes , L. Neas , and E. Hilborn. The Association between Dust Storms and Daily Non-Accidental Mortality in the United States, 1993-2005..   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 124(11): 1735-43, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1503105",
            "keyword": [
                "air quality",
                "cardiovascular mortality",
                "multiple stressors",
                "epidemiology"
            ],
            "contactPoint": {
                "fn": "Timothy Wade",
                "hasEmail": "mailto:wade.tim@epa.gov"
            },
            "distribution": [],
            "modified": "2016-11-01",
            "references": [
                "https://doi.org/10.1289/ehp216"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Hughes_A-0gb9_EH-TBB and BEH-TEBP in vitro dermal absorption 05/24/2017",
            "description": "The data is on 4 tabs, separated by species (rat, human) and chemical (EH-TBB and BEH_TEBP).  The data is by cell (2-4/skin), and includes %dose in receptor fluid over time, % unabsorbed, % absorbed and % penetrated. \n\nThis dataset is associated with the following publication:\nKnudsen, G., M. Hughes, J.M. Sanders, S. Hall, and L. Birnbaum. Estimation of human percutaneous bioavailability for two novel brominated flame retardants, 2-ethylhexyl tetrabromobenzoate (EH-TBB) and bis(2-ethylhexyl) tetrabromophthalate (BEH-TEBP), using the parallelogram approach.   TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 311: 117-127, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1503100",
            "keyword": [
                "brominated flame retardant",
                "in vitro dermal absorption"
            ],
            "contactPoint": {
                "fn": "Michael Hughes",
                "hasEmail": "mailto:hughes.michaelf@epa.gov"
            },
            "distribution": [
                {
                    "title": "Hughes_A-0gb9_EH-TBB and BEH-TEBP in vitro dermal data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503100/Hughes_A-0gb9_EH-TBB%20and%20BEH-TEBP%20in%20vitro%20dermal%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-10-22",
            "references": [
                "https://doi.org/10.1016/j.taap.2016.10.005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "% Viability and zeta potential values of metal nanoparticles used in in vitro dermal irritation assays",
            "description": "1) % Viability of human reconstructed skin exposed to cerium, silver and titanium nanoparticles; 2) Zeta potential of the nanoparticles in media. \n\nThis dataset is associated with the following publication:\nMiyani, V., and M. Hughes. Assessment of the vitro dermal irritation of cerium silver and titanium nanoparticles in a human skin equivalent model.   TOXICOLOGY IN VITRO. Elsevier Science Ltd, New York, NY, USA, 36(2): 145-151, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1503095",
            "keyword": [
                "Nanoparticles",
                "skin",
                "irritation",
                "in vitro assays"
            ],
            "contactPoint": {
                "fn": "Michael Hughes",
                "hasEmail": "mailto:hughes.michaelf@epa.gov"
            },
            "distribution": [
                {
                    "title": "HughesMichael_A-ffbw_Dermal Irritation Data_20170531.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503095/HughesMichael_A-ffbw_Dermal%20Irritation%20Data_20170531.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-25",
            "references": [
                "https://doi.org/10.1080/15569527.2016.1211671"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Transcriptional and physiological responses of nitrifying bacteria to heavy metal inhibition  ",
            "description": "SOUR (oxygen uptake rates) and qPCR for nitrification genes. \n\nThis dataset is associated with the following publication:\nKapoor , V., X. Li , M. Elk , K. Chandran, C. Impellitteri , and J. Santodomingo. Transcriptional and physiological responses of nitrifying bacteria to heavy metal inhibition.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 49: 13454-13462, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503088",
            "keyword": [
                "nitrification",
                "wastewater"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [
                {
                    "title": "A-zs8c - Transcriptional and physiological response SOUR_results Ni Cd Zn Pb.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503088/A-zs8c%20-%20Transcriptional%20and%20physiological%20response%20SOUR_results%20Ni%20Cd%20Zn%20Pb.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "A-zs8c - Transcriptional and physiological response qPCR_results Ni Cd Zn Pb.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503088/A-zs8c%20-%20Transcriptional%20and%20physiological%20response%20qPCR_results%20Ni%20Cd%20Zn%20Pb.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-07-01",
            "references": [
                "http://pubs.acs.org/doi/pdf/10.1021/acs.est.5b02748"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Inhibitory effect of cyanide on wastewater nitrification determined using SOUR and RNA-based gene-specific assays",
            "description": "SOUR and qPCR data. \n\nThis dataset is associated with the following publication:\nKapoor, V., M. Elk, and X. Li. Inhibitory effect of cyanide on wastewater nitrification determined using SOUR and RNA-based gene-specific assays.   Letters in Applied Microbiology. Blackwell Publishing, Malden, MA, USA, 63(2): 155-161, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503089",
            "keyword": [
                "nitrification inhibition",
                "wastewater"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [
                {
                    "title": "A-98sv Inhibitory effect of CN paper data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503089/A-98sv%20Inhibitory%20effect%20of%20CN%20paper%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-11-16",
            "references": [
                "http://onlinelibrary.wiley.com/doi/10.1111/lam.12603/pdf"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "NHEERL MEA Toxcast Single Concentration Screening data",
            "description": "This file contains the data used to generate hit calls from neural activity recordings on microelectrode array (MEA) plates treated with ToxCast compounds at a single concentration. \n\nThis dataset is associated with the following publication:\nStrickland, J., M. Martin, A. Richard, K. Houck, and T. Shafer. Screening the ToxCast phase II libraries for alterations in network function using cortical neurons grown on multi-well microelectrode array (mwMEA) plates.   Archives of Toxicology. Springer, New York, NY, USA, 92(1): 487-500, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1374534",
            "keyword": [
                "in vitro screening",
                "neurotoxicity",
                "Microelectrode array"
            ],
            "contactPoint": {
                "fn": "Timothy Shafer",
                "hasEmail": "mailto:shafer.tim@epa.gov"
            },
            "distribution": [
                {
                    "title": "NHEERL_MEA_TOXCAST_SS_DATA_20160615.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374534/NHEERL_MEA_TOXCAST_SS_DATA_20160615.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-03-30",
            "references": [
                "https://doi.org/10.1007/s00204-017-2035-5"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The impact of variation in scaling factors on the estimation of internal dose metrics:  a case study using bromodichloromethane (BDCM)",
            "description": "This dataset contains model code and supporting analysis files necessary to evaluate the impact of variability in human hepatic  scaling factors.  Variation in scaling factor values impacts metabolic rate parameter estimates (Vmax) and hence estimates of internal dose used in dose response analysis and biomarkers of exposure that are important for interpretation of epidemiology studies. \n\nThis dataset is associated with the following publication:\nKenyon, E., C. Eklund, J. Lipscomb, and R. Pegram. The impact of variation in scaling factors on the estimation of internal dose metrics:  a case study using bromodichloromethane (BDCM).1.   Toxicology Mechanisms and Methods. Taylor & Francis, Inc., Philadelphia, PA, USA, 26(8): 620-626, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1379171",
            "keyword": [
                "human",
                "hepatic",
                "PBPK model",
                "bromodichloromethane",
                "scaling factors",
                "variation",
                "in vitro to in vivo extrapolation",
                "IVIVE",
                "variability"
            ],
            "contactPoint": {
                "fn": "Elaina Kenyon",
                "hasEmail": "mailto:kenyon.elaina@epa.gov"
            },
            "distribution": [
                {
                    "title": "ModelFile_ScalingVariabilityAdultBDCMcsl_JAT'16.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379171/ModelFile_ScalingVariabilityAdultBDCMcsl_JAT%2716.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "AnalysisFiles_ScalingVariabilityAdult.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379171/AnalysisFiles_ScalingVariabilityAdult.pdf",
                    "mediaType": "application/pdf"
                },
                {
                    "title": "ImpactScalingFactorVariabilityAdults_DocumentationMs.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1379171/ImpactScalingFactorVariabilityAdults_DocumentationMs.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2016-09-01",
            "references": [
                "https://doi.org/10.1080/15376516.2016.1225141"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1379171/documents/DataDictionary_ScalingFactorVariabilityAdult.pdf",
            "describedByType": "application/pdf",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Tal et al A-qc09 dataset",
            "description": "This dataset includes data used to generate Figures 4C, 5B, 5C, and 5D in Tal et al. Screening for angiogenic inhibitors in zebrafish to evaluate a predictive model for developmental vascular toxicity. Reproductive Toxicology. 2017. Data underlying all other figures shown in the manuscript are included in the Supplemental Tables published with the original article. \n\nThis dataset is associated with the following publication:\nTal , T., C. Kilty, A. Smith, C. LaLone , B. Kennedy, A. Tennant , C. McCollum, M. Bondesson, T. Knudsen , S. Padilla , and N. Kleinstreuer. Screening for angiogenic inhibitors in zebrafish to evaluate a predictive model for developmental vascular toxicity.   REPRODUCTIVE TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 70: 70-81, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1503108",
            "keyword": [
                "Hyaloid vessel",
                "zebrafish",
                "Developmental Toxicity"
            ],
            "contactPoint": {
                "fn": "Tamara Tal",
                "hasEmail": "mailto:tal.tamara@epa.gov"
            },
            "distribution": [
                {
                    "title": "A-qc09 dataset_20181022.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503108/A-qc09%20dataset_20181022.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-10-22",
            "references": [
                "https://doi.org/10.1016/j.reprotox.2016.12.004"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Mechanistic modeling of insecticide risks to breeding birds in North American agroecosystems",
            "description": "This dataset provides all parameter values necessary to replicate the TIM/MCnest model analysis reported in the manuscript \"Mechanistic modeling of insecticide risks to breeding birds in North American agroecosystems\". \n\nThis dataset is associated with the following publication:\nEtterson, M., K. Garber, and E. Odenkirchen. Mechanistic modeling of insecticide risks to breeding birds in North American agroecosystems.   PLoS ONE. Public Library of Science,  CA, USA,  1-23, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407540",
            "keyword": [
                "pesticide",
                "Insecticide",
                "MCnest",
                "Terrestrial Investigation Model",
                "Birds",
                "Agroecosystems",
                "Risk Assessment"
            ],
            "contactPoint": {
                "fn": "Matthew Etterson",
                "hasEmail": "mailto:etterson.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://doi.org/10.1371/journal.pone.0176998",
                    "accessURL": "https://doi.org/10.1371/journal.pone.0176998"
                }
            ],
            "modified": "2017-04-14",
            "references": [
                "https://doi.org/10.1371/journal.pone.0176998"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Metadata included in dataset file",
            "description": "The data provided in the file are measurements (and calculations) of various morphological characteristics made on individual larval fish specimens. \n\nThis dataset is associated with the following publication:\nPeterson, G., and J. Lietz. Identification of Ruffe larvae (Gymnocephalus cernuus) in the St. Louis River, Lake Superior:  Clarification and guidance regarding morphological descriptions.   JOURNAL OF GREAT LAKES RESEARCH. International Association for Great Lakes Research, Ann Arbor, MI, USA, 43(1): 205-210, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407651",
            "keyword": [
                "Great Lakes",
                "Aquatic invasive species",
                "sampling design",
                "DNA technology"
            ],
            "contactPoint": {
                "fn": "Gregory Peterson",
                "hasEmail": "mailto:peterson.greg@epa.gov"
            },
            "distribution": [
                {
                    "title": "A-m386-RuffeID_Dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407651/A-m386-RuffeID_Dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-26",
            "references": [
                "https://doi.org/10.1016/j.jglr.2016.10.005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Water Recreation and Illness Severity",
            "description": "Data included health survey data from beach goers and water quality measurements. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Data contain PII and cannot be released publically. Limited deidentified data sets can be requested by contacting Tim Wade (wade.tim@epa.gov). Format: Data consist of comma delimited text files of survey data from beach goers and water quality measurements. Codebooks are in MS Word. \n\nThis dataset is associated with the following publications:\nDeFlorio-Baker, S., T. Wade , M. Turyk, and S. Dorevitch. Water Recreation and Illness Severity.   JOURNAL OF WATER AND HEALTH. IWA Publishing, London,  UK, 5: 713-726, (2016).\nDeFlorio-Barker, S., T. Wade , R. Jones, L. Friedman, C. Wing, and S. Dorevitch. Estimated Costs of Sporadic Gastrointestinal Illness Associated with Surface Water Recreation: A Combined Analysis of Data from NEEAR and CHEERS Studies.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 125(2): 215-222, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1503102",
            "keyword": [
                "beach water quality",
                "swimming",
                "diarrhea"
            ],
            "contactPoint": {
                "fn": "Timothy Wade",
                "hasEmail": "mailto:wade.tim@epa.gov"
            },
            "distribution": [],
            "modified": "2017-01-16",
            "references": [
                "https://doi.org/10.2166/wh.2016.002",
                "https://doi.org/10.1289/ehp130"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Region 5 RARE air manganese data set",
            "description": "A cross-sectional design was used where 86 residents of East Liverpool, Ohio, 100 residents from Marietta, Ohio and 90 residents from Mount Vernon, Ohio were recruited and participated in the study. The Marietta/Mount Vernon data collection took place in August, 2009 as this was the original study location. Marietta was an air manganese (air-Mn) exposed community and Mt. Vernon was a comparison community believed to have little or no air-Mn exposure. After receiving additional funding and approvals, East Liverpool was added and data collection occurred in November, 2011 using identical study protocols to the Marietta/Mount Vernon study with the exception of additional specimen collections of hair and toenails (only collected in East Liverpool). All participants underwent a neuropsychological battery of tests of mood, motor and cognitive function. A comprehensive health questionnaire was administered inquiring about sociodemographics, symptoms, diagnosed illnesses, medication use, health habits, work history, and dietary consumption (used to compute dietary intake of Mn and Fe). Additionally, the study included data acquisition on air monitoring and modeling, biomarkers, and health. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Because this dataset includes protected health information, public access is not available. Format: csv files. \n\nThis dataset is associated with the following publication:\nKornblith, E., S. Casey, D. Lobdell, M. Colledge, and R. Bowler. Environmental exposure to manganese in air: Tremor, motor and cognitive symptom profiles.   NEUROTOXICOLOGY. Elsevier B.V., Amsterdam,  NETHERLANDS, 64: 152-158, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1503068",
            "keyword": [
                "air manganese",
                "neurologic outcomes"
            ],
            "contactPoint": {
                "fn": "Danelle Lobdell",
                "hasEmail": "mailto:lobdell.danelle@epa.gov"
            },
            "distribution": [],
            "modified": "2016-07-21",
            "references": [
                "https://doi.org/10.1016/j.neuro.2017.09.012"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Medication use associated with exposure to manganese in two Ohio towns",
            "description": "A cross-sectional design was used where 86 residents of East Liverpool, Ohio, 100 residents from Marietta, Ohio and 90 residents from Mount Vernon, Ohio were recruited and participated in the study. The Marietta/Mount Vernon data collection took place in August, 2009 as this was the original study location. Marietta was an air manganese (air-Mn) exposed community and Mt. Vernon was a comparison community believed to have little or no air-Mn exposure. After receiving additional funding and approvals, East Liverpool was added and data collection occurred in November, 2011 using identical study protocols to the Marietta/Mount Vernon study with the exception of additional specimen collections of hair and toenails (only collected in East Liverpool). All participants underwent a neuropsychological battery of tests of mood, motor and cognitive function. A comprehensive health questionnaire was administered inquiring about sociodemographics, symptoms, diagnosed illnesses, medication use, health habits, work history, and dietary consumption (used to compute dietary intake of Mn and Fe). Additionally, the study included data acquisition on air monitoring and modeling, biomarkers, and health. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Because this data set includes protected health information, public access is not available. Format: csv files. \n\nThis dataset is associated with the following publication:\nBowler, R., S. Adams, C. Wright, Y. Kim, A. Booty, M. Colledge, V. Gocheva, and D. Lobdell. Medication Use Associated with Exposure to Manganese in Two Ohio Towns.   INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH. Carfax Publishing Limited, Basingstoke,  UK, 26(5): 483-96, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1503104",
            "keyword": [
                "medication use",
                "air manganese",
                "neurologic outcomes"
            ],
            "contactPoint": {
                "fn": "Danelle Lobdell",
                "hasEmail": "mailto:lobdell.danelle@epa.gov"
            },
            "distribution": [],
            "modified": "2016-06-13",
            "references": [
                "https://doi.org/10.1080/09603123.2016.1194381"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "County-level cumulative environmental quality associated with cancer incidence.",
            "description": "Population based cancer incidence rates were abstracted from National Cancer Institute,\nState Cancer Profiles for all available counties in the United States for which data were\navailable. This is a national county-level database of cancer data that are collected by state\npublic health surveillance systems. All-site cancer is defined as any type of cancer that is\ncaptured in the state registry data, though non-melanoma skin cancer is not included. All-site\nage-adjusted cancer incidence rates were abstracted separately for males and females.\nCounty-level annual age-adjusted all-site cancer incidence rates for years 2006\u20132010 were\navailable for 2687 of 3142 (85.5%) counties in the U.S. Counties for which there are fewer\nthan 16 reported cases in a specific area-sex-race category are suppressed to ensure\nconfidentiality and stability of rate estimates; this accounted for 14 counties in our study.\nTwo states, Kansas and Virginia, do not provide data because of state legislation and\nregulations which prohibit the release of county level data to outside entities. Data from\nMichigan does not include cases diagnosed in other states because data exchange\nagreements prohibit the release of data to third parties. Finally, state data is not available for\nthree states, Minnesota, Ohio, and Washington. The age-adjusted average annual\nincidence rate for all counties was 453.7 per 100,000 persons.\nWe selected 2006\u20132010 as it is subsequent in time to the EQI exposure data which was\nconstructed to represent the years 2000\u20132005. We also gathered data for the three leading\ncauses of cancer for males (lung, prostate, and colorectal) and females (lung, breast, and\ncolorectal). \n\nThe EQI was used as an exposure metric as an indicator of cumulative environmental\nexposures at the county-level representing the period 2000 to 2005. A complete description\nof the datasets used in the EQI are provided in Lobdell et al.  and methods used for index\nconstruction are described by Messer et al. The EQI was developed for the period 2000\u2013\n2005 because it was the time period for which the most recent data were available when\nindex construction was initiated. The EQI includes variables representing each of the\nenvironmental domains. The air domain includes 87 variables representing criteria and\nhazardous air pollutants. The water domain includes 80 variables representing overall water\nquality, general water contamination, recreational water quality, drinking water quality,\natmospheric deposition, drought, and chemical contamination. The land domain includes 26\nvariables representing agriculture, pesticides, contaminants, facilities, and radon. The built\ndomain includes 14 variables representing roads, highway/road safety, public transit\nbehavior, business environment, and subsidized housing environment. The\nsociodemographic environment includes 12 variables representing socioeconomics and\ncrime. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data are stored as csv files. \n\nThis dataset is associated with the following publication:\nJagai, J., L. Messer, K. Rappazzo , C. Gray, S. Grabich , and D. Lobdell. County-level environmental quality and associations with cancer incidence#.   Cancer. John Wiley & Sons Incorporated, New York, NY, USA, 123(15): 2901-2908, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1503103",
            "keyword": [
                "environmental quality",
                "air quality",
                "water quality",
                "built environment",
                "sociodemographic quality",
                "land quality"
            ],
            "contactPoint": {
                "fn": "Danelle Lobdell",
                "hasEmail": "mailto:lobdell.danelle@epa.gov"
            },
            "distribution": [],
            "modified": "2017-08-01",
            "references": [
                "https://doi.org/10.1002/cncr.30709"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Additive interaction between heterogeneous environmental quality domains (air, water, land, sociodemographic and built environment) on preterm birth",
            "description": "The study population included live births from the National Center for Health Statistics (NCHS) for the entire United States for the years 2000\u20132005 for all 3141 counties. Domain-specific EQIs were used to represent environmental exposure at the county-level for the entire U.S. over the 2000\u20132005 time period. The EQI includes variables representing five environmental domains: air, water, land, built, and sociodemographic (2). The domain-specific indices include both beneficial and detrimental environmental factors. The air domain includes 87 variables representing criteria and hazardous air pollutants. The water domain includes 80 variables representing overall water quality, general water contamination, recreational water quality, drinking water quality, atmospheric deposition, drought, and chemical contamination. The land domain includes 26 variables representing agriculture, pesticides, contaminants, facilities, and radon. The built domain includes 14 variables representing roads, highway/road safety, public transit behavior, business environment, and subsidized housing environment. The sociodemographic environment includes 12 variables representing socioeconomics and crime. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data are stored as csv files. \n\nThis dataset is associated with the following publication:\nGrabich, S., K. Rappazzo, C. Gray, J. Jagai, Y. Jian, L. Messer, and D. Lobdell. Additive interaction between heterogeneous environmental quality domains (air, water, land, sociodemographic and built environment) on preterm birth.   Frontiers in Public Health. Frontiers, Lausanne,  SWITZERLAND, 4: 232, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1503121",
            "keyword": [
                "environmental quality",
                "air quality",
                "water quality",
                "built environment",
                "sociodemographic quality",
                "land quality"
            ],
            "contactPoint": {
                "fn": "Danelle Lobdell",
                "hasEmail": "mailto:lobdell.danelle@epa.gov"
            },
            "distribution": [],
            "modified": "2016-10-24",
            "references": [
                "https://doi.org/10.3389/fpubh.2016.00232"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Associations between environmental quality and mortality in the contiguous United States 2000-2005",
            "description": "Age-adjusted mortality rates for the contiguous United States in 2000\u20132005 were obtained from the Wide-ranging Online Data for Epidemiologic Research system of the U.S. Centers for Disease Control and Prevention (CDC) (2015). Age-adjusted mortality rates were weighted averages of the age-specific death rates, and they were used to account for different age structures among populations (Curtin and Klein 1995). The mortality rates for counties with < 10 deaths were suppressed by the CDC to protect privacy and to ensure data reliability; only counties with \u2265 10 deaths were included in the analyses. The underlying cause of mortality was specified using the World Health Organization\u2019s International Statistical Classification of Diseases and Related Health Problems (10th revision; ICD-10). In this study, we focused on the all-cause mortality rate (A00-R99) and on mortality rates from the three leading causes: heart disease (I00-I09, I11, I13, and I20-I51), cancer (C00-C97), and stroke (I60- I69) (Heron 2013). We excluded mortality due to external causes for all-cause mortality, as has been done in many previous studies (e.g., Pearce et al. 2010, 2011; Zanobetti and Schwartz 2009), because external causes of mortality are less likely to be related to environmental quality. We also focused on the contiguous United States because the numbers of counties with available cause-specific mortality rates were small in Hawaii and Alaska. County-level rates were available for 3,101 of the 3,109 counties in the contiguous United States (99.7%) for all-cause mortality; for 3,067 (98.6%) counties for heart disease mortality; for 3,057 (98.3%) counties for cancer mortality; and for 2,847 (91.6%) counties for stroke mortality. The EQI includes variables representing five environmental domains: air, water, land, built, and sociodemographic (2). The domain-specific indices include both beneficial and detrimental environmental factors. The air domain includes 87 variables representing criteria and hazardous air pollutants. The water domain includes 80 variables representing overall water quality, general water contamination, recreational water quality, drinking water quality, atmospheric deposition, drought, and chemical contamination. The land domain includes 26 variables representing agriculture, pesticides, contaminants, facilities, and radon. The built domain includes 14 variables representing roads, highway/road safety, public transit behavior, business environment, and subsidized housing environment. The sociodemographic environment includes 12 variables representing socioeconomics and crime. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data are stored as csv files. \n\nThis dataset is associated with the following publication:\nJian, Y., L. Messer, J. Jagai, K. Rappazzo, C. Gray, S. Grabich, and D. Lobdell. Associations between environmental quality and mortality in the contiguous United States 2000-2005.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 125(3): 355-362, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1503120",
            "keyword": [
                "environmental quality",
                "air quality",
                "water quality",
                "built environment",
                "sociodemographic quality",
                "land quality"
            ],
            "contactPoint": {
                "fn": "Danelle Lobdell",
                "hasEmail": "mailto:lobdell.danelle@epa.gov"
            },
            "distribution": [],
            "modified": "2017-03-01",
            "references": [
                "https://doi.org/10.1289/ehp119"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Coastal final ecosystem goods and services (FEGS) and habitats meta-analysis data file",
            "description": "Coastal ecosystem goods and services (EGS) have steadily gained traction in the scientific literature over the last few decades, providing a wealth of information about underlying coastal habitat dependencies. This meta-analysis summarizes relationships between coastal habitats and final ecosystem goods and services (FEGS) users. Through a \u201cweight of evidence\u201d approach synthesizing information from published literature, we assessed habitat classes most relevant to coastal users. Approximately 2800 coastal EGS journal articles were identified by online search engines, of which 16% addressed linkages between specific coastal habitats and FEGS users, and were retained for subsequent analysis. Recreational (83%) and industrial (35%) users were most cited in literature, with experiential-users/hikers and commercial fishermen most prominent in each category, respectively. Recreational users were linked to the widest diversity of coastal habitat subclasses (i.e., 22 of 26). Whereas, mangroves and emergent wetlands were most relevant for property owners. We urge EGS studies to continue surveying local users and identifying habitat dependencies, as these steps are important precursors for developing appropriate coastal FEGS metrics and facilitating local valuation. In addition, understanding how habitats contribute to human well-being may assist communities in prioritizing restoration and evaluating development scenarios in the context of future ecosystem service delivery. \n\nThis dataset is associated with the following publication:\nLittles, C., C. Jackson, T. DeWitt, and M. Harwell. Linking People to Coastal Habitats: A meta-analysis of final ecosystem goods and services (FEGS) on the coast.   Ocean & Coastal Management. Elsevier, Shannon,  IRELAND, 165: 356-369, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1424684",
            "keyword": [
                "Ecosystem Goods and Services",
                "nearshore",
                "literature review"
            ],
            "contactPoint": {
                "fn": "Chanda Littles",
                "hasEmail": "mailto:littles.chanda@epa.gov"
            },
            "distribution": [
                {
                    "title": "Manuscript1_data-file_FINAL_SciHub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1424684/Manuscript1_data-file_FINAL_SciHub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-03-08",
            "references": [
                "https://doi.org/10.1016/j.ocecoaman.2018.09.009"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for this project include human subjects PII and cannot be shared. ",
            "description": "Data on approximately 2 million births occurring in NJ, OH, and PA from 2000 - 2005. Linked to PM2.5 and ozone concentration estimates from EPA CMAQ fused model. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Birth data can be acquired through application to the state health statistics departments of NJ, OH, and PA. Contact author for code. rappazzo.kristen@epa.gov. Format: No data included. \n\nThis dataset is associated with the following publication:\nRappazzo, K., D. Lobdell, L. Messer, C. Poole, and J. Daniels. Comparison of gestational dating methods and implications for exposure-outcome associations: an example with PM2.5 and preterm birth.   JOURNAL OF OCCUPATIONAL AND ENVIRONMENTAL MEDICINE. Lippincott Williams & Wilkins, Philadelphia, PA, USA, 74(2): 138-143, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1503119",
            "keyword": [
                "particulate matter",
                "preterm birth"
            ],
            "contactPoint": {
                "fn": "Kristen Rappazzo",
                "hasEmail": "mailto:rappazzo.kristen@epa.gov"
            },
            "distribution": [],
            "modified": "2017-02-15",
            "references": [
                "https://doi.org/10.1136/oemed-2016-103833"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Nitrogen inputs and stream N concentrations NRSA 2008-2009 ",
            "description": "This is a combined dataset that includes data for 1966 of the 2008-2009 National Rivers and Streams Assessment watersheds.  The data includes watershed N inputs and stream TN, TON and DIN concentrations. \n\nThis dataset is associated with the following publication:\nBellmore, R., J. Compton, R. Brooks, E. Fox, R. Hill, D. Sobota, D. Thornbrugh, and M. Weber. Nitrogen inputs drive nitrogen concentrations in U.S. streams and rivers during summer low flow conditions.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 639: 1349-1359, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503062",
            "keyword": [
                "nitrogen",
                "streams",
                "rivers",
                "monitoring",
                "watersheds",
                "N inputs"
            ],
            "contactPoint": {
                "fn": "Jana Compton",
                "hasEmail": "mailto:compton.jana@epa.gov"
            },
            "distribution": [
                {
                    "title": "N data for publication.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503062/N%20data%20for%20publication.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-09-27",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.05.008"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1503062/documents/N%20data%20for%20publication.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Ecosystem Services Content Analysis Data",
            "description": "Content records of public media. \n\nThis dataset is associated with the following publication:\nWeber, M., C. Shannon, P. Ringold, and K. Blocksom. Rivers and Streams in the Media: Evaluating New Sources for Ecosystem Services Content.   Ecology and Society. Resilience Alliance Publications, Waterloo,  CANADA, 22(3): 15, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1503076",
            "keyword": [
                "final ecosystem services",
                "media",
                "multivariate analysis of variance",
                "nonmetric multidimensional scaling",
                "rivers and streams",
                "content analysis"
            ],
            "contactPoint": {
                "fn": "Paul Ringold",
                "hasEmail": "mailto:ringold.paul@epa.gov"
            },
            "distribution": [
                {
                    "title": "Blog_Channel.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503076/Blog_Channel.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Blog_Fish_Wildlife.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503076/Blog_Fish_Wildlife.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Blog_Info.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503076/Blog_Info.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Blog_Human.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503076/Blog_Human.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Blog_Motivations.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503076/Blog_Motivations.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Blog_Water.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503076/Blog_Water.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Blog_with_Families.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503076/Blog_with_Families.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "BlogCodeCounts.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503076/BlogCodeCounts.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Blog_wordcounts.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503076/Blog_wordcounts.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://doi.org/10.5751/ES-09496-220315",
                    "accessURL": "https://doi.org/10.5751/ES-09496-220315"
                }
            ],
            "modified": "2014-09-30",
            "references": [
                "https://doi.org/10.5751/es-09496-220315"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "QT_RR data for effects on diesel exhaust on cardiac conduction",
            "description": "This dataset includes QTc and RR values related to the electrocardiogram of rats exposed to either air or diesel exhaust. \n\nThis dataset is associated with the following publication:\nHazari , M., J. Lancaster, J. Starobin, A. Farraj , and W. Cascio. Diesel exhaust worsens cardiac conduction instability in dobutamine-challenged Wistar-Kyoto and spontaneously hypertensive rats.   Cardiovascular Toxicology. Humana Press Incorporated, Totowa, NJ, USA, 17(2): 120-129, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1503098",
            "keyword": [
                "QTc",
                "electrocardiogram",
                "Diesel Exhaust",
                "cardiac",
                "arrhythmia",
                "Rats"
            ],
            "contactPoint": {
                "fn": "Mehdi Hazari",
                "hasEmail": "mailto:hazari.mehdi@epa.gov"
            },
            "distribution": [
                {
                    "title": "QT_RR data_dobutamine challenge test_Hazari_Dec 2015a.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503098/QT_RR%20data_dobutamine%20challenge%20test_Hazari_Dec%202015a.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "QT_RR data_dobutamine challenge test_Hazari_Dec 2015b.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503098/QT_RR%20data_dobutamine%20challenge%20test_Hazari_Dec%202015b.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "QT_RR data_dobutamine challenge test_Hazari_Dec 2015.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503098/QT_RR%20data_dobutamine%20challenge%20test_Hazari_Dec%202015.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "QT_RR data_dobutamine challenge test_Hazari_Dec 2015b`.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503098/QT_RR%20data_dobutamine%20challenge%20test_Hazari_Dec%202015b%60.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-12-08",
            "references": [
                "https://doi.org/10.1007/s12012-016-9363-1"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cardiac effects of acrolein in mice and role of TRPA1",
            "description": "This data shows the heart rate, heart rate variability and cardiac mechanical function of mice exposed to acrolein or ozone. \n\nThis dataset is associated with the following publication:\nKurhanewicz, N., R. McIntosh-Kastrinsky, H. Tong, A. Ledbetter, L. Walsh, A. Farraj, and M. Hazari. TRPA1 mediates changes in heart rate variability and cardiac mechanical function in mice exposed to acrolein.   TOXICOLOGICAL AND APPLIED PHARMICOLOGY. Elsevier Science BV, Amsterdam,  NETHERLANDS, 324: 51-60, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1503099",
            "keyword": [
                "acrolein",
                "cardiac",
                "TRPA1",
                "mouse"
            ],
            "contactPoint": {
                "fn": "Mehdi Hazari",
                "hasEmail": "mailto:hazari.mehdi@epa.gov"
            },
            "distribution": [
                {
                    "title": "TRPA1 acrolein ozone Hazari_complete data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503099/TRPA1%20acrolein%20ozone%20Hazari_complete%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-12-04",
            "references": [
                "https://doi.org/10.1016/j.taap.2016.10.008"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "SAS code used to analyze data and a datafile with metadata glossary",
            "description": "We compiled macroinvertebrate assemblage data collected from 1995 to 2014 from the St. Louis River Area of Concern (AOC) of western Lake Superior. Our objective was to define depth-adjusted cutoff values for benthos condition classes (poor, fair, reference) to provide tool useful for assessing progress toward achieving removal targets for the degraded benthos beneficial use impairment in the AOC. The relationship between depth and benthos metrics was wedge-shaped. We therefore used quantile regression to model the limiting effect of depth on selected benthos metrics, including taxa richness, percent non-oligochaete individuals, combined percent Ephemeroptera, Trichoptera, and Odonata individuals, and density of ephemerid mayfly nymphs (Hexagenia). We created a scaled trimetric index from the first three metrics. Metric values at or above the 90th percentile quantile regression model prediction were defined as reference condition for that depth. We set the cutoff between poor and fair condition as the 50th percentile model prediction. We examined sampler type, exposure, geographic zone of the AOC, and substrate type for confounding effects. Based on these analyses we combined data across sampler type and exposure classes and created separate models for each geographic zone. We used the resulting condition class cutoff values to assess the relative benthic condition for three habitat restoration project areas. The depth-limited pattern of ephemerid abundance we observed in the St. Louis River AOC also occurred elsewhere in the Great Lakes. We provide tabulated model predictions for application of our depth-adjusted condition class cutoff values to new sample data. \n\nThis dataset is associated with the following publication:\nAngradi, T., W. Bartsch, A. Trebitz, V. Brady, and J. Launspach. A depth-adjusted ambient distribution approach for setting numeric removal targets for a Great Lakes Area of Concern beneficial use impairment: Degraded benthos.   JOURNAL OF GREAT LAKES RESEARCH. International Association for Great Lakes Research, Ann Arbor, MI, USA, 43(1): 108-120, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1412675",
            "keyword": [
                "Great Lakes Areas of Concern",
                "Benthos",
                "reference"
            ],
            "contactPoint": {
                "fn": "Theodore Angradi",
                "hasEmail": "mailto:angradi.theodore@epa.gov"
            },
            "distribution": [
                {
                    "title": "slrebug_TMI_082916.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1412675/slrebug_TMI_082916.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "science_hub_20181024.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1412675/science_hub_20181024.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-10-24",
            "references": [
                "https://doi.org/10.1016/j.jglr.2016.11.006"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": " Dose-Response Analysis of RNA-Seq Profiles in Archival Formalin-Fixed Paraffin-Embedded Samples.",
            "description": "se of archival resources has been limited to date by inconsistent methods for genomic profiling of degraded RNA from formalin-fixed paraffin-embedded (FFPE) samples. RNA-seq offers a novel way to address this problem. In this study we evaluated transcriptomic dose responses using RNA-seq in paired FFPE and frozen (FROZ) samples from two archival studies in mice, one recent (<2 years old) and the other older (>20 years old). Experimental treatments included di(2-ethylhexyl)phthalate (DEHP) and dichloroacetic acid (DCA) for the <2 and >20 year-old studies, respectively. Total RNA was ribodepleted and sequenced using the Illumina HiSeq platform. In the recent study, FFPE samples showed high concordance in total reads (98% vs FROZ), fold-change values of differentially expressed genes (DEGs) (R2 = 0.99), highly enriched target pathways (90% overlap with FROZ), and benchmark dose estimates for preselected target genes (-2% overall vs FROZ). In contrast, RNA-seq data from older FFPE samples had lower total reads (70% vs FROZ) and poor concordance in global DEGs and pathways. Despite a 99% loss of counts, dose responses were still evident for target genes in FFPE samples and positively correlated with paired FROZ samples. These findings highlight potential variability in the quality of RNA-seq data from FFPE samples. More recent FFPE samples were highly similar to FROZ samples in sequencing quality metrics, DEG profiles, and dose-response parameters, while further methods development is needed for older or lower-quality FFPE samples. This work should help broaden the use of archival resources in both chemical safety and translational science. \n\nThis dataset is associated with the following publication:\nHester, S., V. Bhat, B. Chorley, G. Carswell, W. Jones, L. Wehmas, and C. Wood. Dose-Response Analysis of RNA-Seq Profiles in Archival Formalin-Fixed Paraffin-Embedded (FFPE) Samples..   TOXICOLOGICAL SCIENCES. Society of Toxicology,    154(2): 202-213, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1503172",
            "keyword": [
                "Dose-Response Analysis",
                "RNA-Seq Archival FFPE"
            ],
            "contactPoint": {
                "fn": "Susan Hester",
                "hasEmail": "mailto:hester.susan@epa.gov"
            },
            "distribution": [
                {
                    "title": "GEO seq_template_v2_lcw_2016-02-26.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503172/GEO%20seq_template_v2_lcw_2016-02-26.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE78962",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE78962"
                }
            ],
            "modified": "2016-12-01",
            "references": [
                "https://doi.org/10.1093/toxsci/kfw161"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1503172/documents/Hester%20et%20al%20FFPE%20-%20Manuscript_v9f%20clean%20for%20clearance.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Prior knowledge-based approach for associating contaminants with biological effects: a case study in the St. Croix river basin, MN, WI, USA.",
            "description": "Concentrations of 127 organic chemicals measured in water samples collected from five locations in proximity to two municipal wastewater treatment plants in the St. Croix River basin, MN and WI, USA are included.  Additionally, gene expression in the livers of fathead minnows exposed in situ to the site water for 12 d is included. Gene expression was analyzed by oligonucleotide microarray and raw data are accessible through the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO), accession number GSE81263. Additional analyses performed on those data, including construction of knowledge assembly models from comparison of the detected chemicals data with associated genes from the comparative toxicogenomics database, pathway and gene ontology enrichment analyses performed on the gene expression data, and richness and concordance statistics from a Reverse Causal Reasoning-based statistical approach are included. \n\nThis dataset is associated with the following publication:\nSchroeder , A., D. Martinovi\u0107-Weigelt, G. Ankley , K. Lee, N. Garcia-Reyero, E. Perkins, H. Schoenfuss, and D. Villeneuve. Prior knowledge-based approach for associating contaminants with biological effects: A case study in the St. Croix river basin, MN, WI, USA..   ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 221: 427-436, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1503123",
            "keyword": [
                "adverse outcome pathway",
                "ecotoxicology",
                "endocrine disruption",
                "screening and prioritization",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE81263",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE81263"
                },
                {
                    "title": "ORD-012137 Supplementary Tables.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503123/ORD-012137%20Supplementary%20Tables.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-10-25",
            "references": [
                "https://doi.org/10.1016/j.envpol.2016.12.005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Haselman et al 2016 Development of the LAGDA: effects of tOP or TB in Xenopus laevis from embryo to juvenile",
            "description": "These data are from two studies conducted to evaluate the performance of the draft Larval Amphibian Growth and Development Assay for incorporation into the U.S. EPA's Endocrine Disruptor Screening Program Tier II testing battery. 4-tert-octylphenol was chosen as an environmental estrogenic compound and 17-beta-trenbolone was chosen as an environmental androgenic compound. Although the effects of these model environmental endocrine disruptors are not novel, these chemicals were used essentially as positive controls to represent each of the potential modes of toxicity that could be encountered by future unknown compounds ordered to be run through the LAGDA in support of risk assessment. Endpoints evaluated were larval growth and metamorphic development, blood thyroid hormone, thyroid histopathology, juvenile growth, juvenile histopathology of the liver, gonads, kidneys and reproductive ducts. \n\nThis dataset is associated with the following publication:\nHaselman , J., P. Kosian , J. Korte , A. Olmstead, T. Iguchi, R. Johnson , and S. Degitz. Development of the larval amphibian growth and development assay: Effects of chronic 4-tert-octylphenol or 17\u00df-trenbolone exposure in Xenopus laevis from embryo to juvenile.   JOURNAL OF APPLIED TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 36(12): 1639-1650, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1503122",
            "keyword": [
                "EDSP",
                "LAGDA",
                "Xenopus laevis",
                "4-tert-octylphenol",
                "17-beta-trenbolone"
            ],
            "contactPoint": {
                "fn": "Jonathan Haselman",
                "hasEmail": "mailto:haselman.jon@epa.gov"
            },
            "distribution": [
                {
                    "title": "Haselman_et_al_tOP&TB_data_Ar22z.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503122/Haselman_et_al_tOP%26TB_data_Ar22z.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-02-25",
            "references": [
                "https://doi.org/10.1002/jat.3330"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Effects of Simulated Smog in Rodent Models of Disease Dataset.",
            "description": "The dataset includes the draft main paper and supporting information file to be submitted to the journal, and also excel spread sheets containing the raw data which backs up the processed data used in the paper and supporting information file.\n    Data include exposure characterization (temperature, RH, pollutant levels, etc.), physiology data, serum data, lung inflammation data, viral burden data, PCR data, blood data, lung pathology data, and other miscellaneous data.  All the column headings and other relevant definitions and information are included in the data sets, and match the relevant data in the paper to be submitted. \n\nThis dataset is associated with the following publication:\nHargrove, M., S. Snow, R. Luebke, C. Wood, J. Krug, T. Krantz, C. King, C. Copeland, S. McCullough, K. Gowdy, U. Kodavanti, I. Gilmour, and S. Gavett. Effects of Simulated Smog Atmospheres in Rodent Models of Metabolic and Immunologic Dysfunction.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(5): 3062-3070, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1375711",
            "keyword": [
                "Smog",
                "photochemical reactions",
                "allergy",
                "bacterial infection",
                "influenza A",
                "diabetes",
                "pulmonary function",
                "pulmonary injury"
            ],
            "contactPoint": {
                "fn": "Stephen Gavett",
                "hasEmail": "mailto:gavett.stephen@epa.gov"
            },
            "distribution": [
                {
                    "title": "MMH Smog Manuscript 2017 08 22.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375711/MMH%20Smog%20Manuscript%202017%2008%2022.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "MMH Smog Manuscript 2017 08 22 supporting file.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375711/MMH%20Smog%20Manuscript%202017%2008%2022%20supporting%20file.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "MMH Smog manuscript data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375711/MMH%20Smog%20manuscript%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "MMH Smog Supplemental file data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375711/MMH%20Smog%20Supplemental%20file%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-17",
            "references": [
                "https://doi.org/10.1021/acs.est.7b06534"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Multiplex ELISA MTF-1 and western blot raw data",
            "description": "Multiplex ELisa data, MTF-1 and western blot. \n\nThis dataset is associated with the following publication:\nBruno, M., J. Ross, and Y. Ge. Proteomic Responses of BEAS-2B Cells to Nontoxic and Toxic Chromium: Protein Indicators of Cytotoxicity Conversion.   TOXICOLOGY LETTERS. Elsevier Science Ltd, New York, NY, USA, 264: 59-70, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1503118",
            "keyword": [
                "MAP KINASE",
                "apoptosis",
                "CELL GROWTH",
                "Inflammatory cytokines",
                "MTF-1 AKT",
                "proteomics",
                "metal mixtures",
                "chromium",
                "2D gel electrophoresis",
                "ELISA",
                "signaling proteins"
            ],
            "contactPoint": {
                "fn": "Maribel Bruno",
                "hasEmail": "mailto:bruno.maribel@epa.gov"
            },
            "distribution": [
                {
                    "title": "Raw data for sciencehub Chr paper October 24 2018.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503118/Raw%20data%20for%20sciencehub%20Chr%20paper%20October%2024%202018.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-10-24",
            "references": [
                "https://doi.org/10.1016/j.toxlet.2016.08.025"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Developmental Thyroid Hormone Insufficiency Induces Cortical Brain Malformation and Learning Impairments: A Cross-Fostering Study",
            "description": "thyroid hormone from serum of rats exposed to goitrogen. Morphometry in brain. Behavioral data. \n\nThis dataset is associated with the following publication:\nOShaughnessy, K., P. Kosian, J. Ford, W. Oshiro, S. Degitz, and M. Gilbert. Developmental Thyroid Hormone Insufficiency Induces Cortical Brain Malformation and Learning Impairments: A Cross-Fostering Study.   TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA,  163(1): 101-115, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407670",
            "keyword": [
                "thyroid homone",
                "heterotopia",
                "fear conditioning",
                "developmental hypothyroidism"
            ],
            "contactPoint": {
                "fn": "Mary Gilbert",
                "hasEmail": "mailto:gilbert.mary@epa.gov"
            },
            "distribution": [
                {
                    "title": "M0914 Crossfostering Mean Summary Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407670/M0914%20Crossfostering%20Mean%20Summary%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-07",
            "references": [
                "https://doi.org/10.1093/toxsci/kfy016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data For Figures",
            "description": "This dataset contains data presented in the figures of the paper \"Semivolatile POA and parameterized total combustion SOA in CMAQv5.2: impacts on source strength and partitioning\" published in Atmospheric Chemistry and Physics. It also links to the data archive of field observations. \n\nThis dataset is associated with the following publication:\nMurphy, B., M. Woody, J. Jimenez, A.M. Carlton, P. Hayes, S. Liu, N. Ng, L. Russell, A. Setyan, L. Xu, J. Young, R. Zaveri, Q. Zhang, and H. Pye. Semivolatile POA and parameterized total combustion SOA in CMAQv5.2: impacts on source strength and partitioning.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 17: 11107-11133, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434890",
            "keyword": [
                "organic aerosol",
                "CMAQ",
                "particulate matter",
                "volatility",
                "Aging",
                "CalNex",
                "CARES",
                "SOAS"
            ],
            "contactPoint": {
                "fn": "Benjamin Murphy",
                "hasEmail": "mailto:murphy.benjamin@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure_2.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434890/Figure_2.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figure_4.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434890/Figure_4.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figure_3.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434890/Figure_3.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figure_1.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434890/Figure_1.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figure_5.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434890/Figure_5.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figure_8.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434890/Figure_8.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figure_13.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434890/Figure_13.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figure_12.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434890/Figure_12.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figure_9.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434890/Figure_9.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figure_10.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434890/Figure_10.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figure_11.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434890/Figure_11.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figure_6.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434890/Figure_6.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Figure_7.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434890/Figure_7.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-07-20",
            "references": [
                "https://doi.org/10.5194/acp-17-11107-2017"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1434890/documents/Data%20Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Derivation and Evaluation of Putative Adverse Outcome Pathways for Effects of Cycylooxygenase inhibitors on Reproductive Processes in Female Fish",
            "description": "Fathead minnows (Pimephales promelas) were exposed to 100 ug/L indomethacin, 200 ug/L ibuprofen, or 20 ug/L celecoxib for 96 h.  Effects on cycloxygenase enzyme activity in ovary, prostaglandin F2alpha concentrations in plasma, 17beta-estradiol concentrations in plasma, and vitellogenin concentrations in plasma were measured. Gene expression in ovary samples was evaluated using a 15,000 probe oligonucleotide microarray. Transcriptomics data (raw data and normalized) are available through the National Center for Biotechnology Information, Gene Expression Omnibus (GEO), accession number GSE72976. Metabolite profiles in liver tissue were measured by proton nuclear magnetic resonance. In addition to these data, the data set also contains identification of differentially expressed genes, pathway enrichment and gene set enrichment analyes, ToxCast data for indomethacin and celecoxib, chemical-gene interaction data derived from the Comparative Toxicogenomics database, and results from Level 1, Level 2, and Level 3 SeqAPASS analyses that examine conservation of target proteins across species (https://seqapass.epa.gov/seqapass/). \n\nThis dataset is associated with the following publication:\nMartinovic-Weigelt, D., A. Mehinto, G. Ankley , J. Berninger, T. Collette , J. Davis , N. Denslow, E. Durhan, E. Eid, D. Ekman , K. Jensen , M. Kahl , C. LaLone , Q. Teng , and D. Villeneuve. Derivation and evaluation of putative adverse outcome pathways for the effects of cyclooxygenase inhibitors on reproductive processes in female fish.   TOXICOLOGICAL SCIENCES. Society of Toxicology,    156(2): 344-361, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1503124",
            "keyword": [
                "adverse outcome pathway",
                "ecotoxicology",
                "endocrine disruption",
                "screening and prioritization",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE72976",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE72976"
                },
                {
                    "title": "2 ORD-013745 Pathway enrichment and GSEA.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503124/2%20ORD-013745%20Pathway%20enrichment%20and%20GSEA.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "3 ORD-013745 Ingenuity Pathway Analyes.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503124/3%20ORD-013745%20Ingenuity%20Pathway%20Analyes.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "4 ORD-013745 ToxCast data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503124/4%20ORD-013745%20ToxCast%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "5 ORD-013745 CTD Chemical-gene interactions.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503124/5%20ORD-013745%20CTD%20Chemical-gene%20interactions.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "6 ORD-013745 SeqAPASS level 1, cox1.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503124/6%20ORD-013745%20SeqAPASS%20level%201%2C%20cox1.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "7 ORD-013745 SeqAPASS level 1, cox2.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503124/7%20ORD-013745%20SeqAPASS%20level%201%2C%20cox2.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "8 ORD-013745 SeqAPASS level 2, cox1.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503124/8%20ORD-013745%20SeqAPASS%20level%202%2C%20cox1.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "9 ORD-013745 SeqAPASS level 2, cox2.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503124/9%20ORD-013745%20SeqAPASS%20level%202%2C%20cox2.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "10 ORD-013745 SeqAPASS level 3, cox1.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503124/10%20ORD-013745%20SeqAPASS%20level%203%2C%20cox1.xlsx",
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                },
                {
                    "title": "11 ORD-013745 SeqAPASS level 3, cox2.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503124/11%20ORD-013745%20SeqAPASS%20level%203%2C%20cox2.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "1 ORD-013745 Differentially expressed genes.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503124/1%20ORD-013745%20Differentially%20expressed%20genes.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "12 ORD-013745 MartinovicToxSCI_VTG_E2_COX_PGF.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503124/12%20ORD-013745%20MartinovicToxSCI_VTG_E2_COX_PGF.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "14 ORD-013745 COX Inhib_Metabolomics_PCA.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503124/14%20ORD-013745%20COX%20Inhib_Metabolomics_PCA.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "13 ORD-013745 COX Inhib_Metabolomics_Diff Spec.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503124/13%20ORD-013745%20COX%20Inhib_Metabolomics_Diff%20Spec.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
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            ],
            "modified": "2018-10-25",
            "references": [
                "https://doi.org/10.1093/toxsci/kfw257"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Effects of the antimicrobial contaminant triclocarban, and co-exposure with the androgen 17beta-trenbolone, on reproductive function and ovarian transcriptome of the fathead minnow (Pimephales promelas).",
            "description": "Triclocarban (TCC) is a widely used antimicrobial agent that is routinely detected in surface waters. The present study was designed to examine TCC\u2019s efficacy and mode of action as a reproductive toxicant in fish. Reproductively mature Pimephales promelas were continuously exposed to either 1 or 5 \u03bcg TCC/L,  0.5 \u03bcg 17\u03b2-trenbolone (TRB)/L or a mixture (MIX) of 5 \u03bcg TCC and 0.5 \u03bcg TRB/L for 22 d and a variety of reproductive and endocrine-related endpoints were examined. The data set includes:\n-Concentrations of the test chemicals detected in water and tissues of exposed fish\n-Ex vivo production of testosterone and estradiol by gonad tissue placed in culture (ex vivo).\n-Plasma concentrations of testosterone, 17beta estradiol, and vitellogenin\n-Targeted gene expression measurements examining relative abundance of messenger RNA coding for enzymes involved in steroid synthesis: cholesterol side-chain cleavage\n(cyp11a), 17-a-hydroxylase/17,20 lyase (cyp17), aromatase (cyp19a1a), 3b-hydroxysteroid dehydrogenase (3bhsd), 11bhydroxysteroid dehydrogenase (11bhsd), and 17b-hydroxysteroid dehydrogenase (17bhsd) as well as five additional transcripts\nmeasured included steroidogenic acute regulatory protein (star), Vtg receptor (vtgr), follicle-stimulating hormone receptor (fshr), luteinizing hormone receptor (lhr), and\nandrogen receptor (ar). \n-Ovarian transcriptomics data measured using a 15000 feature oligonucleotide microarray (GEO Platform Accession GPL10259).\n-Survival, reproduction, and morphological data.\n-. \n\nThis dataset is associated with the following publication:\nVilleneuve , D., K. Jensen , J. Cavallin , E. Durhan, N. Garcia-Reyero, M. Kahl , R. Leino, E. Makynen, L. Wehmas, E. Perkins, and G. Ankley. Effects of the anti-microbial contaminant triclocarban and co-exposure with the androgen 17\u00e2-trenbolone, on reproductive function and ovarian transcriptome of the fathead minnow (Pimephales promelas).   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 36(1): :231-242, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1503126",
            "keyword": [
                "adverse outcome pathway",
                "ecotoxicology",
                "endocrine disruption",
                "screening and prioritization",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE64291",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE64291"
                },
                {
                    "title": "ORD-011209 Triclocarban Science Hub Data File.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503126/ORD-011209%20Triclocarban%20Science%20Hub%20Data%20File.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-10-26",
            "references": [
                "https://doi.org/10.1002/etc.3531",
                "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6110301/"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "DNA metabarcoding OTU tables",
            "description": "DNA sequence data output with assigned taxonomic IDs. \n\nThis dataset is associated with the following publication:\nHatzenbuhler, C., J.R.  Kelly, J. Martinson, S. Okum, and E. Pilgrim. Sensitivity and accuracy of high-throughput metabarcoding methods for early detection of invasive fish species.   Scientific Reports. Nature Publishing Group,   UK, 7: 1-10 (46393), (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503117",
            "keyword": [
                "DNA Barcoding",
                "Aquatic invasive species",
                "Great Lakes"
            ],
            "contactPoint": {
                "fn": "Chelsea Hatzenbuhler",
                "hasEmail": "mailto:hatzenbuhler.chelsea@epa.gov"
            },
            "distribution": [
                {
                    "title": "TrialA_DNA_SequenceData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503117/TrialA_DNA_SequenceData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "TrialB_DNA_SequenceData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503117/TrialB_DNA_SequenceData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-10-25",
            "references": [
                "https://doi.org/10.1038/srep46393"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Asbestosis and iron",
            "description": "None provided. \n\nThis dataset is associated with the following publication:\nGhio, A., J. Soukup, L. Dailey, H. Tong, and J. Richards. The biological effect of asbestos exposure is dependent on changes in iron homeostasis.   INHALATION TOXICOLOGY. Informa Healthcare USA, New York, NY, USA, 28(14): 698-705, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1503116",
            "keyword": [
                "Particles and fibers"
            ],
            "contactPoint": {
                "fn": "Andrew Ghio",
                "hasEmail": "mailto:ghio.andy@epa.gov"
            },
            "distribution": [
                {
                    "title": "asbestosis and iron figure 1A.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503116/asbestosis%20and%20iron%20figure%201A.xlsx",
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                    "title": "asbestosis and iron figure 2B.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503116/asbestosis%20and%20iron%20figure%202B.xlsx",
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                {
                    "title": "asbestosis and iron figure 1B.xlsx",
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                {
                    "title": "asbestosis and iron figure 2A.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503116/asbestosis%20and%20iron%20figure%202A.xlsx",
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                {
                    "title": "asbestosis and iron figure 2C.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503116/asbestosis%20and%20iron%20figure%202C.xlsx",
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                {
                    "title": "asbestosis and iron figure 2D.xlsx",
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                {
                    "title": "asbestosis and iron figure 4A.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503116/asbestosis%20and%20iron%20figure%204A.xlsx",
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                {
                    "title": "asbestosis and iron figure 5A.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503116/asbestosis%20and%20iron%20figure%205A.xlsx",
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                {
                    "title": "asbestosis and iron figure 6A.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503116/asbestosis%20and%20iron%20figure%206A.xlsx",
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                },
                {
                    "title": "asbestosis and iron figure 4B.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503116/asbestosis%20and%20iron%20figure%204B.xlsx",
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                {
                    "title": "asbestosis and iron figure 5B.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503116/asbestosis%20and%20iron%20figure%205B.xlsx",
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                },
                {
                    "title": "asbestosis and iron figure 6B.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503116/asbestosis%20and%20iron%20figure%206B.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-12-30",
            "references": [
                "https://doi.org/10.1080/08958378.2016.1257665"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
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            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cook et al 2016 data",
            "description": "The data are Excel spreadsheets with detailed physical measurements of 50 mineral fiber samples used for the modeling outlined in the publication. \n\nThis dataset is associated with the following publication:\nCook, P., J.  Swintek, T. Dawson, D. Chapman, M. Etterson , and D. Hoff. Quantitative structure - mesothelioma potency model optimization for complex mixtures of elongated particles in rat pleura: A retrospective study.   JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH - PART B:  CRITICAL REVIEWS. Taylor & Francis, Inc., Philadelphia, PA, USA, 19(5): 266-288, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1503127",
            "keyword": [
                "mesothelioma",
                "elongated particles",
                "rat pleura"
            ],
            "contactPoint": {
                "fn": "Dale Hoff",
                "hasEmail": "mailto:hoff.dale@epa.gov"
            },
            "distribution": [
                {
                    "title": "Cook16 - Amphibole Data Set Leached Surface Area Figure  6 (FibercellAsaL).xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503127/Cook16%20-%20Amphibole%20Data%20Set%20Leached%20Surface%20Area%20Figure%20%206%20%28FibercellAsaL%29.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Cook16 - Amphibole Data Set Unleached Fiber Number Figure 6 (FibercellAfnU).xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503127/Cook16%20-%20Amphibole%20Data%20Set%20Unleached%20Fiber%20Number%20Figure%206%20%28FibercellAfnU%29.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Cook16 - Amphibole Data Set Leached Fiber Number Figure  6 (FibercellAfnL).xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503127/Cook16%20-%20Amphibole%20Data%20Set%20Leached%20Fiber%20Number%20Figure%20%206%20%28FibercellAfnL%29.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Cook16 - Amphibole Data Set Unleached Surface Area  Figure 6 (FibercellAsaU).xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503127/Cook16%20-%20Amphibole%20Data%20Set%20Unleached%20Surface%20Area%20%20Figure%206%20%28FibercellAsaU%29.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Cook16 - Combined Data Set Leached Fiber Number Figure  6 (FibercellCfnL).xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503127/Cook16%20-%20Combined%20Data%20Set%20Leached%20Fiber%20Number%20Figure%20%206%20%28FibercellCfnL%29.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Cook16 - Combined Data Set Leached Surface Area Figure  6 (FibercellCsaL).xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503127/Cook16%20-%20Combined%20Data%20Set%20Leached%20Surface%20Area%20Figure%20%206%20%28FibercellCsaL%29.xls",
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                {
                    "title": "Cook16 - Combined Data Set Unleached Surface Area  Figure 6 (FibercellCsaU).xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503127/Cook16%20-%20Combined%20Data%20Set%20Unleached%20Surface%20Area%20%20Figure%206%20%28FibercellCsaU%29.xls",
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                },
                {
                    "title": "Cook16 - Stanton Data Set Leached Fiber Number Figure  6 (FibercellSRfnL).xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503127/Cook16%20-%20Stanton%20Data%20Set%20Leached%20Fiber%20Number%20Figure%20%206%20%28FibercellSRfnL%29.xls",
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                },
                {
                    "title": "Cook16-Data for Figure 5.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503127/Cook16-Data%20for%20Figure%205.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
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                {
                    "title": "Cook16 - Combined Data Set Unleached Fiber Number Figure 6 (FibercellCfnU).xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503127/Cook16%20-%20Combined%20Data%20Set%20Unleached%20Fiber%20Number%20Figure%206%20%28FibercellCfnU%29.xls",
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                },
                {
                    "title": "Cook16 - Stanton Data Set Unleached Surface Area  Figure 6 (FibercellSRsaU).xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503127/Cook16%20-%20Stanton%20Data%20Set%20Unleached%20Surface%20Area%20%20Figure%206%20%28FibercellSRsaU%29.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Cook16 - Stanton Data Set Unleached Fiber Number Figure 6 (FibercellSRfnU).xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503127/Cook16%20-%20Stanton%20Data%20Set%20Unleached%20Fiber%20Number%20Figure%206%20%28FibercellSRfnU%29.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Cook16-Data for Figure 9.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503127/Cook16-Data%20for%20Figure%209.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Cook16 - Stanton Data Set Leached Surface Area Figure  6 (FibercellSRsaL).xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503127/Cook16%20-%20Stanton%20Data%20Set%20Leached%20Surface%20Area%20Figure%20%206%20%28FibercellSRsaL%29.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2018-10-26",
            "references": [
                "https://doi.org/10.1080/10937404.2016.1195326"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Fox River kindling Bandara et al Summary Data",
            "description": "This study looked at functional endpoints in adult offspring of rats exposed in utero and postnatally to an environmentally relevant mixture of PCBs, Fox River blend. A model of neural plasticity and epilepsy, electrical kindling, was examined. Animals exposed to PCBs had slower kindling rates suggesting impaired plasticity mechanisms, consistent with previous work with PCBs where deficits were seen in another plasticity model, long-term potentiation. \n\nThis dataset is associated with the following publication:\nBandara, S., R. Sadowski, S. Schantz, and M. Gilbert. Developmental Exposure to an Environmental PCB Mixture Delays the Propagation of Kindling in the Amygdala.   NEUROTOXICOLOGY. Elsevier B.V., Amsterdam,  NETHERLANDS,  n/a, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1503125",
            "keyword": [
                "polyclorinated biphenyls",
                "children's health",
                "neruotoxicity",
                "thyroid hormone",
                "developmental hypothryoidism"
            ],
            "contactPoint": {
                "fn": "Mary Gilbert",
                "hasEmail": "mailto:gilbert.mary@epa.gov"
            },
            "distribution": [
                {
                    "title": "Fox River Kindling Bandara et al Summary Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503125/Fox%20River%20Kindling%20Bandara%20et%20al%20Summary%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-10-25",
            "references": [
                "https://doi.org/10.1016/j.neuro.2016.10.016"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Zhixuan Phosphate Data",
            "description": "The dataset shows two tables for linear combination fitting results of phosphorus speciation generated from two figures. \n\nThis dataset is associated with the following publication:\nZhixuan, Q., A. Shober, K. Scheckel, C. Penn, and K. Turner. Mechanisms of Phosphorus Removal by Phosphorus Sorbing Materials.   JOURNAL OF ENVIRONMENTAL QUALITY. American Society of Agronomy, MADISON, WI, USA, 47(5): 1232-1241, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1412837",
            "keyword": [
                "Phosphate Removal",
                "environmental transport",
                "water quality",
                "soil quality",
                "phosphate management"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "PSM Paper_Data for SciHub.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1412837/PSM%20Paper_Data%20for%20SciHub.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2017-12-20",
            "references": [
                "https://doi.org/10.2134/jeq2018.02.0064"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Quantitative constraints on autoxidation and dimer formation from direct probing of monoterpene-derived peroxy radical chemistry",
            "description": "Laboratory data supporting \"Quantitative constraints on autoxidation and dimer formation from direct probing of monoterpene-derived peroxy radical chemistry\" by Zhao, Thornton, and Pye.  \n\nAbstract: Organic peroxy radicals (RO2) are key intermediates in the atmospheric degradation of organic matter and fuel combustion, but to date, few direct studies of specific RO2 in complex reaction systems exist, leading to large gaps in our understanding of their fate. We show, using direct, speciated measurements of a suite of RO2 and gas-phase dimers from O3-initiated oxidation of \u03b1-pinene that ~150 gaseous dimers (C16-20H24-34O4-13) are primarily formed through RO2 cross-reactions, with a typical rate constant of 0.75-2\u00d710-12 cm3 molecule-1 s-1 and a lower-limit dimer formation branching ratio of 4%. These findings imply a gaseous dimer yield that varies strongly with nitric oxide (NO) concentrations, of at least 0.2-2.5% by mole (0.5-6.6% by mass) for conditions typical of forested regions with low to moderate anthropogenic influence (i.e., \u2264 50 ppt NO). Given their very low volatility, the gaseous C16-20 dimers provide a potentially important organic medium for initial particle formation, and alone can explain 5-60% of \u03b1-pinene secondary organic aerosol mass yields measured at atmospherically relevant particle mass loadings. The responses of RO2, dimers, and highly-oxygenated multifunctional compounds (HOM) to reacted \u03b1-pinene concentration and NO imply that an average ~20% of primary \u03b1-pinene RO2 from OH reaction and 10% from ozonolysis autoxidize at 3-10 s-1 and \u2265 1 s-1, respectively, confirming both oxidation pathways produce HOM efficiently, even at higher NO concentrations typical of urban areas. Thus, gas-phase dimer formation and RO2 autoxdiation are ubiquitous sources of low-volatility organic compounds capable of contributing significantly to atmospheric new particle formation and growth. \n\nThis dataset is associated with the following publication:\nZhao, Y., J. Thornton, and H. Pye. Quantitative constraints on autoxidation and dimer formation from direct probing of monoterpene-derived peroxy radical chemistry.   PNAS  (PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES). National Academy of Sciences, WASHINGTON, DC, USA, 115(48): 12142-12147, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1502514",
            "keyword": [
                "autoxidation",
                "Monoterpene",
                "dimer",
                "HOM",
                "pinene",
                "SOA",
                "pm2.5",
                "PM2.5 air quality modeling",
                "Semivolatile Organic Compounds (SVOCs)",
                "Biogenic VOC"
            ],
            "contactPoint": {
                "fn": "Havala Pye",
                "hasEmail": "mailto:pye.havala@epa.gov"
            },
            "distribution": [
                {
                    "title": "direct-probing-of-monoterpene-RO2-chemistry.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502514/direct-probing-of-monoterpene-RO2-chemistry.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-10-29",
            "references": [
                "https://doi.org/10.1073/pnas.1812147115"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Capillary-based immunoassay optimization of p53 and \u0251-tubulin in BEAS-2B cells ",
            "description": "These data were used to generate graphs and tables for the Journal of Visualized Experiments (JoVE) publication 'Procedure and Key Optimization Strategies for an Automated Capillary Electrophoretic-based Immunoassay Method. In general, the data are generated as example data for optimization of this method. \n\nThis dataset is associated with the following publications:\nNelson, G., J. Guynn, and B. Chorley. Procedure and Key Optimization Strategies for an Automated Capillary Electrophoretic-based Immunoassay Method.   Journal of Visualized Experiments. JoVE, Somerville, MA, USA, 127: e55911, (2017).\nNelson, G., J. Currier, and B. Chorley. Procedure and Key Optimization Strategies for an Automated Capillary\r\nElectrophoretic-based Immunoassay Method. JoVE, Somerville, MA, USA, 2017.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1374989",
            "keyword": [
                "capillary immunoassay",
                "method development",
                "p53",
                "BEAS-2B"
            ],
            "contactPoint": {
                "fn": "Brian Chorley",
                "hasEmail": "mailto:chorley.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "Datasetsubmission for A-rr5j.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374989/Datasetsubmission%20for%20A-rr5j.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-13",
            "references": [
                "https://doi.org/10.3791/55911",
                "https://www.jove.com/video/55911/procedure-key-optimization-strategies-for-an-automated-capillary"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data Summary Table for The effects of continuous diazinon exposure on growth and reproduction in Japanese medaka using a modified Medaka Extended One Generation Reproduction Test",
            "description": "Summary data from a Medaka Extended One Generation Reproduction Test (MEOGRT) that assessed the effects of diazinon on growth and reproduction on Japanese medaka.  The data includes fecundity, fertility, hatch, time-to-hatch, various measurements of growth, and counts of anal fin papillae for two generations of medaka. \n\nThis dataset is associated with the following publication:\nFlynn, K., D. Lothenbach, F. Whiteman, D. Hammermeister, J. Swintek, M. Etterson, and R. Johnson. The effects of continuous diazinon exposure on growth and reproduction in Japanese medaka using a modified Medaka Extended One Generation Reproduction Test (MEOGRT).   ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY. Elsevier Science Ltd, New York, NY, USA, 162: 438-445, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1413672",
            "keyword": [
                "aquatic toxicity",
                "growth curve",
                "pesticide",
                "fish"
            ],
            "contactPoint": {
                "fn": "Kevin Flynn",
                "hasEmail": "mailto:flynn.kevin@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data Summary Table 2.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413672/Data%20Summary%20Table%202.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2015-12-31",
            "references": [
                "https://doi.org/10.1016/j.ecoenv.2018.06.088"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Ozone-induced changes in pulmonary metabolites in Humans",
            "description": "Dataset contains a list of metabolites, their fold change after ozone exposure and a p value for that change. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: This dataset can be accessed by contacting Dr. Robert Devlin (devlin.rober@epa.gov). Format: The dataset was sent to us by the company (Metabolon) that did the metabolite analysis, including the statistical analysis).   It is an excel spreadsheet that contains a row for each of the metabolites that were identified, fold changes in each metabolite after air and ozone exposure (and the p value of the ozone-induced change), and the pathway and superpathway to which each metabolite belongs. \n\nThis dataset is associated with the following publication:\nCheng, W., K. Duncan, A. Ghio, C. Ward-Caviness, E. Karoly, D. Diaz-Sanchez, R. Conolly, and R. Devlin. Changes in metabolites present in lung-lining fluid following exposure to humans to ozone.   TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA,  163(2): 430-439, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1376675",
            "keyword": [
                "Ozone",
                "human metabolome",
                "pulmonary",
                "DNA methylation"
            ],
            "contactPoint": {
                "fn": "Robert Devlin",
                "hasEmail": "mailto:devlin.robert@epa.gov"
            },
            "distribution": [],
            "modified": "2016-06-01",
            "references": [
                "https://doi.org/10.1093/toxsci/kfy043"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Zinc speciation results",
            "description": "The dataset contains two figures showing the synchrotron X-ray absorption near edge structure data (figure 4) and corresponding linear combination fitting data deciphering the distribution of zinc species (figure 5). \n\nThis dataset is associated with the following publication:\nDoolette, C., T. Lund, C. Li, K. Scheckel, E. Donner, P. Kopittke, E. Lombi, and J. Schjoerring. Foliar application of zinc sulphate and zinc EDTA to wheat leaves: differences in mobility, distribution, and speciation.   JOURNAL OF EXPERIMENTAL BOTANY. Oxford University Press, Cary, NC, USA, 69(18): 4469-4481, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1435029",
            "keyword": [
                "zinc",
                "plant uptake",
                "nutrient enrichment",
                "contaminant transport",
                "synchrotron speciation"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "JXB Figures 4 and 5_final.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435029/JXB%20Figures%204%20and%205_final.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2018-01-25",
            "references": [
                "https://doi.org/10.1093/jxb/ery236"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Ozone-Induced Vascular Contractility and Pulmonary Injury are Differentially Impacted by Diets Enriched with Coconut Oil, Fish Oil, and Olive Oil",
            "description": "This data set is broken up into 2 Excel files.  In one file are all the data pertaining to the vascular and pulmonary effects of ozone exposure in rats fed either a normal diet or diet enriched with coconut oil, fish oil, or olive oil.  The different tabs of the spreadsheet pertain to each figure or table found in the manuscript.  This file was updated on 12/7/17 to reflect changes to Figure 3 in response to reviewers comments following submission to Toxicological Sciences.  In the second file is all the data for Figure 8 pertaining to the global microRNA assessment. \n\nThis dataset is associated with the following publication:\nSnow, S., W. Cheng, A. Henriquez, M. Hodge, V. Bass, G. Nelson, G. Carswell, J. Richards, M. Schladweiler, A. Ledbetter, B. Chorley, K. Gowdy, H. Tong, and U. Kodavanti. Ozone-Induced Vascular Contractility and Pulmonary Injury are Differentially Impacted by Diets Enriched with Coconut Oil, Fish Oil, and Olive Oil.   TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA,  163(1): 57-69, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1375318",
            "keyword": [
                "Ozone",
                "pulmonary injury",
                "vascular contractility",
                "fish oil",
                "dietary supplements"
            ],
            "contactPoint": {
                "fn": "Samantha Snow",
                "hasEmail": "mailto:snow.samantha@epa.gov"
            },
            "distribution": [
                {
                    "title": "miRNA Analysis for OzoneDiets Vascular Pulmonary Manuscript.XLSX",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375318/miRNA%20Analysis%20for%20OzoneDiets%20Vascular%20Pulmonary%20Manuscript.XLSX",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://www.ncbi.nlm.nih.gov/geo/",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/geo/"
                },
                {
                    "title": "OzoneDiets Vascular and Pulmonary Manuscript - Data for ScienceHub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1375318/OzoneDiets%20Vascular%20and%20Pulmonary%20Manuscript%20-%20Data%20for%20ScienceHub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-31",
            "references": [
                "https://doi.org/10.1093/toxsci/kfy003"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Table formatted data for Figures 1, 2, 3, 4, 5, and 6 regarding point of zero charge",
            "description": "This study utilized the Pb- and As-contaminated soils to determine the combined effect of pH with respect to PZC and different rates of P-application on pyromorphite formation, and Pb and arsenic (As) bioaccessibility as impacted by speciation changes. Solution chemistry analysis along with synchrotron-based Pb- and As-speciation, and bioaccessibility treatment effect ratios (TERs) were conducted. \n\nThis dataset is associated with the following publication:\nKarna, R., M. Noerpel, T. Luxton, and K. Scheckel. Point of Zero Charge: Role in Pyromorphite Formation and Bioaccessibility of Lead and Arsenic in Phosphate-Amended Soils.   Soil Systems. MDPI AG, Basel,  SWITZERLAND, 2(2): 22, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1435031",
            "keyword": [
                "lead",
                "arsenic",
                "in-situ amendments",
                "metal bioavailability",
                "synchrotron speciation"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Table for Fig. 1a,1b,1c,1d.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435031/Table%20for%20Fig.%201a%2C1b%2C1c%2C1d.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table for Fig. 5a,5b,5c,5d.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435031/Table%20for%20Fig.%205a%2C5b%2C5c%2C5d.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table for Fig.3.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435031/Table%20for%20Fig.3.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table for Fig. 2a,2b,2c,2d.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435031/Table%20for%20Fig.%202a%2C2b%2C2c%2C2d.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table for Fig. 6a,6b,6c,6d.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435031/Table%20for%20Fig.%206a%2C6b%2C6c%2C6d.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Table for Fig.4.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435031/Table%20for%20Fig.4.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-03-28",
            "references": [
                "https://doi.org/10.3390/soilsystems2020022"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "June 2018 version of dataset",
            "description": "These are the data associated with each of the figures in the publication. \n\nThis dataset is associated with the following publication:\nThursby, G., K. Sappington, and M. Etterson. Coupling Toxicokinetic-Toxicodynamic and Population Models for Assessing Aquatic Ecological Risks to Time-Varying Pesticide Exposures.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(10): 2633-2644, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1502454",
            "keyword": [
                "Americamysis bahia",
                "matrix modeling",
                "population level risk assessment",
                "time-varying exposures"
            ],
            "contactPoint": {
                "fn": "Glen Thursby",
                "hasEmail": "mailto:thursby.glen@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHub for ORD-023077 June 2018.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502454/ScienceHub%20for%20ORD-023077%20June%202018.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-06-26",
            "references": [
                "https://doi.org/10.1002/etc.4224"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "RNA-sequencing analysis of Douglas-fir transcriptome responses to diesel emissions generated with CeO2 nanoparticle additive",
            "description": "Transcriptome changes of Douglas-fir seedlings were analyzed to investigate molecular impacts of exposure to airborne emissions released from combustion of diesel fuel containing engineered cerium dioxide (CeO2) nanoparticle catalysts (DECe). We analyzed mRNA-sequencing data from exposed one-year-old needles. Our hypothesis is that 2-week chamber exposure to DECe would induce certain distinct transcriptome changes in the needles compared with responses to conventional diesel exhaust (DE) or filtered DECe Gas Phase. Blast2GO gene ontologies (GOs) enriched by significantly up-regulated DECe transcripts were nested within the GOs for DE, however, 93.5% of enriched GOs for significantly down-regulated DECe transcripts were unique. DECe attenuated expression of genes that affect functions of transferases, kinases, transmembrane transporters, transcription factors, diester hydrolases and RNA polymerase III; processes of protein phosphorylation, responses to stimuli, hormones and chemicals, carbohydrate transport, RNA polymerase III transcription, and cellular anion homeostasis; plus, components of the plasma membrane. MapMan analysis also identified RNA regulation of transcription, protein degradation, and lipid metabolism pathways that were enriched with DECe down-regulated transcripts. Divergent DECe treatment effects were associated with significantly elevated needle uptake of cerium. DE affected expression of more genes than DECe. Nevertheless, unique transcriptome profile changes suggest that chronic DECe exposure may adversely affect plant growth and development. \n\nThis dataset is associated with the following publication:\nReichman, J.R., P.T. Rygiewicz, M.G. Johnson, M.A. Bollman, B.M. Smith, Q.T. Krantz, C.J. King, K. Kovalcik, and C.P. Andersen. Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) Transcriptome Profile Changes Induced by Diesel Emissions Generated with CeO2 Nanoparticle Fuel Borne Catalyst.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(17): 10067-10077, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1422729",
            "keyword": [
                "RNA-sequencing",
                "transcriptome",
                "cerium dioxide",
                "fuel borne catalyst",
                "Douglas-fir",
                "Pseudotsuga menziesii",
                "ammonium nitrate",
                "intergenerational effects",
                "isotope",
                "isotopic discrimination",
                "nitrogen",
                "engineered nanomaterials (ENMs)"
            ],
            "contactPoint": {
                "fn": "Christian Andersen",
                "hasEmail": "mailto:andersen.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107902",
                    "accessURL": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107902"
                },
                {
                    "title": "Reichman et al 2018 metadata 022718.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1422729/Reichman%20et%20al%202018%20metadata%20022718.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-12-12",
            "references": [
                "https://doi.org/10.1021/acs.est.8b02169"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Sequencing Data for Hospital Metagenomes",
            "description": "FASTA files containing the sequence data and for Assembled contigs (FastA), Predicted genes (FastA), Predicted proteins (FastA), Gene prediction (GFF v2). This dataset is not publicly accessible because: These are sequences that have already been deposited in publicly available databases and therefore we can avoid replication. Also the data is quite large and there are numerous files associated with these entries, which are included in the links below. It can be accessed through the following means: Using the following web links\n\nhttps://www.ncbi.nlm.nih.gov/bioproject/PRJNA299404\t\nhttps://trace.ncbi.nlm.nih.gov/Traces/sra/?study=SRP065069\nhttp://enve-omics.ce.gatech.edu/data/showerheads. Format: The data represent genome sequencing and assembly of 180 different contigs. \n\nThis dataset is associated with the following publication:\nSoto-Giron, M.J., L. Rodriguez, C. Luo , M. Elk, H. Ryu, J. Santodomingo , and K. Konstantinidis. Biofilms on Hospital Shower Hoses: Characterization and Implications for Nosocomial Infections.   APPLIED AND ENVIRONMENTAL MICROBIOLOGY. American Society for Microbiology, Washington, DC, USA, 82(9): 2872-2883, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503087",
            "keyword": [
                "drinking water",
                "metagenomes",
                "hosppital",
                "shower hoses"
            ],
            "contactPoint": {
                "fn": "Jorge Santo Domingo",
                "hasEmail": "mailto:santodomingo.jorge@epa.gov"
            },
            "distribution": [],
            "modified": "2016-12-05",
            "references": [
                "https://doi.org/10.1128/aem.03529-15"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "XRD Raw data",
            "description": "XRD Raw data collected. \n\nThis dataset is associated with the following publication:\nNadagouda , M., C. Han , D. Dionysiou, and L. Wang. An innovative zinc oxide-coated zeolite adsorbent for removal of humic acid.   JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, USA, 313: 283-290, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1503092",
            "keyword": [
                "Electrostatic interaction; Humic acid; Water treatment; Zeolite; Zinc oxide; Natural organic matter"
            ],
            "contactPoint": {
                "fn": "Mallikarjuna Nadagouda",
                "hasEmail": "mailto:nadagouda.mallikarjuna@epa.gov"
            },
            "distribution": [
                {
                    "title": "XRD.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503092/XRD.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-10-17",
            "references": [
                "http://www.sciencedirect.com/science/article/pii/S0304389416302928"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Zipped NetCDF data for Precipitation partitioning in Multi-Scale Atmospheric Simulations: Impacts of Stability Restoration Methods  ",
            "description": "Data for all figures in NetCDF format zipped files. \n\nThis dataset is associated with the following publication:\nHe, J., and K. Alapaty. Precipitation Partitioning in Multiscale Atmospheric Simulations: Impacts of Stability Restoration Methods.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 123(18): 10,185-10,201, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1407606",
            "keyword": [
                "precipitation",
                "convective timescale",
                "measurements",
                "deep convection",
                "convective parameterization"
            ],
            "contactPoint": {
                "fn": "Kirankumar Alapaty",
                "hasEmail": "mailto:alapaty.kiran@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/EPADataCommons/ORD/dynTauData/",
                    "accessURL": "https://gaftp.epa.gov/EPADataCommons/ORD/dynTauData/"
                }
            ],
            "modified": "2017-08-17",
            "references": [
                "https://doi.org/10.1029/2018jd028710"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Figure. 2 Data . CUOG wastewater dilution as a function of specific conductivity.",
            "description": "Application of ICP-OES for evaluating energy extraction and production wastewater discharge impacts on surface waters in\r\nWestern Pennsylvania Figure 2 data (Pancras et al., Science of the Total Environment 529 (2015) 21\u201329). \n\nThis dataset is associated with the following publication:\nPancras, J.P., G. Norris , M. Landis , K. Kovalcik , J.K. McGee , and A. Kamal. Application of ICP-OES for Evaluating Energy Extraction and Production Wastewater Discharge Impacts on Surface Waters in Western Pennsylvania.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 529: 21-29, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407512",
            "keyword": [
                "ICP-OES",
                "Oil and Gas Wastewater",
                "Elemental composition",
                "Flue Gas Desulfurization",
                "hydraulic fracturing"
            ],
            "contactPoint": {
                "fn": "Gary Norris",
                "hasEmail": "mailto:norris.gary@epa.gov"
            },
            "distribution": [
                {
                    "title": "Figure 2 Data_HF paper.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407512/Figure%202%20Data_HF%20paper.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-12-04",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "weights of metal coupons before and after fumigation with methyl bromide or methyl iodide",
            "description": "This file contains the masses of metal coupons before and after fumigation with methyl bromide or methyl iodide. \n\nThis dataset is associated with the following publication:\nLee, S., S. Serre, A. Adrion, and R. Scheffrahn. Impact of Sporicidal Fumigation with Methyl Bromide or Methyl Iodide on Electronic Equipment.   JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 231: 1021-1027, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1413129",
            "keyword": [
                "Sporicidal Fumigation",
                "methyl bromide",
                "Methyl Iodide",
                "Material Compatibility"
            ],
            "contactPoint": {
                "fn": "Sangdon Lee",
                "hasEmail": "mailto:lee.sangdon@epa.gov"
            },
            "distribution": [
                {
                    "title": "2017_03_28_coupon_weights.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413129/2017_03_28_coupon_weights.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-12-13",
            "references": [
                "https://doi.org/10.1016/j.jenvman.2018.10.118"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "diagnostic test results of computers after fumigation with methyl bromide or methyl iodide",
            "description": "These files contain the results of diagnostic testing (BurnIn Test and PC-Dr) of computers after fumigation with methyl bromide or methyl iodide. \n\nThis dataset is associated with the following publication:\nLee, S., S. Serre, A. Adrion, and R. Scheffrahn. Impact of Sporicidal Fumigation with Methyl Bromide or Methyl Iodide on Electronic Equipment.   JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 231: 1021-1027, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1413130",
            "keyword": [
                "Sporicidal Fumigation",
                "methyl bromide",
                "Methyl Iodide",
                "Material Compatibility"
            ],
            "contactPoint": {
                "fn": "Sangdon Lee",
                "hasEmail": "mailto:lee.sangdon@epa.gov"
            },
            "distribution": [
                {
                    "title": "combined_monthly_summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413130/combined_monthly_summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "first_6_weeks_post_fumigation.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413130/first_6_weeks_post_fumigation.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "combined_monthly.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413130/combined_monthly.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "BIT_data_processed.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413130/BIT_data_processed.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-12-14",
            "references": [
                "https://doi.org/10.1016/j.jenvman.2018.10.118"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "temperature, relative humidity, and fumigant concentration during fumigation of computers with methyl bromide or methyl iodide and the effect of fumigant on humidity sensors",
            "description": "These files contain time-course data for temperature, relative humidity, and fumigant concentration during the fumigation of computers with methyl bromide or methyl iodide. There is a also a file that shows the effect of fumigation on the sensitivity of the HOBO-U10 RH sensor. \n\nThis dataset is associated with the following publication:\nLee, S., S. Serre, A. Adrion, and R. Scheffrahn. Impact of Sporicidal Fumigation with Methyl Bromide or Methyl Iodide on Electronic Equipment.   JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 231: 1021-1027, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1413137",
            "keyword": [
                "Sporicidal Fumigation",
                "methyl bromide",
                "Methyl Iodide",
                "Material Compatibility"
            ],
            "contactPoint": {
                "fn": "Sangdon Lee",
                "hasEmail": "mailto:lee.sangdon@epa.gov"
            },
            "distribution": [
                {
                    "title": "bulk_chamber_T_RH_during_fumigation.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413137/bulk_chamber_T_RH_during_fumigation.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "inside_computers_T_RH_during_fumigation.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413137/inside_computers_T_RH_during_fumigation.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "effect_on_HOBO_loggers.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413137/effect_on_HOBO_loggers.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "2017_MB_MI_comp_spectros_readings.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1413137/2017_MB_MI_comp_spectros_readings.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-12-14",
            "references": [
                "https://doi.org/10.1016/j.jenvman.2018.10.118"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The Impacts of Potassium Permanganate and Powdered Activated Carbon on Cyanobacterial Toxin Release and Degradation",
            "description": "Underlying data for figures in the published manuscript. \n\nThis dataset is associated with the following publication:\nDugan, N., S. Smith, and T. Sanan. The Impacts of Potassium Permanganate and Powdered Activated Carbon on Cyanotoxin Release.   Journal AWWA. American Water Works Association, Denver, CO, USA, 110(11): E31-E42, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1394644",
            "keyword": [
                "cyanobacteria",
                "toxin",
                "microcystin",
                "microcystis aeruginosa",
                "drinking water treatment",
                "oxidation",
                "potassium permanganate",
                "activated carbon"
            ],
            "contactPoint": {
                "fn": "Nicholas Dugan",
                "hasEmail": "mailto:dugan.nicholas@epa.gov"
            },
            "distribution": [
                {
                    "title": "DuganNicholas_A-vq8v_Dataset_Combined.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394644/DuganNicholas_A-vq8v_Dataset_Combined.txt",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2017-09-08",
            "references": [
                "https://doi.org/10.1002/awwa.1125"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1394644/documents/DuganNicholas_A-vq8v_Dataset_Data_Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Plume encounters that exhibited elevated levels of at least one of the three reactive bromine compounds (Br2, BrNO2, and BrCl). ",
            "description": "Plume encounters that exhibited elevated levels of at least one of the three reactive bromine compounds (Br2, BrNO2, and BrCl). \n\nThis dataset is associated with the following publication:\nLee, B., F. Lopez-Hilfiker, J. Schroder, P. Campuzano-Jost, J. Jimenez, E. McDuffie, D. Fibiger, P. Veres, S. Brown, T. Campos, A. Weinheimer, F. Flocke, G. Norris, K. O'Mara, J. Green, M. Fiddler, S. Bililign, V. Shah, L. Jaegl\u00e9, and J. Thornton. Airborne Observations of Reactive Inorganic Chlorine and Bromine Species in the Exhaust of Coal\u2010Fired Power Plants.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 123(19): 11,225-11,237, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1500925",
            "keyword": [
                "bromine",
                "plume",
                "aircraft",
                "coal"
            ],
            "contactPoint": {
                "fn": "Gary Norris",
                "hasEmail": "mailto:norris.gary@epa.gov"
            },
            "distribution": [
                {
                    "title": "Plume encounters with bromine.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500925/Plume%20encounters%20with%20bromine.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2018-06-05",
            "references": [
                "https://doi.org/10.1029/2018jd029284"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset: An Integrated Multidisciplinary Research Project Researching Questions of Ecosystem Services and Ecological Receptor Characterization in the Kanawha",
            "description": "GIS data associated with hydrogeomorphic variables measured from remotely sensed coverages of the Little Miami River, Ohio. \n\nThis dataset is associated with the following publication:\nThoms, M., M. Scown, and J. Flotemersch. Characterization of River Networks: A GIS Approach and Its Applications.   JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION. American Water Resources Association, Middleburg, VA, USA, 54(4): 899-913, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1424213",
            "keyword": [
                "functional process zones",
                "RESonate",
                "hydrogeomorphic measures",
                "Hydro-geomorphic diversity",
                "Hierarchy",
                "Multivariate analyses"
            ],
            "contactPoint": {
                "fn": "Joseph Flotemersch",
                "hasEmail": "mailto:flotemersch.joseph@epa.gov"
            },
            "distribution": [
                {
                    "title": "Thoms et al. _A-x3g7_Data_20180320.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1424213/Thoms%20et%20al.%20_A-x3g7_Data_20180320.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-10-01",
            "references": [
                "https://doi.org/10.1111/1752-1688.12649"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "QCL data turf microcosms 09Aug2017",
            "description": "Four turfgrass systems in or near the Pinehurst Resort and Country Club, Sandhills region, North Carolina, USA was sampled. Twenty intact soil cores (5 cm diameter x 10 cm length) were collected from each turfgrass system in January and August 2016, respectively. For each turfgrass system, a total of 12 intact soil cores were used to measure N effluxes during three-week incubation, representing three replicates and four treatments: (1) no N input and 23 \u00b0C, (2) low N input (i.e., addition of 5.9 mg N as NH4NO3, equivalent to 30 kg N ha-1) and 23 \u00b0C, (3) high N input (i.e., addition of 11.8 mg N as NH4NO3, equivalent to 60 kg N ha-1) and 23 \u00b0C, and (4) high N input and 13 \u00b0C for winter samples (or 33 \u00b0C for summer samples). On day 0, water and NH4NO3 solution were added to the respective soil cores to bring soil moisture to 60% water filled pore space (WFPS). Here, we estimated soil bulk density and moisture content from the other eight intact soil cores and then calculated soil porosity assuming that soil particle density was 2.65 g cm-3. These soil cores were also used for soil pH measurement. \nSoil N2O and CO2 effluxes were measured almost daily via soil cores closed for 2 h and then 30-ml gas samples withdrawn from headspaces using gas-tight push button syringes with one-way luer stopcocks. On day 4, 11, and 18, roughly 80 ml leachate was collected from each soil core after 80 ml distilled water poured slowly to soil surface, drained up to 2 h, and then vacuum pumped out. Nitrous oxide was measured using a dual quantum cascade laser (QCL) N2O measurement system (Model CWQCL-200-D, Aerodyne, Billerica, MA, USA) (Chen et al., 2016). The efflux rate of N2O (\u00b5g m-2 h-1) was calculated as: ((Csample-Cair) \u00d7 M \u00d7 V) / (r \u00d7 m \u00d7 t), where Csample and Cair are the N2O concentrations in the headspace of intact soil core and ambient air (ppbv), respectively; V is the volume of intact soil core headspace (L); M is the molar mass of N2O (g mol-1); r is the molar volume at 1 atm (23.47 L mol-1 at 13 oC, 24.29 L mol-1 at 23 oC, and 25.11 L mol-1 at 33 oC), m is soil core surface area (m2), and t is the incubation time (h). \nThe QCL system also provided the mixing ratio of natural abundance of 15N in the center and edge position of N2O, i.e., 15N\u03b1 and 15N\u03b2, respectively. After normalized to total N2O-N concentration, these ratios were used to calculate the natural abundance of 15N\u03b1 and 15N\u03b2 of N2O. Then, 15N site preference was estimated by \u03b415N\u03b1 - \u03b415N\u03b2 and used to help probe the biological source of N2O efflux. \n\nThis dataset is associated with the following publication:\nChen, H., T. Yang, Q. Xia, D. Bowman, D. Williams, J. Walker, and W. Shi. The extent and pathways of nitrogen loss in turfgrass systems: Age impacts.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 637638: 746-757, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1425459",
            "keyword": [
                "Reactive N",
                "Soluble organic N",
                "temperature",
                "Turfgrass",
                "Chronosequence"
            ],
            "contactPoint": {
                "fn": "David Williams",
                "hasEmail": "mailto:williams.davidj@epa.gov"
            },
            "distribution": [
                {
                    "title": "QCl turk data.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1425459/QCl%20turk%20data.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-08-25",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.05.053"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1425459/documents/data%20dictionary%20N2O%20chamber%20data.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Influence of uncertainties in burned area estimates on modeled wildland fire PM2.5 and ozone pollution in the contiguous U.S.",
            "description": "Data files used in manuscript - \"Influence of burned area uncertainties on modeled wildland fire PM2.5 and ozone pollution in the contiguous U.S.\". \n\nThis dataset is associated with the following publication:\nKoplitz, S., C. Nolte, G. Pouliot, J. Vukovich, and J. Beidler. Influence of uncertainties in burned area estimates on modeled wildland fire PM2.5 and ozone pollution in the contiguous U.S..   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 191: 328-339, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1430830",
            "keyword": [
                "wildland fires",
                "burned area",
                "pm2.5",
                "Ozone",
                "CMAQ"
            ],
            "contactPoint": {
                "fn": "Shannon Koplitz",
                "hasEmail": "mailto:koplitz.shannon@epa.gov"
            },
            "distribution": [
                {
                    "title": "cmaq_for_BA_cmpr_20180814.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1430830/cmaq_for_BA_cmpr_20180814.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-08-13",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2018.08.020"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Assessing threats of non-native species to native freshwater biodiversity: Conservation priorities for the United States",
            "description": "Non-native species pose one of the greatest threats to native biodiversity, and may have particularly severe negative impacts in freshwater ecosystems. Identifying regions of spatial overlap between high freshwater biodiversity value and elevated stress associated with non-native species can thus inform the determination of conservation priorities. Here we employ geospatial analysis of species distribution data at the watershed scale, extracted from publicly available databases, to investigate the potential threat of non-native species to vulnerable aquatic animal taxa across the continental United States. We mapped non-native aquatic plant and animal species richness and an index of cumulative invasion pressure, which weights non-native richness by time since introduction in order to estimate overall negative impact associated with species introductions. These distributions were compared to distributions of native aquatic animal taxa (fish, amphibians, mollusks, and decapods) derived from the International Union for the Conservation of Nature (IUCN) database. To identify hotspots of native biodiversity value we mapped overall species richness, proportion of species listed by IUCN as threatened and endangered, and a community index of species rarity calculated at the watershed scale. An overall priority index allowed identification of watersheds experiencing high pressure from non-native species and also exhibiting high native biodiversity conservation value. While these priority regions are roughly consistent with previously reported attempts to map biodiversity conservation needs across the US, we also recognize novel priority areas characterized by moderate-to-high native diversity but extremely high invasion pressure. We further explore the utility of this approach by comparing priority areas with existing conservation protections as well as projected future threats associated with land use change. Our findings suggest that many regions of elevated freshwater biodiversity value are compromised by high invasion pressure, and also may be poorly safeguarded by existing conservation mechanisms and likely to experience significant additional stresses in the future. \n\nThis dataset is associated with the following publication:\nPanlasigui, S., A. Davis, M. Mangiante, and J. Darling. Assessing threats of non-native species to native freshwater biodiversity: Conservation priorities for the United States.   BIOLOGICAL CONSERVATION. Elsevier Science Ltd, New York, NY, USA, 224: 199-208, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1407599",
            "keyword": [
                "freshwater biodiversity",
                "priority mapping",
                "invasive species",
                "non-indigenous aquatic species",
                "biodiversity",
                "threatened and endangered species",
                "geospatial analysis",
                "EnviroAtlas"
            ],
            "contactPoint": {
                "fn": "John Darling",
                "hasEmail": "mailto:darling.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "MASTER_wPriorityIndex_HUC8_v3_variabledictionary.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407599/MASTER_wPriorityIndex_HUC8_v3_variabledictionary.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "MASTER_wPriorityIndex_HUC8_v3.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407599/MASTER_wPriorityIndex_HUC8_v3.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "NativeExtantRichnessAndRarity_HUC8.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407599/NativeExtantRichnessAndRarity_HUC8.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "NativeExtantRichnessAndRarity_HUC8_variabledictionary.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407599/NativeExtantRichnessAndRarity_HUC8_variabledictionary.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "nonNativeRich_HUC12.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407599/nonNativeRich_HUC12.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "nonNativeRich_HUC12_variabledictionary.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407599/nonNativeRich_HUC12_variabledictionary.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-08-10",
            "references": [
                "https://doi.org/10.1016/j.biocon.2018.05.019"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CPDat 2017",
            "description": "This dataset represents quantitative data on product chemical composition for >75,000 chemicals contained in >15,000 consumer products. The dataset provided at the FigShare link is fully described in the associated Scientific Data publication (Dionisio et al.). The dataset is presented in the form of a MySQL relational database, which mimics CPDat data available under the 'Exposure' tab of the CompTox Chemistry Dashboard (https://comptox.epa.gov/dashboard). \n\nThis dataset is associated with the following publication:\nDionisio, K., K. Phillips, P. Price, C. Grulke, A. Williams, D. Biryol, T. Hong, and K. Isaacs. The Chemical and Products Database, a resource for exposure-relevant data on chemicals in consumer products.   Scientific Data. Springer Nature Group, New York, NY,  5: 180125, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1434276",
            "keyword": [
                "consumer products",
                "Exposure modeling",
                "chemical exposure",
                "high-throughput",
                "product composition"
            ],
            "contactPoint": {
                "fn": "Kathie Dionisio",
                "hasEmail": "mailto:dionisio.kathie@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://figshare.com/articles/The_Chemical_and_Products_Database_CPDat_MySQL_Data_File/5352997",
                    "accessURL": "https://figshare.com/articles/The_Chemical_and_Products_Database_CPDat_MySQL_Data_File/5352997"
                }
            ],
            "modified": "2017-10-13",
            "references": [
                "https://doi.org/10.1038/sdata.2018.125"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Human Health Impact of Cross-Connections in Non-potable Reuse Systems",
            "description": "Provides estimated event risks and target dilution fractions for cross-connections in non-potable reuse systems. \n\nThis dataset is associated with the following publication:\nSchoen, M., M. Jahne, and J. Garland. Human Health Impact of Cross-Connections in Non-Potable Reuse Systems.   WATER. MDPI AG, Basel,  SWITZERLAND, 10(10): 1352, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503067",
            "keyword": [
                "QMRA",
                "cross-connection",
                "onsite",
                "non-potable",
                "reclaimed",
                "wastewater"
            ],
            "contactPoint": {
                "fn": "Michael Jahne",
                "hasEmail": "mailto:jahne.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Dataset.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503067/Dataset.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-08-16",
            "references": [
                "https://doi.org/10.3390/w10101352"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Regional Similarities and NOx-related Increases in Biogenic Secondary Organic Aerosol in Summertime Southeastern U.S.",
            "description": "Data set contains CMAQ model output for Look Rock, Tennessee and Centreville, Alabama during summer 2013. \n\nThis dataset is associated with the following publication:\nLiu, J., L. Russell, G. Ruggeri, S. Takahama, M. Claflin, P. Ziemann, H. Pye, B. Murphy, L. Xu, N. Ng, K. McKinney, S. Hapsari Budisulistiorini, T. Bertram, A. Nenes, and J. Surratt. Regional Similarities and NOx\u2010Related Increases in Biogenic Secondary Organic Aerosol in Summertime Southeastern United States.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 123(18): 10,620-10,636, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434258",
            "keyword": [
                "SOAS",
                "CMAQ",
                "SOA",
                "Aerosol",
                "PM2.5 air quality modeling",
                "NOx",
                "FTIR"
            ],
            "contactPoint": {
                "fn": "Havala Pye",
                "hasEmail": "mailto:pye.havala@epa.gov"
            },
            "distribution": [
                {
                    "title": "20170406.11Aug2016svpoaisop.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434258/20170406.11Aug2016svpoaisop.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "https://github.com/USEPA/CMAQ",
                    "accessURL": "https://github.com/USEPA/CMAQ"
                },
                {
                    "title": "https://esrl.noaa.gov/csd/groups/csd7/measurements/2013senex/",
                    "accessURL": "https://esrl.noaa.gov/csd/groups/csd7/measurements/2013senex/"
                }
            ],
            "modified": "2017-04-06",
            "references": [
                "https://doi.org/10.1029/2018jd028491"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Trends in non-native aquatic species richness in the United States reveal shifting patterns of both species introductions and sampling effort",
            "description": "Analysis of spatio-temporal trends in non-native species distributions across the continental United States, based on publicly available distribution data. \n\nThis dataset is associated with the following publication:\nMangiante, M., A. Davis, S. Panlasigui, M. Neilson, I. Pfingsten, P. Fuller, and J. Darling. Trends in nonindigenous aquatic species richness in the United States reveal shifting spatial and temporal patterns of species introductions.   Aquatic Invasions. Regional Euro-Asian Biological Invasions Centre, Helsinki,  FINLAND, 13(3): 323-338, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1407566",
            "keyword": [
                "Aquatic invasive species",
                "non-native species richness",
                "sampling effort",
                "temporal trends",
                "non-indigenous aquatic species",
                "biodiversity",
                "threatened and endangered species",
                "geospatial analysis",
                "EnviroAtlas"
            ],
            "contactPoint": {
                "fn": "John Darling",
                "hasEmail": "mailto:darling.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "Animals_DB_conus.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407566/Animals_DB_conus.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "AIS_native_ranges.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407566/AIS_native_ranges.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Plants_DB_conus.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407566/Plants_DB_conus.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "variable_dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407566/variable_dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-06-14",
            "references": [
                "https://doi.org/10.3391/ai.2018.13.3.02"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Construction and Demolition Debris 2014 Final Disposition Estimates Using the CDDPath Method v2",
            "description": "Estimates of the final amount and final disposition of materials generated in the Construction and Demolition waste stream measured in total mass of each material. Traditional C&D materials included are concrete, asphalt pavement, asphalt shingles, bricks and clay, metal, wood, and gypsum drywall. Non-traditional materials in this stream include cardboard, organics, carpet, glass, plastic, and fines. The estimates are based on generation amounts described in the EPA SMM Facts and Figures reports. The method used to estimate final disposition is called CDDpath. \n\nThis dataset is associated with the following publication:\nTownsend, T., W. Ingwersen, B. Niblick, P. Jain, and J. Wally. CDDPath: A method for quantifying the loss and recovery of construction and demolition debris in the United States.   WASTE MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 84: 302-309, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1503167",
            "keyword": [
                "Concrete",
                "asphalt pavement",
                "Wood",
                "bricks",
                "carpet",
                "plastic",
                "asphalt shingles",
                "mixed CDD MRF",
                "recycling estimates",
                "metal",
                "drywall",
                "Sustainable materials management",
                "construction and demolition debris",
                "life cycle assessment",
                "end-of-life management"
            ],
            "contactPoint": {
                "fn": "Briana Niblick",
                "hasEmail": "mailto:niblick.briana@epa.gov"
            },
            "distribution": [
                {
                    "title": "CDD_2014_US_Disposition_Estimates_Using_CDDPath_v2.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503167/CDD_2014_US_Disposition_Estimates_Using_CDDPath_v2.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-11-07",
            "references": [
                "https://doi.org/10.1016/j.wasman.2018.11.048"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for the journal article \"Preparation of water-selective polybutadiene membranes and their use in drying\" ACS Sustainable Chemistry & Engineering, 4, 4442-4450 (2016)",
            "description": "The dataset is supporting information containing experimental details, data, and reduced data for figures and tables presented in the journal article \"Preparation of water-selective polybutadiene membranes and their use in drying alcohols by pervaporation and vapor permeation technologies\" ACS Sustainable Chemistry & Engineering, 4, 4442-4450 (2016). \n\nThis dataset is associated with the following publication:\nVane, L., V. Namboodiri, G. Lin, M. Abar, and F. Alvarez. Preparation of Water-Selective Polybutadiene Membranes and Their Use in Drying Alcohols by Pervaporation and Vapor Permeation Technologies.   SCIENCE. American Association for the Advancement of Science (AAAS), Washington, DC, USA, 4(8): 4442-4450, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1503078",
            "keyword": [
                "organic solvents",
                "solvents",
                "membranes",
                "recovery",
                "pervaporation",
                "vapor permeation",
                "reclamation"
            ],
            "contactPoint": {
                "fn": "Leland Vane",
                "hasEmail": "mailto:vane.leland@epa.gov"
            },
            "distribution": [
                {
                    "title": "Supporting Info sc6b01072_si_001.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503078/Supporting%20Info%20sc6b01072_si_001.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2016-09-20",
            "references": [
                "https://doi.org/10.1021/acssuschemeng.6b01072"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset of Chemosphere Publication in 2015, Chamber study of PCB emissions from caulking materials and light ballasts ",
            "description": "The data presented in this data file is a product of a journal publication. The dataset contains PCB chamber air concentrations emitted from caulk and model simulation of PCB air concentrations in a room with a PCB caulk. \n\nThis dataset is associated with the following publication:\nLiu , X., Z. Guo, K. Krebs , R. Stinson, J. Nardin, R. Pope, and N. Roache. Chamber study of polychlorinated biphenyl (PCB)emissions from caulking materials and light ballasts.   ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH. Ecomed Verlagsgesellschaft AG, Landsberg,  GERMANY, 137: 115-121, (2015).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390116",
            "keyword": [
                "PCBs",
                "air concentration",
                "Polychlorinated biphenyls (PCBs)",
                "Aroclor",
                "Chamber testing",
                "Source emissions",
                "Caulking materials"
            ],
            "contactPoint": {
                "fn": "Xiaoyu Liu",
                "hasEmail": "mailto:liu.xiaoyu@epa.gov"
            },
            "distribution": [
                {
                    "title": "XiaoyuLiu_A-9cnx_Data Tables&Dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390116/XiaoyuLiu_A-9cnx_Data%20Tables%26Dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-12",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2015.05.102"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset of Chemosphere Publication in 2016, Laboratory study of PCB transport from primary sources to settled dust",
            "description": "The data presented in this data file is a product of a journal publication. The dataset contains PCB sorption concentrations to settled dust due to dust/air partition and PCB migration concentration due to dust/source partitioning. \n\nThis dataset is associated with the following publication:\nLiu , X., Z. Guo, K. Krebs , D. Greenwell , N. Roache, A. Stinson, J. Nardin, and R. Pope. Laboratory study of PCB transport from primary sources to settled dust.   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 169: 62-69, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390117",
            "keyword": [
                "migration",
                "PCBs",
                "Settled dust",
                "Sorption concentration",
                "Polychlorinated biphenyls (PCBs)",
                "Chamber testing",
                "Dust/source partition",
                "Dust/air partition"
            ],
            "contactPoint": {
                "fn": "Xiaoyu Liu",
                "hasEmail": "mailto:liu.xiaoyu@epa.gov"
            },
            "distribution": [
                {
                    "title": "XiaoyuLiu_A-w3rq_Data Tables&Dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390117/XiaoyuLiu_A-w3rq_Data%20Tables%26Dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-10",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2016.01.075"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Social media data with CUI redacted 11192018",
            "description": "Data includes the metadata and links for images posted to social media with CUI redacted. \n\nThis dataset is associated with the following publication:\nAngradi, T., J. Launspach, and R. Debbout. Determining preferences for ecosystem benefits in Great Lakes Areas of Concern from photographs posted to social media.   JOURNAL OF GREAT LAKES RESEARCH. International Association for Great Lakes Research, Ann Arbor, MI, USA, 44(2): 340-351, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1503176",
            "keyword": [
                "social media",
                "Ecosystems services",
                "Great Lakes Areas of Concern",
                "Ecosystem services and benefits",
                "Decision making",
                "restoration"
            ],
            "contactPoint": {
                "fn": "Theodore Angradi",
                "hasEmail": "mailto:angradi.theodore@epa.gov"
            },
            "distribution": [
                {
                    "title": "Angradi_social_media_online_sciencehub_11172018.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503176/Angradi_social_media_online_sciencehub_11172018.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-11-19",
            "references": [
                "https://doi.org/10.1016/j.jglr.2017.12.007"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Complete Validation Data for_Direct aqueous injection of the fluoroacetate anion in potable water for analysis by liquid chromatography tandem mass-spectrometry_180226 ",
            "description": "This file presents data generated for the analysis of the fluoroacetate anion in drinking water. Data is divided onto separate excel sheet tabs and labeled with the corresponding figure or table in the manuscript. The first tab is labeled as a data dictionary and contains the meta data (column headings and fields).  Much of the data for the publication will also be placed in the online supplementary material which will be available online through the journal. \n\nThis dataset is associated with the following publication:\nParry, E., and S. Willison. Direct aqueous injection of the fluoroacetate anion in potable water for analysis by liquid chromatography tandem mass-spectrometry.   Analytical Methods. RSC Publishing, Cambridge,  UK,  8 pages, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1422470",
            "keyword": [
                "compound 1080",
                "sodium fluoroacetate",
                "fluoroacetate",
                "drinking water",
                "analytical method",
                "LC-MS/MS"
            ],
            "contactPoint": {
                "fn": "Emily Parry",
                "hasEmail": "mailto:parry.emily@epa.gov"
            },
            "distribution": [
                {
                    "title": "Copy of FAA_manuscript_sciencehub_180111.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1422470/Copy%20of%20FAA_manuscript_sciencehub_180111.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-04-19",
            "references": [
                "https://doi.org/10.1039/c8ay02046a"
            ],
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                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Novel Fast Analysis Method Dataset 09-2018",
            "description": "Recovery data from microbiological analysis procedures developed to speed Bacillus anthracis environmental sample analysis following a biological incident. \n\nThis dataset is associated with the following publication:\nAbdel-Hady, A., W. Calfee, D. Aslett, S. Lee, B. Wyrzykowska-Ceradini, R. Delafield, K. May, and A. Touati. Alternative Fast Analysis Method for Cellulose Sponge Surface Sampling Wipes with Low Concentrations of Bacillus Spores.   JOURNAL OF MICROBIOLOGICAL METHODS. Elsevier Science Ltd, New York, NY, USA,  ., (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1502637",
            "keyword": [
                "Bacillus anthracis",
                "sponge wipe",
                "surface sampling",
                "Laboratory Response Network",
                "CDC",
                "anthrax"
            ],
            "contactPoint": {
                "fn": "Michael Calfee",
                "hasEmail": "mailto:calfee.worth@epa.gov"
            },
            "distribution": [
                {
                    "title": "Novel Fast Analysis Dataset_20180911.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502637/Novel%20Fast%20Analysis%20Dataset_20180911.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "CalfeeMichael_A-sxmj_QASum-20180911.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502637/CalfeeMichael_A-sxmj_QASum-20180911.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2018-09-25",
            "references": [
                "https://doi.org/10.1016/j.mimet.2018.11.013"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The potential effects of climate change on air quality across the conterminous U.S. at 2030 under three Representative Concentration Pathways",
            "description": "This dataset is the underlying data described in Nolte et al., \"The potential effects of climate change on air quality across the conterminous U.S. at 2030 under three Representative Concentration Pathways\", Atmos. Chem. Phys., in press, 2018.\nThe paper describes simulated changes in U.S. air quality (ozone and particulate matter) between 2000 and 2030 under three scenarios of climate change. \nOzone data are in parts per billion by volume, particulate matter are in micrograms per cubic meter, temperature changes are in degrees Celsius, and precipitation has units of millimeters of accumulated precipitation per month. \n\nThis dataset is associated with the following publication:\nNolte, C., T. Spero, J. Bowden, M. Mallard, and P. Dolwick. The potential effects of climate change on air quality across the conterminous US at 2030 under three Representative Concentration Pathways.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 18(20): 15471-15489, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1502507",
            "keyword": [
                "air quality",
                "climate change",
                "regional climate modeling",
                "dynamical downscaling",
                "CMAQ"
            ],
            "contactPoint": {
                "fn": "Christopher Nolte",
                "hasEmail": "mailto:nolte.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Nolte_ACP2018.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502507/Nolte_ACP2018.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-10-23",
            "references": [
                "https://doi.org/10.5194/acp-18-15471-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "MagnusonMatthew_A-txb0_dataset_20181022.xlsx",
            "description": "The dataset contains the raw data for the graphs in the paper. \n\nThis dataset is associated with the following publication:\nScott, R., P. Mudimbi, M. Miller, M. Magnuson , S. Willison , R. Phillips, and W. Harper. Advanced Oxidation of Tartrazine and Brilliant Blue with Pulsed Ultraviolet Light Emitting Diodes.   WATER ENVIRONMENT RESEARCH. Water Environment Federation, Alexandria, VA, USA, 89(1): 24-31, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1503109",
            "keyword": [
                "advanced oxidation",
                "treatment",
                "dyes",
                "tartrazine",
                "wastewater",
                "LED",
                "light emitting diode"
            ],
            "contactPoint": {
                "fn": "Matthew Magnuson",
                "hasEmail": "mailto:magnuson.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "MagnusonMatthew_A-txb0_dataset_20181022.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503109/MagnusonMatthew_A-txb0_dataset_20181022.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-10-22",
            "references": [
                "https://doi.org/10.2175/106143016x14733681696167"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "MagnusonMatthew_A-7h4g_dataset_20181031",
            "description": "Data corresponding to the figures in the paper. \n\nThis dataset is associated with the following publication:\nJolin, W., and M. Kaminski. Sorbent Materials for Rapid Remediation of Washwater during Radiological Event Relief.   Environmental Science & Technology Letters. American Chemical Society, Washington, DC, USA,  165-171, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1503135",
            "keyword": [
                "radionuclides",
                "Retention",
                "breakthrough",
                "vermiculite",
                "cesium",
                "Montmorillonite",
                "dirty bomb",
                "RDD",
                "radiological dispersal device",
                "nuclear power plant accident"
            ],
            "contactPoint": {
                "fn": "Matthew Magnuson",
                "hasEmail": "mailto:magnuson.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "MagnusonMatthew_A-7h4g_dataset_20181031.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503135/MagnusonMatthew_A-7h4g_dataset_20181031.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-10-31",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2016.07.077"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "MagnusonMatthew_A-ht7r_dataset_20181023.xlsx",
            "description": "The dataset contains the raw data for the graphs in the paper. \n\nThis dataset is associated with the following publication:\nRauglas, E., S. Martin, K. Bailey, C. Starr, M. Magnuson, R. Phillips, and W. Harper. The Effect of Malathion on the Activity, Performance, and Microbial Ecology of Activated Sludge- journal.   JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA,  220-228, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1503111",
            "keyword": [
                "wastewater",
                "malathion",
                "biosolid",
                "activated sludge",
                "EMPA"
            ],
            "contactPoint": {
                "fn": "Matthew Magnuson",
                "hasEmail": "mailto:magnuson.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "MagnusonMatthew_A-ht7r_dataset_20181023.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503111/MagnusonMatthew_A-ht7r_dataset_20181023.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-10-23",
            "references": [
                "https://doi.org/10.1016/j.jenvman.2016.08.076"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Watt_HTS_Uncertainty_Quantification_2017_data",
            "description": "In this work, we introduce a new method for uncertainty quantification in ToxCast data. We explore how unavoidable uncertainties in the data result in uncertainties in concentration-response parameters such as potency and efficacy. These uncertainties are then extended throughout to the analysis and interpretation of results for risk assessment. By quantifying these uncertainties through the analysis stages we increase the confidence in the data interpretation and allow for a more robust risk assessment. We also flag chemicals and assays for manual inspection, removal, and retesting so that data quality and model outputs can be further improved. \n\nThis dataset is associated with the following publication:\nWatt, E., and R. Judson. Uncertainty Quantification in ToxCast High Throughput Screening.   PLoS Computational Biology. Public Library of Science, San Francisco, CA, USA, 13(7): 1-23, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407004",
            "keyword": [
                "High throughput screening",
                "ToxCast",
                "bootstrap resampling",
                "uncertainty quantification",
                "ACToR"
            ],
            "contactPoint": {
                "fn": "Richard Judson",
                "hasEmail": "mailto:judson.richard@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/Judson/Watt%20ER%20Uncertainty%202017/",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/Judson/Watt%20ER%20Uncertainty%202017/"
                }
            ],
            "modified": "2017-09-18",
            "references": [
                "https://doi.org/10.1371/journal.pone.0196963"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Representing the Process of Inflammation as Key Events in Adverse Outcome Pathways",
            "description": "A set of three proposed \"hub\" key events were used to link together a series of example adverse outcome pathway (AOP) descriptions that were previously not linked in an AOP network. While there are no data associated with this product, the relevant adverse outcome pathway descriptions can be found at aopwiki.org. This dataset is not publicly accessible because: This product is a workshop report.  There are no data associated with this product. It can be accessed through the following means: AOP descriptions that illustrate concepts discussed in this paper can be accessed via aopwiki.org. Format: There are no data associated with this product. \n\nThis dataset is associated with the following publication:\nVilleneuve, D., B.  Landesmann, P. Allavena, N. Ashley, A. Bal-Price, E. Corsini, S.  Halappanavar, T.  Hussell, D. Laskin, T. Lawrence, D.  Nikolic-Paterson, M. Pallardy, A. Paini, R. Pieters, R. Roth, and F. Tschudi-Monnet. Representing the process of inflammation as key events in adverse outcome pathways.   TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA,  163(2): 346-352, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1423301",
            "keyword": [
                "inflammation",
                "knowledgebase",
                "adverse outcome pathway",
                "ecotoxicology",
                "endocrine disruption",
                "screening and prioritization",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [],
            "modified": "2018-03-01",
            "references": [
                "https://doi.org/10.1093/toxsci/kfy047"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset of Indoor and Built Environment Publication in 2016, Laboratory evaluation of polychlorinated biphenyls encapsulation methods",
            "description": "The data presented in this data file is a product of a journal publication. The dataset contains PCB sorption concentrations on encapsulants, PCB concentrations in the air and in wipe samples, model simulation of the PCB concentration gradient in the source and encapsulant layers on exposed surfaces of encapsulants and in room air at different times, the ranking of encapsulants\u2019 performance. \n\nThis dataset is associated with the following publication:\nLiu , X., Z. Guo, K. Krebs , N. Roache, R. Stinson, J. Nardin, R. Pope, C. Mocka, and R. Logan. Laboratory evaluation of PCBs encapsulation method.   Indoor and Built Environment. Sage Publications, THOUSAND OAKS, CA, USA, 25(6): 895-915, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390118",
            "keyword": [
                "PCBs",
                "encapsulant",
                "Polychlorinated biphenyls (PCBs)",
                "Encapsulation",
                "Abatement technique",
                "Sink chamber tests",
                "Wipe Sampling",
                "Barrier modelling",
                "Solid-air partition coefficient",
                "Solid-phase diffusion coefficient"
            ],
            "contactPoint": {
                "fn": "Xiaoyu Liu",
                "hasEmail": "mailto:liu.xiaoyu@epa.gov"
            },
            "distribution": [
                {
                    "title": "XiaoyuLiu_A-k6f0_Data Tables&Dictionary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390118/XiaoyuLiu_A-k6f0_Data%20Tables%26Dictionary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-08-10",
            "references": [
                "https://doi.org/10.1177/1420326x16645150"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Nitrogen Deposition and Climate Change Effects on Tree Species Composition and Ecosystem Services: A Cohort Analysis in ",
            "description": "A tree database representing a single cohort of trees was assembled using\ndata from U.S Forest Service monitoring plots. Applying existing species specific\nresponse relationships from Thomas et al. (2010), we simulated\nhow forest stands in a 19-state study area would change (biomass and stem density) from 2005 to 2100 under 12 different future N deposition \u2013 climate scenarios based on historic levels, current policy and potential futures. \n\nThis dataset is associated with the following publication:\nvan Houtven, G., J. Phelan, C. Clark, R. Sabo, J. Buckley, R.Q. Thomas, K. Horn, and S. LeDuc. Nitrogen Deposition and Climate Change Effects on Tree Species Composition and Ecosystem Services: A Cohort Analysis.   ECOLOGICAL MONOGRAPHS. Ecological Society of America, Ithaca, NY, USA,  75, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1500027",
            "keyword": [
                "atmospheric deposition",
                "climate change",
                "nitrogen deposition",
                "ecosystem services",
                "forest",
                "Northeast U.S."
            ],
            "contactPoint": {
                "fn": "Christopher Clark",
                "hasEmail": "mailto:clark.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "forest_comp_2005-2100_county.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500027/forest_comp_2005-2100_county.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-10-26",
            "references": [
                "https://doi.org/10.1002/ecm.1345"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1500027/documents/Data_Dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Concentrations of total phosphorus and ortho phosphate in inflow and outflow",
            "description": "The dataset includes total phosphorus and ortho-phosphate concentrations in water. \n\nThis dataset is associated with the following publication:\nBaek, S., S.H. Joo, D. Linne, S. Leon, C. Luciano, C. Bariley, C. Su, and Y. Wan. Pilot-Scale Application of Shotblast Dust for Phosphorus Removal.   Journal AWWA. American Water Works Association, Denver, CO, USA, 110(11): 64-68, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1431903",
            "keyword": [
                "phosphorus",
                "Shotblast dust",
                "Waste material",
                "iron",
                "remediation"
            ],
            "contactPoint": {
                "fn": "Chunming Su",
                "hasEmail": "mailto:su.chunming@epa.gov"
            },
            "distribution": [
                {
                    "title": "Sung Hee Joo P removal Raw data 418.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1431903/Sung%20Hee%20Joo%20P%20removal%20Raw%20data%20418.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2018-11-01",
            "references": [
                "https://doi.org/10.1002/awwa.1186"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Ecosystem services associated with changes in forest composition",
            "description": "This dataset includes the estimated changes in selected ecosystem services associated with the changes in forest composition from the other dataset associated with this Research Effort. \n\nThis dataset is associated with the following publication:\nvan Houtven, G., J. Phelan, C. Clark, R. Sabo, J. Buckley, R.Q. Thomas, K. Horn, and S. LeDuc. Nitrogen Deposition and Climate Change Effects on Tree Species Composition and Ecosystem Services: A Cohort Analysis.   ECOLOGICAL MONOGRAPHS. Ecological Society of America, Ithaca, NY, USA,  75, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1503110",
            "keyword": [
                "atmospheric deposition",
                "climate change",
                "nitrogen deposition",
                "ecosystem services",
                "forest",
                "Northeast U.S."
            ],
            "contactPoint": {
                "fn": "Christopher Clark",
                "hasEmail": "mailto:clark.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "carbon_timber_analyses final.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503110/carbon_timber_analyses%20final.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-10-22",
            "references": [
                "https://doi.org/10.1002/ecm.1345"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1503110/documents/T016_ES_dataset_description.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for tables and figures",
            "description": "A zipped and tarred file which contains netCDF files needed to replicate all tables and figures shown in the referenced journal article. \n\nThis dataset is associated with the following publication:\nMallard, M., T. Spero, and S. Taylor. Examining WRF\u2019s Sensitivity to Contemporary Land-Use Datasets across the Contiguous United States Using Dynamical Downscaling.   JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY. American Meteorological Society, Boston, MA, USA, 57(11): 2561-2583, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1503084",
            "keyword": [
                "land use",
                "WRF",
                "National Land Cover Database (NLCD)",
                "USGS"
            ],
            "contactPoint": {
                "fn": "Megan Mallard",
                "hasEmail": "mailto:mallard.megan@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/EPADataCommons/ORD/NERL_SED/IEMB/mallard_ORD-021329/",
                    "accessURL": "https://gaftp.epa.gov/EPADataCommons/ORD/NERL_SED/IEMB/mallard_ORD-021329/"
                }
            ],
            "modified": "2018-10-15",
            "references": [
                "https://doi.org/10.1175/jamc-d-17-0328.1"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Local Real-time Forecasting of Ozone Exposure using Temperature Data",
            "description": "Contains all subject data used the journal paper, including all ozone and meteorological data. \n\nThis dataset is associated with the following publication:\nLu, X., A. Gelfand, and D. Holland. Local real\u2010time forecasting of ozone exposure using temperature data.   ENVIRONMETRICS. John Wiley & Sons Incorporated, New York, NY, USA, 29(7): e2509, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1366697",
            "keyword": [
                "Village Green monitoring",
                "hierarchical model",
                "ozone forecasting"
            ],
            "contactPoint": {
                "fn": "David Holland",
                "hasEmail": "mailto:holland.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "subset_durham.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1366697/subset_durham.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "subset_dc.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1366697/subset_dc.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2016-09-15",
            "references": [
                "https://doi.org/10.1002/env.2509"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Mutagenicity and Disinfection By-product Concentrations after Chlorination of ICM-Containing Source Waters",
            "description": "The dataset consists of two categories of data:  (1) the mutagenicity data, which is composed of the number of mutants (revertants) per Petri plate and (2) the concentrations of various disinfection by-products in the water. \n\nThis dataset is associated with the following publication:\nPostigo, C., D. DeMarini, M. Armstrong, H. Liberatore, K. Lamann, S. Kimura, A. Cuthbertson, S. Warren, S. Richardson, T. Mcdonald, Y. Sey, N. Ackerson, S. Duirk, and J. Simmons. Chlorination of Source Water Containing Iodinated X-Ray Contrast Media:  Mutagenicity and Identification of New Iodinated Disinfection by-products.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(22): 13047-13056, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1502529",
            "keyword": [
                "iodinated disinfection by-products",
                "DBPs",
                "X-ray contrast media",
                "chlorination",
                "drinking water",
                "Mutagenicity",
                "Salmonella"
            ],
            "contactPoint": {
                "fn": "David Demarini",
                "hasEmail": "mailto:demarini.david@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science Hub Constrast Media Data Set.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502529/Science%20Hub%20Constrast%20Media%20Data%20Set.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-08-06",
            "references": [
                "https://doi.org/10.1021/acs.est.8b04625"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Allometric scaling of hepatic biotransformation in rainbow trout",
            "description": "This dataset illustrates relationships between body weight and hepatic phase I and phase II metabolic activity in rainbow trout. \n\nThis dataset is associated with the following publication:\nFitzsimmons, P., A. Hoffman, K. Fay, and J. Nichols. Allometric scaling of hepatic biotransformation in rainbow trout..   COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY PART C: TOXICOLOGY & PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 214: 52-60, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1435040",
            "keyword": [
                "rainbow trout",
                "allometry",
                "biotransformation",
                "liver S9 fraction"
            ],
            "contactPoint": {
                "fn": "Patrick Fitzsimmons",
                "hasEmail": "mailto:fitzsimmons.patrick@epa.gov"
            },
            "distribution": [
                {
                    "title": "Fitzsimmons-20180501-ScienceHub data summary.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435040/Fitzsimmons-20180501-ScienceHub%20data%20summary.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Fitzsimmons-20180831-ScienceHub supplemental data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435040/Fitzsimmons-20180831-ScienceHub%20supplemental%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-05-07",
            "references": [
                "https://doi.org/10.1016/j.cbpc.2018.08.004"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Estimating n-octanol-water partition coefficients for highly hydrophobic chemicals using measured n-butanol-water partition coefficients",
            "description": "A table of measured n-butanol/water partition coefficients and n-octanol/water partition coefficients. \n\nThis dataset is associated with the following publication:\nHanson, K., D. Hoff, T. Lahren, D. Mount, A. Squillace, and L. Burkhard. Estimating n-octanol-water partition coefficients for neutral highly hydrophobic chemicals using measured n-butanol-water partition coefficients.   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 218: 616-623, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1502508",
            "keyword": [
                "bioaccumulation",
                "sediment",
                "chemical uptake",
                "bioavailability",
                "sediment testing",
                "fish dietary studies"
            ],
            "contactPoint": {
                "fn": "Lawrence Burkhard",
                "hasEmail": "mailto:burkhard.lawrence@epa.gov"
            },
            "distribution": [
                {
                    "title": "Table S4.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502508/Table%20S4.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2018-09-07",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2018.11.141"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data contributed by EPA/ORD/NERL/CED researchers to the manuscript \"Attributing Differences in the Fate of Lateral Boundary Ozone in AQMEII3 Models to Physical Process Representations\"",
            "description": "This dataset contains the data used in the Figures and Tables of the manuscript \u201cAttributing Differences in the Fate of Lateral Boundary Ozone in AQMEII3 Models to Physical Process Representations \". \n\nThis dataset is associated with the following publication:\nLiu, P., C. Hogrefe, U. Im, J. Christensen, J. Bieser, U. Nopmongcol, G. Yarwood, R. Mathur, S. Roselle, and T. Spero. Attributing differences in the fate of lateral boundary ozone in AQMEII3 models to physical process representations.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 18(23): 17157-17175, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434297",
            "keyword": [
                "boundary conditions",
                "tracers",
                "vertical mixing",
                "model intercomparison"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/Exposure/A-ksnj/A-ksnj.zip",
                    "accessURL": "https://gaftp.epa.gov/Exposure/A-ksnj/A-ksnj.zip"
                }
            ],
            "modified": "2018-11-01",
            "references": [
                "https://doi.org/10.5194/acp-18-17157-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1434297/documents/DataDictionary_LiuEtAl_A-ksnj.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset 1: Studies included in literature review",
            "description": "This dataset contains the results of a literature review of experimental nutrient addition studies to determine which nutrient forms were most often measured in the scientific literature. To obtain a representative selection of relevant studies, we searched Web of Science\u2122 using a search string to target experimental studies in artificial and natural lotic systems while limiting irrelevant papers. We screened the titles and abstracts of returned papers for relevance (experimental studies in streams/stream mesocosms that manipulated nutrients). To supplement this search, we sorted the relevant articles from the Web of Science\u2122 search alphabetically by author and sequentially examined the bibliographies for additional relevant articles (screening titles for relevance, and then screening abstracts of potentially relevant articles) until we had obtained a total of 100 articles. If we could not find a relevant article electronically, we moved to the next article in the bibliography. Our goal was not to be completely comprehensive, but to obtain a fairly large sample of published, peer-reviewed studies from which to assess patterns. We excluded any lentic or estuarine studies from consideration and included only studies that used mesocosms mimicking stream systems (flowing water or stream water source) or that manipulated nutrient concentrations in natural streams or rivers. We excluded studies that used nutrient diffusing substrate (NDS) because these manipulate nutrients on substrates and not in the water column. We also excluded studies examining only nutrient uptake, which rely on measuring dissolved nutrient concentrations with the goal of characterizing in-stream processing (e.g., Newbold et al., 1983). From the included studies, we extracted or summarized the following information: study type, study duration, nutrient treatments, nutrients measured, inclusion of TN and/or TP response to nutrient additions, and a description of how results were reported in relation to the research-management mismatch, if it existed. Below is information on how the search was conducted: \n\nSearch string used for Web of Science advanced search \nSearch conducted on 27 September 2016. \nTS= (stream* OR creek* OR river* OR lotic OR brook OR headwater OR tributary) AND TS = (mesocosm OR flume OR \"artificial stream\" OR \"experimental stream\" OR \"nutrient addition\") AND TI= (nitrogen OR phosphorus OR nutrient OR enrichment OR fertilization OR eutrophication)",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503173",
            "keyword": [
                "nutrients",
                "nitrogen",
                "phosphorus",
                "eutrophication",
                "streams",
                "rivers",
                "systematic review",
                "environmental evidence",
                "synthesis"
            ],
            "contactPoint": {
                "fn": "Micah Bennett",
                "hasEmail": "mailto:bennett.micah@epa.gov"
            },
            "distribution": [
                {
                    "title": "BennettLee_mismatch_asloBull_ScienceHub.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503173/BennettLee_mismatch_asloBull_ScienceHub.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2018-11-20",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "WASP Output for Model Simulations",
            "description": "Data provided includes: the details on the WASP setup, including segment characteristics, the flow path, flow, initial and boundary conditions, and the load; the USGS gage flow information and the hydraulic parameters; and the output from the model simulations. \n\nThis dataset is associated with the following publication:\nKnightes, C., R. Ambrose, B. Avant, Y. Han, B. Acrey, D. Bouchard, R. Zepp, and T. Wool. Modeling framework for simulating concentrations of solute chemicals, nanoparticles, and solids in surface waters and sediments: WASP8 Advanced Toxicant Module.   ENVIRONMENTAL MODELLING AND SOFTWARE. Elsevier Science Ltd, New York, NY, USA, 111: 444-458, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1502480",
            "keyword": [
                "WASP",
                "water quality",
                "nanomaterials",
                "photoreactions"
            ],
            "contactPoint": {
                "fn": "Christopher Knightes",
                "hasEmail": "mailto:knightes.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "WASP Output.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502480/WASP%20Output.zip",
                    "mediaType": "application/zip"
                },
                {
                    "title": "Final_WASP_SetUp_CapeFear03222018.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502480/Final_WASP_SetUp_CapeFear03222018.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "USGS_gages.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502480/USGS_gages.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-07-11",
            "references": [
                "https://doi.org/10.1016/j.envsoft.2018.10.012"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Foy Lake Abundance data",
            "description": "Percent abundance of 109 diatom species collected from a Foy Lake (Montana, USA) sediment core that was sampled every \u223c5\u201320 years, yielding a \u223c7 kyr record over 800 time-steps. \n\nThis dataset is associated with the following publication:\nSpanbauer, T., C. Allen, D. Angeler, T. Eason , S. Fritz, A. Garmestani , K. Nash, J. Stone, C. Stow, and S. Sundstrom. Body size distributions signal a regime shift in a lake ecosystem.   ECOSYSTEMS. Springer, New York, NY, USA, 283(1833): 00, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1503290",
            "keyword": [
                "Foy Lake",
                "Montana",
                "diatoms",
                "resilience",
                "leading indicators",
                "governance",
                "environmental change",
                "complex systems",
                "law and policy"
            ],
            "contactPoint": {
                "fn": "Tarsha Eason",
                "hasEmail": "mailto:eason.tarsha@epa.gov"
            },
            "distribution": [
                {
                    "title": "Foy Lake (Abundance data).xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503290/Foy%20Lake%20%28Abundance%20data%29.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-06-26",
            "references": [
                "https://doi.org/10.1098/rspb.2016.0249"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Contaminants in bald eagles of the upper Midwestern U.S.: A framework for prioritizing future research based on in-vitro bioassays",
            "description": "Contaminant data from bald eagles in the Upper-Midwest of the US. Dataset contains five tables in total including details of sample collection locations, organic contaminant data, and exposure-activity ratios (EARs) individual samples and chemicals. \n\nThis dataset is associated with the following publication:\nElliott, S., W. Route, L. DeCicco, D. VanderMeulen, S. Corsi, and B. Blackwell. Contaminants in bald eagles of the upper Midwestern U.S.: A framework for prioritizing future research based on in-vitro bioassays.   ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 244: 861-870, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1500887",
            "keyword": [
                "adverse outcome pathway",
                "endocrine disruption",
                "ecotoxicology",
                "aquatic ecosystems",
                "screening and prioritization"
            ],
            "contactPoint": {
                "fn": "Brett Blackwell",
                "hasEmail": "mailto:blackwell.brett@epa.gov"
            },
            "distribution": [
                {
                    "title": "ContamsInEagles_SI_Final.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500887/ContamsInEagles_SI_Final.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-12-13",
            "references": [
                "https://doi.org/10.1016/j.envpol.2018.10.093"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Black Carbon and related environmental data for fate and transport",
            "description": "We determined soil hydrology, soil carbon pools (organic carbon, black carbon, and inorganic carbon) from urban soil assessments (surface and sub-surface horizons) carried out in the core areas of eleven cities in the United States. We used both ordinary least squares and non-parametric CART methods to discern trends in BC concentrations with regard to soil, landscape, and emission metrics. \n\nThis dataset is associated with the following publication:\nSchifman, L., A. Prues, K. Gilkey, and W. Shuster. Realizing the Opportunities of Black carbon in Urban Soils: Implications for Water Quality Management with Green Infrastructure.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 644: 1027-1035, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407689",
            "keyword": [
                "Black Carbon",
                "urban soil",
                "Green Infrastructure",
                "water quality"
            ],
            "contactPoint": {
                "fn": "William Shuster",
                "hasEmail": "mailto:shuster.william@epa.gov"
            },
            "distribution": [
                {
                    "title": "Schifmanetal_BlackCarbon_ScienceHub.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407689/Schifmanetal_BlackCarbon_ScienceHub.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-11-03",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.06.396"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data contributed by EPA/ORD/NERL/CED researchers to the manuscript \"A New Method for Assessing the Efficacy of Emission Control Strategies to Comply with the Ambient Ozone Standard\"",
            "description": "Files containing daily maximum 8-hr ozone mixing ratio observations used in the analysis presented in the manuscript \u201cA New Method for Assessing the Efficacy of Emission Control Strategies to Comply with the Ambient Ozone Standard\u201d. \n\nThis dataset is associated with the following publication:\nLuo, H., M. Astitha, C. Hogrefe, R. Mathur, and S.T. Rao. A new method for assessing the efficacy of emission control strategies.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 199: 233-243, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434296",
            "keyword": [
                "Ozone",
                "emission control strategies",
                "attainment demonstration",
                "probability of exceeding the standard"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "HogrefeChristian_A-h718_Data_Dictionary.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434296/HogrefeChristian_A-h718_Data_Dictionary.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "sitecompare_daily_o3_aqmeii3_conus12_2010_bc_glo_em_glo.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434296/sitecompare_daily_o3_aqmeii3_conus12_2010_bc_glo_em_glo.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "sitecompare_daily_o3_aqmeii3_conus12_2010_base.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434296/sitecompare_daily_o3_aqmeii3_conus12_2010_base.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "sitecompare_daily_o3_doe_conus36_sf_1990_2010.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434296/sitecompare_daily_o3_doe_conus36_sf_1990_2010.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-01-01",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2018.11.010"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1434296/documents/HogrefeChristian_A-h718_Data_Dictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Landsat surface temperature",
            "description": "Relatively cloud-free Landsat scenes within \u00b13 days of coincident in situ measures were retained for validation across the CONUS. The Landsat surface temperature data were interpolated to 30 m to ensure alignment with the solar reflective bands in the Level-1 products, which were in turn used as inputs to the surface temperature retrieval algorithms. For lake and reservoir validation, two sets of temperature data were evaluated: land-water boundary (<59 m from shore) data and far shore (>180 m from shore) data. Estuary data were retained and evaluated only if they were >180 m from shore.  The 59 m near shore threshold was chosen to be smaller than the finer of the two thermal band spatial resolutions for both the Landsat 7 ETM+ (60 m) and Landsat 5 TM (90 m) sensors. \n\nThis dataset is associated with the following publication:\nSchaeffer, B., J. Iiames, J. Dwyer, E. Urquhart, W. Salls, J. Rover, and B. Seegers. An initial validation of Landsat 5 and 7 derived surface water temperature for U.S. lakes, reservoirs, and estuaries.   INTERNATIONAL JOURNAL OF REMOTE SENSING. Taylor & Francis, Inc., Philadelphia, PA, USA, 39(22): 7789-7805, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1408879",
            "keyword": [
                "Landsat",
                "temperature",
                "lake",
                "estuary",
                "water quality"
            ],
            "contactPoint": {
                "fn": "Blake Schaeffer",
                "hasEmail": "mailto:schaeffer.blake@epa.gov"
            },
            "distribution": [
                {
                    "title": "Landsat_temp_manuscript.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1408879/Landsat_temp_manuscript.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-12-18",
            "references": [
                "https://doi.org/10.1080/01431161.2018.1471545"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A state-of-the-science review of chemical and non-chemical stressors found in the built and natural environments and how they may impact American Indian/Alaska Native children\u2019s health and well-being: Dataset",
            "description": "Data gathered from 35 published references (until 2016) targeting built and natural environment stressors for American Indian/Alaska Native children. \n\nThis dataset is associated with the following publication:\nBarros, N., N. Tulve, D. Heggem, and K. Bailey. Review of built and natural environment stressors impacting American-Indian/Alaska-Native children.   REVIEWS ON ENVIRONMENTAL HEALTH. Freund Publishing House Limited, Tel Aviv,  ISRAEL, 33(4): 349\u2013381, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1423768",
            "keyword": [
                "state-of-the-science review",
                "children",
                "American Indian/Alaska Native",
                "built environment",
                "Natural environment",
                "Stressors"
            ],
            "contactPoint": {
                "fn": "Nirmalla Barros",
                "hasEmail": "mailto:barros.nilla@epa.gov"
            },
            "distribution": [
                {
                    "title": "Barros et al BuiltNatEnvStressorsReviewManuscript and Dataset 03012018_final.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1423768/Barros%20et%20al%20BuiltNatEnvStressorsReviewManuscript%20and%20Dataset%2003012018_final.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2018-03-01",
            "references": [
                "https://doi.org/10.1515/reveh-2018-0034"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset: A patchy continuum? Stream macronutrient concentration and system metabolism show varied responses to patch- and continuum-based analyses. ",
            "description": "At 21 sites located in the Kanawha River Basin in West Virginia, U.S.A., Oxygen concentration (mg l-1) and water temperature (\u00b0C) were measured every 15 min for > 72 h using TROLL\u00ae 9500 multiparameter water quality instruments. \n\nThis dataset is associated with the following publication:\nCollins, S., S. Matter, I. Buffam, and J. Flotemersch. A patchy continuum? Stream processes show varied responses to patch\u2010 and continuum\u2010based analyses.   Ecosphere. ESA Journals,    9(11): e02481, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1500943",
            "keyword": [
                "Oxygen",
                "temperature",
                "River Continuum Concept",
                "Riverine Ecosystem Synthesis",
                "stream order",
                "functional process zones"
            ],
            "contactPoint": {
                "fn": "Joseph Flotemersch",
                "hasEmail": "mailto:flotemersch.joseph@epa.gov"
            },
            "distribution": [
                {
                    "title": "Kanawha River Basin temperature and DO data.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500943/Kanawha%20River%20Basin%20temperature%20and%20DO%20data.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2014-03-31",
            "references": [
                "https://doi.org/10.1002/ecs2.2481"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data contributed by EPA/ORD/NERL/CED researchers to the manuscript \"Seasonal ozone vertical profiles over North America using the AQMEII group of air quality models: model inter-comparison and stratospheric intrusions\"",
            "description": "This dataset contains the data contributed by EPA/ORD/NERL/CED researchers to the manuscript \"Seasonal ozone vertical profiles over North America using the AQMEII group of air quality models: model inter-comparison and stratospheric intrusions\" led by Dr. Marina Astitha of the University of Connecticut. \n\nThis dataset is associated with the following publication:\nAstitha, M., I. Kioutskioukis, G.A. Fisseha, R. Bianconi, J. Bieser, J. Christensen, O. Cooper, S. Galmarini, C. Hogrefe, U. Im, B. Johnson, P. Liu, U. Nopmongcol, I. Petropavlovskikh, E. Solazzo, D. Tarasick, and G. Yarwood. Seasonal ozone vertical profiles over North America using the AQMEII3 group of air quality models: model inter-comparison and stratospheric intrusions.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 18(19): 13925-13945, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434292",
            "keyword": [
                "model evaluation",
                "stratospheric intrusion",
                "free tropospheric ozone",
                "model intercomparison"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "HogrefeChristian_A-nk9w_DataSet.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434292/HogrefeChristian_A-nk9w_DataSet.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-01-01",
            "references": [
                "https://doi.org/10.5194/acp-18-13925-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1434292/documents/HogrefeChristian_A-nk9w_DataDescription.zip",
            "describedByType": "application/zip",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Continuous, Near Real-Time Evaluation of CMAQ: An Approach for the Rapid Scientific Evolution of the Modeling System",
            "description": "Near Real Time CMAQ Simulations compared to AQS Observations. \n\nThis dataset is associated with the following publication:\nEder, B., R. Gilliam, G. Pouliot, R. Mathur, and J. Pleim. Continuous, Near Real-Time Evaluation of Air Quality Models: An Approach for the Rapid Scientific Evolution of Modeling Systems.   EM Magazine. Air and Waste Management Association, Pittsburgh, PA, USA,  1-6, (2017).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434608",
            "keyword": [
                "CMAQ",
                "Ozone",
                "particulate matter",
                "Model Evluation"
            ],
            "contactPoint": {
                "fn": "Brian Eder",
                "hasEmail": "mailto:eder.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "O3_AIRNOW_CMAQ_24h_0Z_20160610.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434608/O3_AIRNOW_CMAQ_24h_0Z_20160610.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "PM25_AIRNOW_CMAQ_24h_0Z_20140201.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434608/PM25_AIRNOW_CMAQ_24h_0Z_20140201.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "PM25_AIRNOW_CMAQ_24h_0Z_20150705.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434608/PM25_AIRNOW_CMAQ_24h_0Z_20150705.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "PM25_AIRNOW_CMAQ_24h_0Z_20170201.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434608/PM25_AIRNOW_CMAQ_24h_0Z_20170201.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "PM25_AIRNOW_CMAQ_24h_0Z_20170131.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434608/PM25_AIRNOW_CMAQ_24h_0Z_20170131.txt",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2018-07-12",
            "references": null,
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1434608/documents/PM25_AIRNOW_CMAQ_24h_0Z_20170131.txt",
            "describedByType": "text/plain",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Experimental and model estimates of the contributions from biogenic monoterpenes and sesquiterpenes to secondary organic aerosol in the southeastern United States",
            "description": "Atmospheric organic aerosol (OA) has important impacts on climate and human health but its sources remain poorly understood. Biogenic monoterpenes and sesquiterpenes are important precursors of secondary organic aerosol (SOA), but the amounts and pathways of SOA generation from these precursors are not well constrained by observations. We propose that the less-oxidized oxygenated organic aerosol (LO-OOA) factor resolved from positive matrix factorization (PMF) analysis on aerosol mass spectrometry (AMS) data can be used as a surrogate for fresh SOA from monoterpenes and sesquiterpenes in the southeastern US. This hypothesis is supported by multiple lines of evidence, including lab-in-the-field perturbation experiments, extensive ambient ground-level measurements, and state-of-the-art modeling. We performed lab-in-the-field experiments in which the ambient air is perturbed by the injection of selected monoterpenes and sesquiterpenes, and the subsequent SOA formation is investigated. PMF analysis on the perturbation experiments provides an objective link between LO-OOA and fresh SOA from monoterpenes and sesquiterpenes as well as insights into the sources of other OA factors. Further, we use an upgraded atmospheric model and show that modeled SOA concentrations from monoterpenes and sesquiterpenes could reproduce both the magnitude and diurnal variation of LO-OOA at multiple sites in the southeastern US, building confidence in our hypothesis. We estimate the annual average concentration of SOA from monoterpenes and sesquiterpenes in the southeastern US to be roughly 2\u00b5gm\u22123.\n\nDataset (csv file) contains CMAQ model predictions for locations in the southeastern US during 2012 and 2013. The species definition file (txt) defines how quantities were obtained from the model. Data in the csv files follows the writesite utility output format (https://github.com/USEPA/CMAQ/tree/5.2.1/POST/writesite). Links to additional datasets are provided. \n\nThis dataset is associated with the following publication:\nXu, L., H. Pye, J. He, Y. Chen, B. Murphy, and N. Ng. Experimental and model estimates of the contributions from biogenic monoterpenes and sesquiterpenes to secondary organic aerosol in the southeastern United States.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 18(17): 12613-12637, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1502524",
            "keyword": [
                "Monoterpene",
                "Secondary Organic Aerosol",
                "CMAQ",
                "Community Multi-scale Air Quality (CMAQ) model",
                "SOAS",
                "SOA",
                "pm2.5",
                "PM2.5 air quality modeling",
                "Semivolatile Organic Compounds (SVOCs)",
                "Biogenic VOC"
            ],
            "contactPoint": {
                "fn": "Havala Pye",
                "hasEmail": "mailto:pye.havala@epa.gov"
            },
            "distribution": [
                {
                    "title": "cmaqv52withsaha.20170525.may2012.3c.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502524/cmaqv52withsaha.20170525.may2012.3c.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "cmaqv52withsaha.20170525.june2013.1cd.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502524/cmaqv52withsaha.20170525.june2013.1cd.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "cmaqv52withsaha.20170525.nov2012.5c.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502524/cmaqv52withsaha.20170525.nov2012.5c.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "cmaqv52withsaha.20170525.june2012.4cd.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502524/cmaqv52withsaha.20170525.june2012.4cd.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "species.lu.20170525.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502524/species.lu.20170525.txt",
                    "mediaType": "text/plain"
                },
                {
                    "title": "https://esrl.noaa.gov/csd/groups/csd7/measurements/2013senex/",
                    "accessURL": "https://esrl.noaa.gov/csd/groups/csd7/measurements/2013senex/"
                },
                {
                    "title": "https://github.com/USEPA/CMAQ",
                    "accessURL": "https://github.com/USEPA/CMAQ"
                },
                {
                    "title": "https://doi.org/10.5281/zenodo.1079878",
                    "accessURL": "https://doi.org/10.5281/zenodo.1079878"
                }
            ],
            "modified": "2017-05-25",
            "references": [
                "https://doi.org/10.5194/acp-18-12613-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "1990-2010 PM & O3 concentrations and related premature mortality estimates",
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                {
                    "title": "Tables_2_O3.xlsx",
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            ],
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                    "name": "U.S. Environmental Protection Agency",
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        },
        {
            "title": "Column NO2 from ground, aircraft and satellite",
            "description": "Vertical and slant column densities over Seoul and Los Angeles. \n\nThis dataset is associated with the following publication:\nJudd, L., J.A. Al-Saadi, L. Valin, R.B. Pierce, K. Yang, S.J. Janz, M.G. Kowalewski, J. Szykman, M. Tiefengraber, and M. Mueller. The Dawn of Geostationary Air Quality Monitoring: Case Studies From Seoul and Los Angeles.   Frontiers in Environmental Science. Frontiers, Lausanne,  SWITZERLAND, 6: 85, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
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                "020:00"
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            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1502545",
            "keyword": [
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                "air quality",
                "pandora",
                "GeoTASO",
                "satellite",
                "geostationary"
            ],
            "contactPoint": {
                "fn": "James Szykman",
                "hasEmail": "mailto:szykman.jim@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://www-air.larc.nasa.gov/cgi-bin/ArcView/korusaq?B200=1",
                    "accessURL": "https://www-air.larc.nasa.gov/cgi-bin/ArcView/korusaq?B200=1"
                },
                {
                    "title": "https://www-air.larc.nasa.gov/cgi-bin/ArcView/lmos",
                    "accessURL": "https://www-air.larc.nasa.gov/cgi-bin/ArcView/lmos"
                },
                {
                    "title": "https://dx.doi.org/10.5067/Q22N0XVLE2QAVR3",
                    "accessURL": "https://dx.doi.org/10.5067/Q22N0XVLE2QAVR3"
                },
                {
                    "title": "https://nomads.ncep.noaa.gov",
                    "accessURL": "https://nomads.ncep.noaa.gov"
                },
                {
                    "title": "https://www.arb.ca.gov/aqmis2/metselect.php.",
                    "accessURL": "https://www.arb.ca.gov/aqmis2/metselect.php."
                }
            ],
            "modified": "2018-05-01",
            "references": [
                "https://doi.org/10.3389/fenvs.2018.00085"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
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            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "HgSe XANES data",
            "description": "This dataset represents Figure 4 in the manuscript which shows the comparison of Se speciation of HgSe relative to samples with linear combination fits. \n\nThis dataset is associated with the following publication:\nGajdosechova, Z., M. Lawan, D. Urgast, A. Raab, K. Scheckel , E. Lombi, P. Kopittke, K. L\u00f6eschner, E. Larsen, G. Woods, A. Brownlow, F. Read, J. Feldmann, and E. Krupp. <I>In vivo</I> formation of natural HgSe nanoparticles in the liver and brain of pilot whales.  Staffan Normark  NATURE. Macmillan Publishers Ltd., London,  UK, 6(34361): 1-11, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1503210",
            "keyword": [
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                "mercury",
                "bioavailability"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Gajdosechova HgSe XANES Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503210/Gajdosechova%20HgSe%20XANES%20Data.xlsx",
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            "modified": "2016-08-04",
            "references": [
                "https://doi.org/10.1038/srep34361"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Overflow System Capacity",
            "description": "This dataset contains results of overflow system experiments for 4-, 6-, and 8-inch overflow systems. The systems were operated without a mesh, or with varying degrees of blockage, from clean to 60% blocked. \n\nThis dataset is associated with the following publication:\nBurkhardt, J., J. Goodrich, J. Szabo, J. Hall, J. Crosby, S. Tourney, and R. Clement. Understanding the Impact of Mesh on Tank Overflow System Capacity - journal.   JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA, 110(12): E44-E51, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1407687",
            "keyword": [
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                "hydraulics",
                "mesh",
                "overflow systems"
            ],
            "contactPoint": {
                "fn": "Jonathan Burkhardt",
                "hasEmail": "mailto:burkhardt.jonathan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Burkhardt-SciHub_A-rr5m_-TankOverflow.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407687/Burkhardt-SciHub_A-rr5m_-TankOverflow.xlsx",
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            "references": [
                "https://doi.org/10.1002/awwa.1162"
            ],
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                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "2014HarshaLakeFlyover_WaterChemistryDataUsedForChlorophyllStudy.xlsx",
            "description": "Chlorophyll and General Water Quality variables collected during a flyover event of Harsha Lake in Southwestern Ohio. 44 sites were sampled within one hour of aerial imagery acquisition. \n\nThis dataset is associated with the following publication:\nBeck, R., S. Zhan, H. Liu, S. Tong, B. Yang, M. Xu, Z. Ye, Y. Huang, S. Shu, K. Berling, M. Andrew, E. Emery, M. Reif, J. Harwood, J. Young, C. Nietch , D. Macke , M. Martin, G. Stillings, R. Stumpf, and H. Su. Comparison of satellite reflectance algorithms for estimating chlorophyll-a in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations.   REMOTE SENSING OF ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 178: 15-30, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503177",
            "keyword": [
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                "Chlorophyll-a",
                "algal bloom",
                "harmful algal bloom",
                "algorithm",
                "satellite",
                "hyperspectral"
            ],
            "contactPoint": {
                "fn": "Christopher Nietch",
                "hasEmail": "mailto:nietch.christopher@epa.gov"
            },
            "distribution": [
                {
                    "title": "2014HarshaLakeFlyover_WaterChemistryDataUsedForChlorophyllStudy.xlsx",
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            "modified": "2018-11-19",
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                "http://www.sciencedirect.com/science/article/pii/S0034425716300943"
            ],
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                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "In silico site-directed mutagenesis informs species-specific predictions of chemical susceptibility derived from the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) ",
            "description": "All data associated with publication are publicly available online at https://datadryad.org/ by searching doi:10.5061/dryad.2tg6967\nUpon accessing data on datadryad.org:\nData descriptions are found with Supplemental Data presented in the pdf (Supplementary Data.pdf (600.4 Kb)).\nData description of supplemental Data (Supplementary Data File.xlsx (1.167 Mb)) is provided below:\nTabs one, two, and three contain the raw data for acetylcholinesterase (AChE) Level 1 (Figure 1A), Level 2 (Figure 1B), and Level 3 (Table 2) SeqAPASS analysis, respectively. Tab four contains the raw data for AChE Level 3 improved SeqAPASS analysis (Table 5). Tabs five, six, and seven contain the raw data for ecdysone receptor (EcR) Level 1 (Figure 2A), Level 2 (Figure 2B), and Level 3 (Table 6) SeqAPASS analysis, respectively. Tab eight contains the raw data for EcR Level 3 improved SeqAPASS analysis (Table 8). \n\nThis dataset is associated with the following publication:\nDoering, J., S. Lee, K. Kristiansen, L. Evenseth, M. Barron, I. Sylte, and C. LaLone. In silico site-directed mutagenesis informs species-specific predictions of chemical susceptibility derived from the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool..   TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA,  166(1): 131-145, (2018).",
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            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
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            "programCode": [
                "020:095"
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            "identifier": "https://doi.org/10.23719/1432264",
            "keyword": [
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                "ecotoxicology",
                "honey bee",
                "cross-species extrapolation",
                "screening and prioritization",
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            ],
            "contactPoint": {
                "fn": "Carlie Lalone",
                "hasEmail": "mailto:lalone.carlie@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://datadryad.org/",
                    "accessURL": "https://datadryad.org/"
                }
            ],
            "modified": "2018-07-30",
            "references": [
                "https://doi.org/10.1093/toxsci/kfy186"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Wilkin et al. (2018) PRB Long-term Performance TCE",
            "description": "The dataset accompanies the manuscript. The data provided include concentration data for trichloroethene, cis-dichloroethene, vinyl chloride, ethane, and ethane. Stable isotope data are provided for trichloroethene, cis-dichloroethene, vinyl chloride, methane, and dissolved carbon dioxide. Additional data are provided in the supporting information published with the article. \n\nThis dataset is associated with the following publication:\nWilkin, R.T., T.R. Lee, M.R. Sexton, S.D. Acree, R.W. Puls, D.W. Blowes, C. Kalinowski, J.M. Tilton, and L.L. Woods. Geochemical and Isotope Study of Trichloroethene Degradation in a Zero-Valent Iron Permeable Reactive Barrier: A Twenty-Two-Year Performance Evaluation.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 53: 296-306, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1502491",
            "keyword": [
                "groundwater",
                "chromium",
                "Aquifer remediation",
                "arsenic",
                "TCE",
                "Permeable Reactive Barrier"
            ],
            "contactPoint": {
                "fn": "Richard Wilkin",
                "hasEmail": "mailto:wilkin.rick@epa.gov"
            },
            "distribution": [
                {
                    "title": "Wilkin et al. (2018) PRB Long-term Performance TCE.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502491/Wilkin%20et%20al.%20%282018%29%20PRB%20Long-term%20Performance%20TCE.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2018-07-20",
            "references": [
                "https://doi.org/10.1021/acs.est.8b04081"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data contributed by EPA/ORD/NERL/CED researchers to the manuscript \"Modelling black carbon absorption of solar radiation: combining external and internal mixing assumptions\"",
            "description": "This dataset contains the data contributed by EPA/ORD/NERL/CED researchers to the manuscript \"Modelling black carbon absorption of solar radiation: combining external and internal mixing assumptions\" led by Dr. Gabriele Curci of the University of L\u2019Aquila in L\u2019Aquila, Italy. \n\nThis dataset is associated with the following publication:\nCurci, G., U. Alyuz, R. Baro, R. Bianconi, J. Bieser, J. Christensen, A. Colette, A. Farrow, X. Francis, P. Jimenez-Guerrero, U. Im, P. Liu, A. Manders, L. Palacios-Pena, M. Prank, L. Pozzoli, R. Sokhi, E. Solazzo, P. Tuccella, A. Unal, M. Garcia Vivanco, C. Hogrefe, and S. Galmarini. Modelling black carbon absorption of solar radiation: combining external and internal mixing assumptions.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 19(1): 181-204, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1434291",
            "keyword": [
                "Aerosol optics",
                "aerosol mixing states",
                "model intercomparison",
                "FlexAOD"
            ],
            "contactPoint": {
                "fn": "Christian Hogrefe",
                "hasEmail": "mailto:hogrefe.christian@epa.gov"
            },
            "distribution": [
                {
                    "title": "HogrefeChristian_A-wh7s_DataSet.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434291/HogrefeChristian_A-wh7s_DataSet.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-01-01",
            "references": [
                "https://doi.org/10.5194/acp-19-181-2019"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1434291/documents/HogrefeChristian_A-wh7s_DataDescription.zip",
            "describedByType": "application/zip",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for: Evaluation of Chemical Effects on Network Formation in Cortical Neurons Grown on Microelectrode Arrays",
            "description": "This dataset contains the raw data, Area under the curve measurements and EC50 values for effects of 146 compounds (136 unique plus 10 biological replicates) on parameters of network development measured in vitro. There are 17 parameters plus 2 measures of viability. In addition, the data for the ranking of potency and selectivity are provided, as well as data for the comparisons to other ToxCast assays and in vitro to in vivo extrapolations. \n\nThis dataset is associated with the following publication:\nShafer, T., J. Brown, B. Lynch, S. Davila-Montero, K. Wallace, and K. Paul-Friedman. Evaluation of Chemical Effects on Network Formation in Cortical Neurons Grown on Microelectrode Arrays.   TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA,  169(2): 436-455, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1503191",
            "keyword": [
                "developmental neurotoxicity",
                "Chemical Screening",
                "Microelectrode array",
                "In vitro assay"
            ],
            "contactPoint": {
                "fn": "Timothy Shafer",
                "hasEmail": "mailto:shafer.tim@epa.gov"
            },
            "distribution": [
                {
                    "title": "MEA_and_ToxCast_and AEDs_for_TC_NTP_25Oct2018.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503191/MEA_and_ToxCast_and%20AEDs_for_TC_NTP_25Oct2018.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Excel scatter plot potency vs viability_Nov_26_2018.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503191/Excel%20scatter%20plot%20potency%20vs%20viability_Nov_26_2018.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Excel_selectivity_Oct 26_2018_alt.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503191/Excel_selectivity_Oct%2026_2018_alt.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "NTP_TC_Analysis.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503191/NTP_TC_Analysis.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-11-26",
            "references": [
                "https://doi.org/10.1093/toxsci/kfz052"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Iodotyrosine deiodinase: mRNA expression and experimental inhibition study in Xenopus laevis",
            "description": "This excel file contains the resultant data from a study on iodotyrosine deiodinase in the model amphibian species, Xenopus laevis. These data include: tadpole growth and development, thyroid hormones in plasma and glands, and expression of thyroid-relevant genes. The initial worksheet tab that provides metadata for each dataset included in the other worksheets that make up the file. \n\nThis dataset is associated with the following publication:\nOlker, J., J. Haselman, P. Kosian, K. Donnay, J. Korte, C. Blanksma, M. Hornung, and S. Degitz. Evaluating iodide recycling inhibition as a novel molecular initiating event for thyroid axis disruption in amphibians.   TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA,  166(2): 318-331, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1500003",
            "keyword": [
                "iodotyrosine deiodinase",
                "thyroid",
                "amphibian metamorphosis",
                "iodine deficiency",
                "endocrine disruption",
                "Xenopus laevis"
            ],
            "contactPoint": {
                "fn": "Jennifer Olker",
                "hasEmail": "mailto:olker.jennifer@epa.gov"
            },
            "distribution": [
                {
                    "title": "Olker_et_al_IYD_180803.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500003/Olker_et_al_IYD_180803.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-08-03",
            "references": [
                "https://doi.org/10.1093/toxsci/kfy203"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Purpose Driven Reconciliation Approaches Estimate Chemical Releases DataSet",
            "description": "Curated input data for regression tree modeling, links for EPA sources of data, and glossary of terms used in the data are presented in a spreadsheet.  The data set has production volumes, emissions, and physicochemical properties for chemicals. \n\nThis dataset is associated with the following publication:\nMeyer, D., V. Mittal, W. Ingwersen, G. Ruiz-Mercado, W. Barrett, M. Gonzalez, J. Abraham, and R. Smith. Purpose-Driven Reconciliation of Approaches to Estimate Chemical Releases.   ACS Sustainable Chemistry & Engineering. American Chemical Society, Washington, DC, USA, 7(1): 1260-1270, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1503037",
            "keyword": [
                "LCI",
                "data mining",
                "Chemical Manufacture",
                "US EPA Database",
                "Process Design",
                "Simulation"
            ],
            "contactPoint": {
                "fn": "Raymond Smith",
                "hasEmail": "mailto:smith.raymond@epa.gov"
            },
            "distribution": [
                {
                    "title": "PurposeDrivenReconciliationApproachesEstimateChemicalReleases DataSet.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503037/PurposeDrivenReconciliationApproachesEstimateChemicalReleases%20DataSet.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-09-18",
            "references": [
                "https://doi.org/10.1021/acssuschemeng.8b04923"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Potential toxicity of complex mixtures in surface waters from a nationwide survey of United States streams: Identifying in vitro bioactivities and causative chemicals",
            "description": "In vitro biological activity data from a extracts of a nationwide survey of US streams. \n\nThis dataset is associated with the following publication:\nBlackwell, B., G. Ankley, P. Bradley, K. Houck, S.S.  Makarov, A. Medvedev, J. Swintek, and D. Villeneuve. Potential toxicity of complex mixtures in surface waters from a nationwide survey of United States streams: Identifying in vitro bioactivities and causative chemicals.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 53(2): 973-983, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1500886",
            "keyword": [
                "adverse outcome pathway",
                "endocrine disruption",
                "ecotoxicology",
                "aquatic ecosystems",
                "screening and prioritization"
            ],
            "contactPoint": {
                "fn": "Brett Blackwell",
                "hasEmail": "mailto:blackwell.brett@epa.gov"
            },
            "distribution": [
                {
                    "title": "Blackwell_es-2018-05304s_Final SI Tables.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500886/Blackwell_es-2018-05304s_Final%20SI%20Tables.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-12-13",
            "references": [
                "https://doi.org/10.1021/acs.est.8b05304"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Sr transfer",
            "description": "SR Transfer. \n\nThis dataset is associated with the following publication:\nMelnyk, L., M. Donohue, M. Pham, and J. Donohue. Absorption of Strontium by Foods Prepared in Drinking Water.   American Journal of Public Health. American Public Health Association, Washington, DC, USA, 53: 22-26, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1502471",
            "keyword": [
                "Strontium",
                "transfer",
                "water",
                "foods",
                "relative source contribution"
            ],
            "contactPoint": {
                "fn": "Lisa Melnyk",
                "hasEmail": "mailto:melnyk.lisa@epa.gov"
            },
            "distribution": [
                {
                    "title": "SR TRANSFER.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502471/SR%20TRANSFER.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-09-04",
            "references": [
                "https://doi.org/10.1016/j.jtemb.2019.01.001"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Georgeite paper dataset in spreadsheet",
            "description": "The dataset represents data used to create tables and figures used in in manuscript. \n\nThis dataset is associated with the following publication:\nLytle, D., D. Wahman, M. Schock, M. Nadagouda, S. Harmon, K. Webster, and J. Botkins. Georgeite: A Rare Copper Mineral with Important Drinking Water Implications.   Chemical Engineering Journal. Elsevier BV, AMSTERDAM,  NETHERLANDS, 355: 1-10, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1371617",
            "keyword": [
                "Georgeite",
                "Copper",
                "drinking water"
            ],
            "contactPoint": {
                "fn": "Darren Lytle",
                "hasEmail": "mailto:lytle.darren@epa.gov"
            },
            "distribution": [
                {
                    "title": "Georgeite Paper Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1371617/Georgeite%20Paper%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-07-17",
            "references": [
                "https://doi.org/10.1016/j.cej.2018.08.106"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Coliform persistence in aircraft water systems and assessment of disinfection and flushing procedures",
            "description": "In 2009, the EPA promulgated the Aircraft Drinking Water Rule (ADWR), which aims to ensure that safe and reliable drinking water is provided to aircraft passengers and crew.  The rule sets a schedule for disinfection, flushing and coliform/E. coli sampling, in addition to instituting best practices and operator training.  In this study, a full scale reproduction of an aircraft drinking water system was constructed at the Test and Evaluation (T&E) facility in Cincinnati, OH.  The water system was conditioned using municipal tap water with a mixture of free chlorine and chloramines, and subsequently contaminated with coliforms.   Disinfection was undertaken using two common airline industry methods: chlorine dioxide at 100 mg/L (or higher) for two hours, and ozone at 1 mg/L (or higher) for 5 minutes. After disinfection, the water system was flushed until no disinfectant residual remained and then filled with treated municipal drinking water.  \n\nResults show that coliforms were not persistent on the aircraft plumbing surfaces, and no coliform positives were detected after disinfection and flushing.  The one exception was the aerator attached to the faucet typically installed in the lavatory, was positive for coliforms after disinfection. These data suggest that the faucet aerators could be a source of coliform contamination that may result in coliform positive samples taken under the ADWR.  Further experiments conducted on disinfection of aerators with glycolic acid and quaternary ammonia (both commonly used by the airlines) showed no detectable coliforms on coliform contaminated aerators after 30 minutes of soaking in the disinfectants.  However, many airlines disinfect aerators by the above methods or simply replace the aerators during each disinfection, effectively eliminating this potential source of coliform contamination. \n\nThis dataset is associated with the following publication:\nSzabo, J., M. Rodgers, J. Mistry, J. Steenbock, J. Hoelle, and J. Hall. The effectiveness of disinfection and flushing procedures to prevent coliform persistence in aircraft water systems.   JOURNAL OF WATER SUPPLY: RESEARCH AND TECHNOLOGY - AQUA. IWA Publishing, London,  UK,  1-8, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1390163",
            "keyword": [
                "drinking water",
                "Drinking water distribution system",
                "E. coli",
                "chlorine dioixde",
                "Ozone",
                "aircraft engines"
            ],
            "contactPoint": {
                "fn": "Jeffrey Szabo",
                "hasEmail": "mailto:szabo.jeff@epa.gov"
            },
            "distribution": [
                {
                    "title": "Aircraft Decon Analysis Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390163/Aircraft%20Decon%20Analysis%20Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-21",
            "references": [
                "https://doi.org/10.2166/ws.2018.195"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Calapooia_NInventory_2008",
            "description": "The dataset contains calculated results of annual and seasonal input of nitrogen from seven major sources in the Calapooia River Watershed and its subwatersheds. It also contains annual and seasonal export of nitrogen from crop harvest and stream export. \n\nThis dataset is associated with the following publication:\nLin, J., J. Compton, S. Leibowitz, G. Mueller-Warrant, W. Matthews, S. Schoenholz, D. Evans, and R. Coulombe. Seasonality of nitrogen balances in a Mediterranean climate watershed, Oregon, US.   BIOGEOCHEMISTRY. Springer, New York, NY, USA, 142(2): 247-264, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1500883",
            "keyword": [
                "Agriculture",
                "GIS",
                "nutrient use efficiency",
                "grass seed crops",
                "seasonal analysis",
                "water quality",
                "nitrogen"
            ],
            "contactPoint": {
                "fn": "Jiajia Lin",
                "hasEmail": "mailto:lin.jiajia@epa.gov"
            },
            "distribution": [
                {
                    "title": "Calapooia_NInventory_2008.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500883/Calapooia_NInventory_2008.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-05-22",
            "references": [
                "https://doi.org/10.1007/s10533-018-0532-0"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Peat fire emission factors",
            "description": "These data include calculated emissions factors for the peat fire data set. PAH, PCDD/PCDFs, BC and other pollutants are included. \n\nThis dataset is associated with the following publication:\nBlack, R., B. Gullett , I. George , J. Aurell, A. Holder , M. Hays , C. Geron , and D. Tabor. Characterization of Gas and Particle Emissions from Laboratory Burns of Peat.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 132: 49-57, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390095",
            "keyword": [
                "PM",
                "CO",
                "peat fires",
                "PAH",
                "PCDDs",
                "PCDD/PCDF"
            ],
            "contactPoint": {
                "fn": "Brian Gullett",
                "hasEmail": "mailto:gullett.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "Peat summary sheet 08 18 2014 BG.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390095/Peat%20summary%20sheet%2008%2018%202014%20BG.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-03-09",
            "references": [
                "https://doi.org/10.1016/j.atmosenv.2016.02.024"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Urban soil hydrology, hydraulic conductivity measurements",
            "description": "We used field measurements of seldom-assessed hydraulic conductivity in urban locations.\nAlthough emphasis is placed on soils as permeable surfaces that regulate the rainfall-runoff process, representative soil hydraulic and hydrologic parameters for urban areas are rare. The extent to which measured and commonly simulated hydraulic data may differ is also largely uncharacterized. As part of the EPA urban soil assessment infiltration and drainage rates were measured in 12 cities and compared these to estimates generated from the EPA National Stormwater Calculator (NSWC), USDA Soil Survey Geographic Database (SSURGO), and USDA Rosetta. \n\nThis dataset is associated with the following publication:\nSchifman, L., and W. Shuster. Comparison of Measured and Simulated Urban Soil Hydrologic Properties.   Journal of Hydrologic Engineering. American Society of Civil Engineers  (ASCE), Reston, VA, USA, 24(1): 04018056, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1395236",
            "keyword": [
                "Hydraulic Conductivity",
                "National Stormwater Calculator",
                "USDA Rosetta",
                "SSURGO",
                "Green Infrastructure",
                "pedotransfer functions"
            ],
            "contactPoint": {
                "fn": "William Shuster",
                "hasEmail": "mailto:shuster.william@epa.gov"
            },
            "distribution": [
                {
                    "title": "Schifman_UrbanSoilConductivity.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395236/Schifman_UrbanSoilConductivity.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-09-05",
            "references": [
                "https://doi.org/10.1061/(asce)he.1943-5584.0001684"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "In vitro and in vivo estrogen receptor data sets",
            "description": "In vitro and in vivo data for the estrogen receptor. The in vivo data is for binding, agonism, and antagonism. The in vivo data is from mouse uterotropic assay data.  The following columns are provided in each data set:  molecular id, SMILES structure, class (1=active, 0 =  inactive), and set (T=training, P=prediction set). \n\nThis dataset is associated with the following publication:\nMartin , T. Prediction of in vitro and in vivo oestrogen receptor activity using hierarchical clustering.   SAR AND QSAR IN ENVIRONMENTAL RESEARCH. Taylor & Francis, Inc., Philadelphia, PA, USA, 27(1): 17-30, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1503161",
            "keyword": [
                "qsar",
                "estrogenic activity in vitro and in vivo"
            ],
            "contactPoint": {
                "fn": "Todd Martin",
                "hasEmail": "mailto:martin.todd@epa.gov"
            },
            "distribution": [
                {
                    "title": "scihub data for ER paper.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503161/scihub%20data%20for%20ER%20paper.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-11-08",
            "references": [
                "https://doi.org/10.1080/1062936x.2015.1125945"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Summary of RHESSys Simulations of GI Sensitivity",
            "description": "Summary of RHESSys simulation output supporting the journal article title \"Simulated Sensitivity of Urban Green Infrastructure Practices to Climate Change\". \n\nThis dataset is associated with the following publication:\nSarkar, S., J. Butcher, T. Johnson, and C. Clark. Simulated Sensitivity of Urban Green Infrastructure Practices to Climate Change.   Earth Interactions. American Meteorological Society, Boston, MA, USA, 22(13): 1-37, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1427166",
            "keyword": [
                "climate",
                "urban",
                "bmp",
                "Green Infrastructure"
            ],
            "contactPoint": {
                "fn": "Thomas Johnson",
                "hasEmail": "mailto:johnson.thomas@epa.gov"
            },
            "distribution": [
                {
                    "title": "Sarkar_2018_GI Sensitivity_Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1427166/Sarkar_2018_GI%20Sensitivity_Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-03-20",
            "references": [
                "https://doi.org/10.1175/ei-d-17-0015.1"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Theoretical Study of Isoprene Peroxy Radical 1-5 Hydrogen Shift Reactions that Regenerate HOx Radicals and Produce Highly Oxidized Molecules",
            "description": "The attached extensive computational chemistry dataset involves detailed electronic structure (density functional theory - DFT) and kinetic calculation (master equation formalism) outputs for the reactions of isoprene and first generation oxidants with the hydroxyl radical. There are a total of 9 tabs in the Excel spreadsheet.  The first two tabs provide the potential energy surfaces (PESs) of the isoprene+OH and isopOOH+OH (1st generation oxidant) reactions.  The PESs are zero-point energy corrected and obtained at the M062x/maug-cc-pVTZ level of DFT.  The third tab provides the reaction barriers for first and second generation 1,5-hydrogen atom shifts for two different isoprene peroxy radical isomers with several different DFT methods.  The fourth and fifth tabs provide microcanonical rate constants for the reactions of isoprene and isopOOH with OH respectively. The remaining tabs give the rate constants for the 1,5-H shifts for four different isoprene peroxy radicals.  The rate constants are computed using the M062x density functional and an average of 4 different DFT methods given in tab 3 for comparison.  The average values are reported as the final rate constants determined by computational methods. \n\nThis dataset is associated with the following publication:\nPiletic, I., R. Howell, L. Bartolotti, T. Kleindienst, S. Kaushik, and E. Edney. Multigenerational Theoretical Study of Isoprene Peroxy Radical 1\u20135-Hydrogen Shift Reactions that Regenerate HOx Radicals and Produce Highly Oxidized Molecules.   JOURNAL OF PHYSICAL CHEMISTRY A. American Chemical Society, Washington, DC, USA, 123(4): 906-919, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1502513",
            "keyword": [
                "air quality",
                "NOx",
                "pm2.5",
                "ozone concentrations",
                "CMAQ",
                "computational chemistry",
                "atmospheric chemistry"
            ],
            "contactPoint": {
                "fn": "Ivan Piletic",
                "hasEmail": "mailto:piletic.ivan@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHub_IRPDataset_2018_IsopreneIsomerizationChemistry_Final.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502513/ScienceHub_IRPDataset_2018_IsopreneIsomerizationChemistry_Final.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-08-13",
            "references": [
                "https://doi.org/10.1021/acs.jpca.8b09738"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1502513/documents/COMPCHEMDataDictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Transformation of Silver Nanoparticle Consumer Products during Simulated Usage and Disposal",
            "description": "The data set contains the details on the silver speciation in silver nanoparticle consumer products and the transformation of the silver during their usage and disposal. Synthetic stomach fluid and wastewater sludge are used to create a model for the lifecycle of silver nanoparticle dietary supplements. \n\nThis dataset is associated with the following publication:\nPotter, P., J. Navratilova, K. Rogers, and S. Al-Abed. Transformation of silver nanoparticle consumer products during simulated usage and disposal.   Environmental Science: Nano. RSC Publishing, Cambridge,  UK, 6(2): 592-598, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1502493",
            "keyword": [
                "silver nanoparticles",
                "environmental fate and transformation",
                "consumer products",
                "particle size",
                "capping agent"
            ],
            "contactPoint": {
                "fn": "Souhail Al-Abed",
                "hasEmail": "mailto:al-abed.souhail@epa.gov"
            },
            "distribution": [
                {
                    "title": "raw data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502493/raw%20data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2018-06-29",
            "references": [
                "https://doi.org/10.1039/c8en00958a"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1502493/documents/data%20dictionary.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "PCBs in Caulk report 07132010",
            "description": "A method was developed to determine the levels of polychlorinated biphenyls (PCBs) in caulk and window glazing. This method was tested on a combination of 36 samples of caulk and glazing materials from older buildings in the northeastern area of the United States. \n\nThis dataset is associated with the following publication:\nOsemwengie, L., and J. Morgan. PCBs in Older Buildings: Measuring PCB Levels in Caulk and Window Glazing Materials in Older Buildings.   Environments. MDPI AG, Basel,  SWITZERLAND, 6(2): 15, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407532",
            "keyword": [
                "PCBs",
                "Pressurized liquid extraction (PLE)",
                "Caulking materials",
                "Arochlor",
                "gas chromatography",
                "Old buildings"
            ],
            "contactPoint": {
                "fn": "Lantis Osemwengie",
                "hasEmail": "mailto:osemwengie.lantis@epa.gov"
            },
            "distribution": [
                {
                    "title": "PCB final report 07132010.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407532/PCB%20final%20report%2007132010.xls",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "Metadata_A-p8dh_SDMP_20170307.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407532/Metadata_A-p8dh_SDMP_20170307.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2010-07-13",
            "references": [
                "https://doi.org/10.3390/environments6020015"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Variability of pyrethroid and pyrethroid degradate concentrations on hard surface kitchen flooring in occupied residences.",
            "description": "Concentrations of pyrethroids and pyrethroid degradates in surface wipe samples collected from occupied residences. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Restricted access may be granted to authorized persons by contacting the party listed. \r\nJames Starr\r\nResearch Physical Scientist\r\nUSEPA/ORD/NERL/EMMD/PHCB\r\nMD D205-05\r\n109 TW Alexander Dr.\r\nRTP, NC 27711. Format: These data are from a human study. The study design was approved by the US EPA\u2019s Human Subjects Research Review Official and the University of North Carolina\u2019s Institutional Review Board (study number 09-0741). \n\nThis dataset is associated with the following publication:\nStarr, J., S. Graham, W. Li, A. Gemma, and M. Morgan. Variability of pyrethroid concentrations on hard surface kitchen flooring in occupied housing.   INDOOR AIR. Blackwell Publishing, Malden, MA, USA, 28(5): 665-675, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1407682",
            "keyword": [
                "indoor",
                "pyrethorid degrates",
                "pyrethorids",
                "Wipe Sampling"
            ],
            "contactPoint": {
                "fn": "James Starr",
                "hasEmail": "mailto:starr.james@epa.gov"
            },
            "distribution": [],
            "modified": "2017-07-31",
            "references": [
                "https://doi.org/10.1111/ina.12471"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Bioaccessibility of fipronil sorbed to soils and house dusts",
            "description": "Bioaccessibility values for fipronil determined using 37 paired soil and dust samples. Values for the physicochemical properties of the soils and dusts used to model the bioaccessibility data. \n\nThis dataset is associated with the following publication:\nStarr , J., W. Li, S. Graham , K. Bradham , D. Stout , A. Williams , and J. Sylva. Using paired soil and house dust samples in an in vitro assay to assess the post ingestion bioaccessibility of sorbed fipronil.   JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, USA, 312: 141-149, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1500445",
            "keyword": [
                "fipronil",
                "Bioaccessibility",
                "ingestion",
                "Soils",
                "House dusts"
            ],
            "contactPoint": {
                "fn": "James Starr",
                "hasEmail": "mailto:starr.james@epa.gov"
            },
            "distribution": [
                {
                    "title": "Science Hub data Fipronil bioaccessibility.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500445/Science%20Hub%20data%20Fipronil%20bioaccessibility.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2016-05-16",
            "references": [
                "http://www.sciencedirect.com/science/article/pii/S0304389416302758"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The role of soil and house dust physicochemical properties in the post ingestion bioaccessibility of sorbed polychlorinated biphenyls",
            "description": "This file presents physicochemical properties of soils, house dusts, PCBs, and the bioaccessibility values calculated from the analysis of PCBs in the soils, house dusts, and synthetic digestive fluids. Bioaccessibility values were calculated using the ratio of the analyte in the sediment relative to that in the digestive fluids. The first tab in the excel spreadsheet is the data dictionary and contains the meta data (column headings and fields).  The second tab contains the soil/dust/PCB physicochemical properties and the associated bioaccessibility values. \n\nThis dataset is associated with the following publication:\nShen, H., W. Li, S. Graham, and J. Starr. The role of soil and house dust physicochemical properties in determining the post ingestion bioaccessibility of sorbed polychlorinated biphenyls.   CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 217: 1-8, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1500917",
            "keyword": [
                "Polychlorinated biphenyls",
                "Bioaccessibility Soil",
                "House dust",
                "ingestion",
                "physicochemical properties"
            ],
            "contactPoint": {
                "fn": "James Starr",
                "hasEmail": "mailto:starr.james@epa.gov"
            },
            "distribution": [
                {
                    "title": "PCB data for ScienceHub_Final.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500917/PCB%20data%20for%20ScienceHub_Final.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-06-01",
            "references": [
                "https://doi.org/10.1016/j.chemosphere.2018.10.195"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Datasets used in ORD-023413: Frequent Modulation of the Sterol Regulatory Element Binding Protein (SREBP) by Chemical Exposure in the Livers of Rats ",
            "description": "Datasets used in ORD-023413: Frequent Modulation of the Sterol Regulatory Element Binding Protein (SREBP) by Chemical Exposure in the Livers of Rats. \n\nThis dataset is associated with the following publication:\nCorton, C. Frequent modulation of the sterol regulatory element binding protein (SREBP) by chemical exposure in the livers of rats.   Computational Toxicology. Elsevier B.V., Amsterdam,  NETHERLANDS, 10: 113-129, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407626",
            "keyword": [
                "Gene Expression Omnibus Accession Numbers",
                "sterol regulatory element binding protein",
                "cholesterol synthesis",
                "fatty acid synthesis",
                "microarray",
                "fatty liver disease",
                "hepatic steatosis"
            ],
            "contactPoint": {
                "fn": "Jon Corton",
                "hasEmail": "mailto:corton.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data submission for A-1ns5.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407626/Data%20submission%20for%20A-1ns5.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-01",
            "references": [
                "https://doi.org/10.1016/j.comtox.2019.01.007"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for 3D Organoid Model Assessment of Influence of Chemicals on Morphogenetic Fusion.",
            "description": "Organogenesis in the embryo involves cell differentiation and organization events that are unique to each tissue and organ and are susceptible to developmental toxicants. Animal models are the gold standard for identifying putative teratogens, but the limited throughput of developmental toxicological studies in animals coupled with the limited concordance between animal and human teratogenicity motivates a different approach. In vitro organoid models can mimic the cellular architecture and phenotype of many tissues and organs, and the three-dimensional (3D) architecture of organoids presents an opportunity to study developmental human toxicology. Common themes during development like the involvement of epithelial-mesenchymal transition and tissue fusion present an opportunity to develop in vitro models to study cell and tissue morphogenesis. We previously described organoids composed of human stem and progenitor cells that recapitulated the cellular features of palate fusion, and here we further characterized the model by examining pharmacological inhibitors targeting known palatogenesis and epithelial morphogenesis pathways as well as twelve cleft palate teratogens identified from rodent models. Organoid survival was dependent on signaling through EGF, IGF, HGF, and FGF pathways, and organoid fusion was disrupted by inhibition of BMP signaling. We observed concordance between the effects of EGF, FGF, and BMP inhibitors on organoid fusion and epithelial cell migration in vitro, suggesting that organoid fusion is dependent on epithelial morphogenesis. Three of the twelve putative cleft palate teratogens studied here significantly disrupted in vitro fusion, including theophylline, triamcinolone, and valproic acid. Tributyltin chloride and all-trans retinoic acid (ATRA) were cytotoxic to fusing organoids.  The study herein demonstrates the utility of the in vitro fusion assay for identifying chemicals that disrupt human organoid survival and morphogenesis in a scalable format amenable to toxicology screening. \n\nThis dataset is associated with the following publication:\nBelair, D., C. Wolf, S. Moorefield, C. Wood, C. Becker, and B. Abbott. A Three-Dimensional Organoid Culture Model to Assess the Influence of Chemicals on Morphogenetic Fusion..   TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA,   394-408, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1432529",
            "keyword": [
                "mesenchymal cells",
                "tissue engineering",
                "extracellular matrix",
                "teratogens",
                "pharmacological inhibitors",
                "Morphogenetic fusion",
                "palate fusion",
                "stromal cells",
                "epithelial cells",
                "cell spheroids",
                "osteogenesis"
            ],
            "contactPoint": {
                "fn": "Barbara Abbott",
                "hasEmail": "mailto:abbott.barbara@epa.gov"
            },
            "distribution": [
                {
                    "title": "Belair et al 2018 Main Text & Suppl Figures Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1432529/Belair%20et%20al%202018%20Main%20Text%20%26%20Suppl%20Figures%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-04-10",
            "references": [
                "https://doi.org/10.1093/toxsci/kfy207"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset for Summertime organic carbon absorption and sources at a southeastern U.S. location - dominance of secondary organic aerosol",
            "description": "The data tables in this file were used to generate the figures in the manuscript, \"Summertime organic carbon absorption and sources at a southeastern U.S. location - dominance of secondary organic aerosol\". Light-absorbing organic carbon, i.e. brown carbon, has been intensively investigated in atmospheres impacted by biomass burning impacted atmospheres. However, other brown carbon sources have been rarely studied in ambient aerosols. This data set includes forty-five PM2.5 filter samples that were collected in Research Triangle Park (RTP), NC, USA from June 1st to July 15th, 2013. The bulk carbonaceous components, including organic carbon, elemental carbon, water soluble organic carbon, and an array of organic molecular markers were measured; an ultraviolet (UV)/visible  (Vis) spectrometer was used to measure the light absorption of methanol and water extractable organic carbon. A complete description of how the data was acquired and and analyzed is provided in the manuscript.  A description of each parameter presented is provided in the file in the Data Dictionary. \n\nThis dataset is associated with the following publication:\nXie, M., X. Chen, A. Holder, M. Hays, M. Lewandowski, J. Offenberg, T. Kleindienst, and M. Jaoui. Summertime organic carbon absorption and sources at a southeastern U.S. location \u2013 dominance of secondary organic aerosol.   ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 244: 38-46, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1424737",
            "keyword": [
                "Combustion Emissions",
                "Black Carbon",
                "Brown Carbon",
                "Fine Particulate Matter",
                "Aerosol Optical Properties",
                "Secondary Organic Aerosol"
            ],
            "contactPoint": {
                "fn": "Amara Holder",
                "hasEmail": "mailto:holder.amara@epa.gov"
            },
            "distribution": [
                {
                    "title": "SOAS Light absorption Data for Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1424737/SOAS%20Light%20absorption%20Data%20for%20Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-03-08",
            "references": [
                "https://doi.org/10.1016/j.envpol.2018.09.125"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Investigating the role of distributed energy in the industrial and commercial sectors in the U.S. to attain greenhouse gas reductions goals ",
            "description": "The dataset presents the metadata going into Figures presented in the manuscript. \n\nThis dataset is associated with the following publication:\nKaplan, O., and J. Witt. What is the role of distributed energy resources under scenarios of greenhouse gas reductions? A specific focus on combined heat and power systems in the industrial and commercial sectors.   Applied Energy. Elsevier B.V., Amsterdam,  NETHERLANDS, 235: 83-94, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1500446",
            "keyword": [
                "energy modeling",
                "industrial sector",
                "chp",
                "greenhouse gases",
                "air pollution"
            ],
            "contactPoint": {
                "fn": "Pervin Kaplanakman",
                "hasEmail": "mailto:kaplan.ozge@epa.gov"
            },
            "distribution": [
                {
                    "title": "KaplanWitt_the role of distributed energy in industrial and commercial sectors_dataset 06JUNE2018.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500446/KaplanWitt_the%20role%20of%20distributed%20energy%20in%20industrial%20and%20commercial%20sectors_dataset%2006JUNE2018.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-05-15",
            "references": [
                "https://doi.org/10.1016/j.apenergy.2018.10.125"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Scenario Output Table",
            "description": "Output from three different scenarios generated using stormwater management planning support software to reduce occurrence of combined sewer overflow events through the use of green infrastructure. \n\nThis dataset is associated with the following publication:\nFu, X., H. Goddard, X. Wang, and M. Hopton. Development of a scenario-based stormwater management planning support system for reducing combined sewer overflows (CSOs).   JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 236: 571-580, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1502523",
            "keyword": [
                "Green Infrastructure",
                "scenario planning",
                "stormwater management"
            ],
            "contactPoint": {
                "fn": "Matthew Hopton",
                "hasEmail": "mailto:hopton.matthew@epa.gov"
            },
            "distribution": [
                {
                    "title": "Output of the paper SWPSS-CSO to STICS.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502523/Output%20of%20the%20paper%20SWPSS-CSO%20to%20STICS.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-08-06",
            "references": [
                "https://doi.org/10.1016/j.jenvman.2018.12.089"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for Measures of abdominal obesity, metabolic dysfunction, and metabolic syndrome in United States adolescents: exploratory analysis using the National Health and Nutrition Examination Survey (NHANES) 2011-2014 data ",
            "description": "NHANES data from the 2011-2014 survey years. Specific to adolescents. Ancillary data related to metabolic syndrome and other covariates. \n\nThis dataset is associated with the following publication:\nGaston, S., N. Tulve, and T. Ferguson. Abdominal obesity, metabolic dysfunction, and metabolic syndrome in U.S. adolescents: National Health and Nutrition Examination Survey 2011\u20132016.   ANNALS OF EPIDEMIOLOGY. Elsevier Science Ltd, New York, NY, USA, 30: 30-36, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1407701",
            "keyword": [
                "adolescents",
                "NHANES",
                "metabolic syndrome"
            ],
            "contactPoint": {
                "fn": "Nicolle Tulve",
                "hasEmail": "mailto:tulve.nicolle@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data for Measures of abdominal obesity metabolic dysfunction and metabolic syndrome in United States adolescents- exploratory analysis using the National Health and Nutrition Examination Survey 2011-2014 data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407701/Data%20for%20Measures%20of%20abdominal%20obesity%20metabolic%20dysfunction%20and%20metabolic%20syndrome%20in%20United%20States%20adolescents-%20exploratory%20analysis%20using%20the%20National%20Health%20and%20Nutrition%20Examination%20Survey%202011-2014%20data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-08-01",
            "references": [
                "https://doi.org/10.1016/j.annepidem.2018.11.009"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1407701/documents/Data%20dictionary_NHANES_11_14_SAD_vs_WC.xlsx",
            "describedByType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Wetland Figures/Tables Dataset",
            "description": "Data sets for all figures and tables in the manuscript. \n\nThis dataset is associated with the following publication:\nMcMinn, B., S. Klemm, A. Korajkic, K. Wyatt, M. Herrmann, R. Haugland, J. Lu, E. Villegas, and C. Frye. A constructed wetland for treatment of an impacted waterway and the influence of native waterfowl on its perceived effectiveness..   ECOLOGICAL ENGINEERING. Elsevier Science Ltd, New York, NY, USA, 128: 48-56, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1502595",
            "keyword": [
                "wetland",
                "Microbial Source Tracking",
                "fecal indicator"
            ],
            "contactPoint": {
                "fn": "Brian McMinn",
                "hasEmail": "mailto:mcminn.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHubData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502595/ScienceHubData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-06-26",
            "references": [
                "https://doi.org/10.1016/j.ecoleng.2018.11.026"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Method Comparison Manuscript",
            "description": "Coliphage are alternative fecal indicators that may be suitable surrogates for viral pathogens, but a majority of standard detection methods utilize insufficient sample volumes (1-100 mL) for routine detection in environmental waters. Here we compare three somatic and F+ coliphage enumeration methods based on a paired measurement from 1L samples collected from the Great Lakes region (n=74). Methods include: 1) a dead-end hollow fiber ultrafilter combined with single agar layer plaque assay (D-HFUF-SAL); 2) a modified SAL (M-SAL); and 3) a direct membrane filtration (DMF) technique. Overall, D-HFUF-SAL outperformed all other methods as it yielded the lowest frequency of non-detects [(ND); 10.8%] and the highest average coliphage concentrations (2.51 \u00b1 1.02 log10 plaque forming unit/liter (PFU/L) and 0.79 \u00b1 0.71 log10 PFU/L for somatic and F+, respectively). M-SAL yielded 29.7% ND and average concentrations of 2.26 \u00b1 1.15 log10 PFU/L (somatic) and 0.59 \u00b1 0.82 log10 PFU/L (F+). DMF performed worse compared to D-HFUF-SAL and M-SAL methods (ND of 65.6%; average somatic coliphage concentration 1.52 \u00b1 1.32 log10 PFU/L, with no F+ detected), indicating this procedure is unsuitable for 1L surface water sample volumes. This study represents an important step toward the use of a coliphage method for recreational water quality criteria purposes. \n\nThis dataset is associated with the following publication:\nMcMinn, B., E. Rhodes, E. Huff, P. Wanjugi, M. Ware, S. Nappier, M. Cyterski, O. Shanks, K. Oshima, and A. Korajkic. Comparison of somatic and F+ coliphage enumeration methods with large volume surface water samples.   JOURNAL OF VIROLOGICAL METHODS. Elsevier Science Ltd, New York, NY, USA, 261: 63-66, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1434005",
            "keyword": [
                "coliphage",
                "culture-based methods",
                "method comparison"
            ],
            "contactPoint": {
                "fn": "Asja Korajkic",
                "hasEmail": "mailto:korajkic.asja@epa.gov"
            },
            "distribution": [
                {
                    "title": "ScienceHub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1434005/ScienceHub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-04-23",
            "references": [
                "https://doi.org/10.1016/j.jviromet.2018.08.007"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Florida cattle decay study",
            "description": "Fecal contamination of recreational waters with cattle manure can pose a risk to public health due to the potential presence of various zoonotic pathogens. Fecal indicator bacteria (FIB) have a long history of use in the assessment. However, FIB quantification provides no information about pollution sources. Microbial source tracking (MST) genetic markers have been developed in response to a need to identify pollution sources, yet factors that influence host-identifier target decay once discharged into the environment are often poorly understood, especially for agriculture fecal waste sources. Here, we investigate the influence of water type (freshwater versus marine) and select environmental parameters (indigenous microbiota, ambient sunlight) on the decay of FIB and MST genetic markers originating from cattle manure. Experiments were conducted in situ using a submersible aquatic mesocosm containing dialysis bags filled with a mixture of cattle manure and ambient water. Culturable FIB (E. coli and enterococci) were enumerated by membrane filtration and the concentration of general fecal indicator bacteria (GenBac3, Entero1a, and EC23S857) and MST (Rum2Bac, CowM2, and CowM3) genetic markers were estimated by qPCR. Water type was the most significant factor influencing the decay of cattle manure indicator bacteria (three-way ANOVA, p: 0.006 to < 0.001), although the magnitude of the effect differed among microbial targets and over time. The presence of indigenous microbiota and exposure to sunlight were both significantly correlated (three-way ANOVA, p: 0.044 to < 0.001) with decay of enterococci and CowM2, while E. coli, EC23S857, Rum2Bac, and CowM3 (three-way ANOVA, p: 0.044 <0.001) were significantly impacted by either sunlight or indigenous microbiota. Findings indicate the extended persistence (>144 hours) of both cultivated FIB and genetic markers in marine and freshwater water types. Findings suggest that multiple environmental stressors are important determinants of FIB and MST marker persistence, but their magnitude can vary across different indicators. Selective exclusion of natural aquatic microbiota and/or sunlight typically resulted in extended survival, but the effect was minor and limited to select microbial targets. \n\nThis dataset is associated with the following publication:\nKorajkic, A., B. McMinn, N. Ashbolt, M. Sivaganesan, V. Harwood, and O. Shanks. Extended persistence of general and cattle-associated fecal indicators in marine and freshwater environment.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 650(1): 1292-1302, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1502486",
            "keyword": [
                "decay",
                "fecal indicator bacteria",
                "microbial source tracking markers",
                "pathogens",
                "biotic factors",
                "abiotic factors"
            ],
            "contactPoint": {
                "fn": "Asja Korajkic",
                "hasEmail": "mailto:korajkic.asja@epa.gov"
            },
            "distribution": [
                {
                    "title": "FL cattle decay data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502486/FL%20cattle%20decay%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-07-17",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.09.108"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "FIB concentrations, rate of release from manure, FIB transport, daily flow, non-point source",
            "description": "FIB concentrations, rate of release from manure, FIB transport, daily flow, non-point source. \n\nThis dataset is associated with the following publication:\nKim, K., G. Whelan, M. Molina, R. Parmar, K. Wolfe, M. Galvin, P. Duda, R. Zepp, J. Kinzelman, G. Kleinheinz, and M. Borchardt. Using Integrated Environmental Modeling to Assess Sources of Microbial Contamination in Mixed-Use Watersheds.   JOURNAL OF ENVIRONMENTAL QUALITY. American Society of Agronomy, MADISON, WI, USA, 47(5): 1103-1114, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1433315",
            "keyword": [
                "Integrated environmental modeling",
                "manure",
                "pathogens",
                "QMRA",
                "Risk Assessment",
                "source apportionment",
                "watershed modeling"
            ],
            "contactPoint": {
                "fn": "Marirosa Molina",
                "hasEmail": "mailto:molina.marirosa@epa.gov"
            },
            "distribution": [
                {
                    "title": "RDB_files_062017.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1433315/RDB_files_062017.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Calibration Files_061617.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1433315/Calibration%20Files_061617.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2017-06-17",
            "references": [
                "https://doi.org/10.2134/jeq2018.02.0071"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Phage Data",
            "description": "Phage Data. \n\nThis dataset is associated with the following publication:\nZepp, R., M. Cyterski, K. Wong , O. Georgacopoulos, B. Acrey, G. Whelan, R. Parmar, and M. Molina. Biological Weighting Functions for Evaluating the Role of Sunlight-Induced Inactivation of Coliphages at Selected Beaches and Nearby Tributaries.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(22): 13068-13076, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1433318",
            "keyword": [
                "drinking water",
                "Great Lakes",
                "microbial fate and transport",
                "recreational waters"
            ],
            "contactPoint": {
                "fn": "Richard Zepp",
                "hasEmail": "mailto:zepp.richard@epa.gov"
            },
            "distribution": [
                {
                    "title": "Action_Spectra data .xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1433318/Action_Spectra%20data%20.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-10-04",
            "references": [
                "https://doi.org/10.1021/acs.est.8b02191"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Watford_Novel_application__NPMI_Biomedlit_genesets_usecase_breast_cancer",
            "description": "We present a novel use of normalized pointwise mutual information (NPMI) to mine biomedical literature for gene associations with biological concepts as represented by Medical Subject Headings (MeSH terms) in PubMed. \n\nThis dataset is associated with the following publication:\nWatford, S., R. Grashow, V. De La Rosa, R. Rudel, K. Paul-Friedman, and M. Martin. Novel application of normalized pointwise mutual information (NPMI) to mine biomedical literature for gene sets associated with disease: Use case in breast carcinogenesis.   Computational Toxicology. Elsevier B.V., Amsterdam,  NETHERLANDS, 7: 46-57, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1502465",
            "keyword": [
                "Biomedical Literature",
                "Data Integration",
                "genes",
                "Breast Carcinogenesis",
                "Chemical Exposures",
                "Literature Mining",
                "ACToR"
            ],
            "contactPoint": {
                "fn": "Richard Judson",
                "hasEmail": "mailto:judson.richard@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/Watford/Novel_application__NPMI_Biomedlit_genesets_usecase_breast_cancer",
                    "accessURL": "https://gaftp.epa.gov/COMPTOX/NCCT_Publication_Data/Watford/Novel_application__NPMI_Biomedlit_genesets_usecase_breast_cancer"
                },
                {
                    "title": "https://doi.org/10.23645/epacomptox.6635564",
                    "accessURL": "https://doi.org/10.23645/epacomptox.6635564"
                },
                {
                    "title": "https://github.com/USEPA/CompTox-HTTr-EMCON",
                    "accessURL": "https://github.com/USEPA/CompTox-HTTr-EMCON"
                }
            ],
            "modified": "2018-10-15",
            "references": [
                "https://doi.org/10.1016/j.comtox.2018.06.003"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CatronTara_A-brvd_MB2Dataset_20180221",
            "description": "This file contains data used to generate figures shown in Catron et al. Characterization of host toxicity and microbiota disruption in larval zebrafish following developmental exposure to BPA and BPA alternatives. \n\nThis dataset is associated with the following publication:\nCatron, T., S. Keely, N. Brinkman, T. Zurlinden, C. Wood, J. Wright, D. Phelps, E. Wheaton, A. Kvasnicka, S. Gaballah, R. Lamendella, and T. Tal. Host Developmental Toxicity of BPA and BPA Alternatives Is Inversely Related to Microbiota Disruption in Zebrafish.   TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA,  167(2): 468-483, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1417030",
            "keyword": [
                "Bisphenol A (BPA)",
                "zebrafish",
                "microbiome",
                "Developmental Toxicity"
            ],
            "contactPoint": {
                "fn": "Tara Catron",
                "hasEmail": "mailto:catron.tara@epa.gov"
            },
            "distribution": [
                {
                    "title": "CatronTara_A-brvd_MB2Dataset_201801005.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1417030/CatronTara_A-brvd_MB2Dataset_201801005.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-02-21",
            "references": [
                "https://doi.org/10.1093/toxsci/kfy261"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Emergy accounting of Greater Cincinnati water and wastewater systems",
            "description": "All the data used to generate figures and tables, the background data such as unit emergy value library are in the dataset. \n\nThis dataset is associated with the following publication:\nArden, S., C. Ma, and M. Brown. Holistic Analysis of Urban Water Systems in the Greater Cincinnati Region: (2) Resource Use Profiles by Emergy Accounting Approach - journal needs to be Water Research X.   Water Research X. Elsevier B.V., Amsterdam,  NETHERLANDS, 2: 100012, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1417304",
            "keyword": [
                "Emergy",
                "Integrated Urban Water Management",
                "sustainability",
                "system analysis",
                "Resource Efficiency"
            ],
            "contactPoint": {
                "fn": "Xin Ma",
                "hasEmail": "mailto:ma.cissy@epa.gov"
            },
            "distribution": [
                {
                    "title": "Arden et al., 2017 Tables Figures and SI (9.21.17) - old UEVs.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1417304/Arden%20et%20al.%2C%202017%20Tables%20Figures%20and%20SI%20%289.21.17%29%20-%20old%20UEVs.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-03-07",
            "references": [
                "https://doi.org/10.1016/j.wroa.2018.100012"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Transport of Nanohybrids Dataset",
            "description": "Characterization of nanohybrids using TEM, XPS, zeta potential measurement, UV-Vis spectrometry. Modeling results of nanohybrids transport. \n\nThis dataset is associated with the following publication:\nWang, D., Y. Jin, C. Park, J. Heo, X. Bai, N. Aich, and C. Su. Modeling the Transport of the \"New Horizon\" Reduced Graphene Oxide\u2014Metal Oxide Nanohybrids in Water-Saturated Porous Media.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52: 4610-4622, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1500938",
            "keyword": [
                "Column transport test",
                "reduced graphene oxide (RGO)-magnetite (Fe3O4)",
                "RGO-titanium dioxide (TiO2)",
                "and RGO-zinc oxide (ZnO) nanohybrids"
            ],
            "contactPoint": {
                "fn": "Chunming Su",
                "hasEmail": "mailto:su.chunming@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data_Wang Su EST Paper_2018.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500938/Data_Wang%20Su%20EST%20Paper_2018.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2018-06-12",
            "references": [
                "https://doi.org/10.1021/acs.est.7b06488"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Abiotic hydroxylamine nitrification involving manganese- and iron-bearing minerals. ",
            "description": "Data used in the figures and tables presented in the manuscript. \n\nThis dataset is associated with the following publication:\nRue, K., K. Rusevova, C. Biles, and S. Huling. Abiotic hydroxylamine nitrification involving manganese- and iron-bearing minerals.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, issue}: 567-575, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1432363",
            "keyword": [
                "Hydroxylamine",
                "Abiotic nitrification",
                "manganese",
                "iron",
                "nitrous oxide"
            ],
            "contactPoint": {
                "fn": "Scott Huling",
                "hasEmail": "mailto:huling.scott@epa.gov"
            },
            "distribution": [
                {
                    "title": "Abiotic Hydroxylamine Nitrification_Huling_Results_Science Hub.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1432363/Abiotic%20Hydroxylamine%20Nitrification_Huling_Results_Science%20Hub.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-04-12",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.06.397"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1432363/documents/Data%20Dictionary%20for%20SDMP_Abiotic%20Hydroxylamine%20Nitrification.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CIMEK water chemistry",
            "description": "Water chemistry data from 60 sites in a partially mined eastern Kentucky watershed.  Sites are spatially located from headwater tributaries to mouth for analysis of cumulative downstream impacts. \n\nThis dataset is associated with the following publication:\nJohnson, B., E. Smith, J. Ackerman, S. Dye, R. Polinsky, E. Somerville, C. Decker, D. Little, G. Pond, and E. DAmico. Spatial Convergence in Major Dissolved Ion Concentrations and Implications of Headwater Mining for Downstream Water Quality.   JAWRA. American Water Resources Association, Middleburg, VA, USA, 55(1): 247-258, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407636",
            "keyword": [
                "chemistry",
                "mining",
                "network",
                "solute",
                "stream",
                "valley fill",
                "Watershed",
                "water chemistry"
            ],
            "contactPoint": {
                "fn": "Brent Johnson",
                "hasEmail": "mailto:johnson.brent@epa.gov"
            },
            "distribution": [
                {
                    "title": "Water Chem analyses.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407636/Water%20Chem%20analyses.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Collated Water Chemistry All dates.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407636/Collated%20Water%20Chemistry%20All%20dates.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-18",
            "references": [
                "https://doi.org/10.1111/1752-1688.12725"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Non-Targeted Analysis of ENTACT Mixtures",
            "description": "Results from a non-targeted analysis of synthetic chemical mixtures. \n\nThis dataset is associated with the following publication:\nSobus, J., J. Grossman, A. Chao, R. Singh, A. Williams, C. Grulke, A. Richard, S. Newton, A. McEachran, and E. Ulrich. Using Prepared Mixtures of ToxCast Chemicals to Evaluate Non-Targeted Analysis (NTA) Method Performance..   Analytical and Bioanalytical Chemistry. Springer, New York, NY, USA, 411(4): 835-851, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1500907",
            "keyword": [
                "entact",
                "exposome",
                "mass spectrometry",
                "non-targeted analysis",
                "ToxCast"
            ],
            "contactPoint": {
                "fn": "Jon Sobus",
                "hasEmail": "mailto:sobus.jon@epa.gov"
            },
            "distribution": [
                {
                    "title": "Supplemental_Manuscript_Tables_Final.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500907/Supplemental_Manuscript_Tables_Final.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-05-17",
            "references": [
                "https://doi.org/10.1007/s00216-018-1526-4"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Chemical composition of isoprene SOA under acidic and non-acidic conditions: Effect of relative humidity",
            "description": "The effect of acidity and relative humidity on bulk isoprene aerosol parameters has been investigated in several studies, however few measurements have been conducted on individual aerosol compounds. The focus of this study has been the examination of the effect of acidity and relative humidity on secondary organic aerosol (SOA) chemical composition from isoprene photooxidation in the presence of nitrogen oxide (NOx). A detailed characterization of SOA at the molecular level was also investigated. Experiments were conducted in a 14.5 m3 smog chamber operated in flow mode. Based on a detailed analysis of mass spectra obtained from gas chromatography-mass spectrometry of silylated derivatives in electron impact and chemical ionization modes, and ultra-high performance liquid chromatography/electrospray ionization/time-of-flight high resolution mass spectrometry, and collision-induced dissociation in the negative ionization modes, we characterized not only typical isoprene products, but also new oxygenated compounds. A series of nitroxy-organosulfates (OS) were tentatively identified on the basis of high resolution mass spectra. Under acidic conditions, the major identified compounds include 2-methyltetrols (2MT), 2-methylglyceric acid (2MGA) and 2MT-OS. Other products identified include epoxydiols, mono- and dicarboxylic acids, other organic sulfates, and nitroxy- and nitrosoxy-OS. The contribution of SOA products from isoprene oxidation to PM2.5 was investigated by analysing ambient aerosol collected at rural sites in Poland. Methyltetrols, 2MGA and several organosulfates and nitroxy-OS were detected in both the field and laboratory samples. The influence of relative humidity on SOA formation was modest in non-acidic seed experiments, and stronger under acidic seed aerosol. Total secondary organic carbon decreased with increasing relative humidity under both acidic and non-acidic conditions. While the yields of some of the specific organic compounds decreased with increasing relative humidity others varied in an indeterminate manner from changes in the relative humidity. \n\nThis dataset is associated with the following publication:\nNestorowicz, K., M. Jaoui, K. Rudzinski, M. Lewandowski, T. Kleindienst, G. Spolnik, W. Danikiewicz, and R. Szmigielski. Chemical Composition of Isoprene SOA Under Acidic and Non-Acidic Conditions: Effect of Relative Humidity.   Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau,  GERMANY, 18(4): 18101-18121, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1423026",
            "keyword": [
                "isoprene",
                "organosulfate",
                "GC-MS",
                "LC-MS",
                "air quality",
                "Secondary Organic Aerosol",
                "air toxics",
                "Ozone"
            ],
            "contactPoint": {
                "fn": "Michael Lewandowski",
                "hasEmail": "mailto:lewandowski.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "Nestorowicz et al Fig 1-2-4.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1423026/Nestorowicz%20et%20al%20Fig%201-2-4.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-12-03",
            "references": [
                "https://doi.org/10.5194/acp-18-18101-2018"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for \"The impact of U.S. wildland fires on ozone and particulate matter: a comparison of measurements and CMAQ model predictions from 2008-2012\"",
            "description": "This dataset contains the underlying data for the evaluation of a 5 year CMAQ simulation with and without fires. The pollutant evaluated in the journal article is PM2.5.  Daily Average concentrations of PM2.5 from two 5 year CMAQ simulations are included.  Area burned on a daily basis is also included. Finally model and observed paired CSV files of PM2.5 are included for the 5 year simulation from the IMPROVE and CSN networks. Datasets are in several formats including netCDF (tar and zipped), csv (tar and zipped), and Excel. \n\nThis dataset is associated with the following publication:\nWilkins, J., G. Pouliot, K. Foley, W. Appel, and T. Pierce. The impact of US wildland fires on ozone and particulate matter: a comparison of measurements and CMAQ model predictions from 2008 to 2012.   International Journal of Wildland Fire. CSIRO Publishing, Collingwood Victoria,  AUSTRALIA, 27(10): 684-698, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1500891",
            "keyword": [
                "CSN",
                "IMPROVE",
                "emissions",
                "CMAQ",
                "Wildland Fire",
                "biomass burning",
                "air quality modeling"
            ],
            "contactPoint": {
                "fn": "Sergey Napelenok",
                "hasEmail": "mailto:napelenok.sergey@epa.gov"
            },
            "distribution": [
                {
                    "title": "Wilkins_A-nckf_Dataset_figures6-7.20181107.tar.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500891/Wilkins_A-nckf_Dataset_figures6-7.20181107.tar.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Wilkins_A-nckf_Dataset_figures1-2-3.2008.20181107.tar.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500891/Wilkins_A-nckf_Dataset_figures1-2-3.2008.20181107.tar.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Wilkins_A-nckf_Dataset_figures1-2-3.2009.20181107.tar.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500891/Wilkins_A-nckf_Dataset_figures1-2-3.2009.20181107.tar.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Wilkins_A-nckf_Dataset_figures1-2-3.2010.20181107.tar.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500891/Wilkins_A-nckf_Dataset_figures1-2-3.2010.20181107.tar.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Wilkins_A-nckf_Dataset_figures1-2-3.2012.20181107.tar.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500891/Wilkins_A-nckf_Dataset_figures1-2-3.2012.20181107.tar.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Wilkins_A-nckf_Dataset_figures1-2-3.2011.20190131.tar.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500891/Wilkins_A-nckf_Dataset_figures1-2-3.2011.20190131.tar.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Wilkins_A-nckf_Dataset_figure4.20190131.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500891/Wilkins_A-nckf_Dataset_figure4.20190131.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Wilkins_A-nckf_Dataset_metadata_20190131.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500891/Wilkins_A-nckf_Dataset_metadata_20190131.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-11-07",
            "references": [
                "https://doi.org/10.1071/wf18053"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Raw data for seed germination study with biochar and 8 plant species.",
            "description": "Biochar is being evaluated as an amendment to improve soil characteristics to increase crop yields, revitalize degraded soils and facilitate the establishment of plant cover. Unfortunately, there are few rapid tests to determine potential effects of biochar on soil and associated plant responses. Seed germination (emergence of hypocotyl) is a critical parameter for plant establishment and may be a rapid indicator of biochar effects. We adapted Oregon State University Seed Laboratory procedures to develop a \u201crapid-test\u201d to screen for effects of biochar on seed germination and soil characteristics. Soils were amended with 1% biochar by weight and placed in 11.0 cm square x 3.5 cm deep containers fitted with premoistened blotter paper. Seeds were placed in a uniform 5 x 5 pattern and covered with 15 g of the soil-biochar mixtures. Two South Carolina Coastal Plain soils, the Norfolk (Fine-loamy, kaolinitic, thermic Typic Kandiudults) and Coxville (Fine, kaolinitic, thermic Typic Paleaquults), were used. Eighteen biochars were evaluated produced from 6 feedstocks [pine chips (PC), poultry litter (PL), swine solids (SS), switchgrass (SG); and two blends of PC and PL, 50% PC/50% PL (55), and 80% PC/20% PL (82).  For each feedstock biochars were made by pyrolysis at 350, 500 and 700\u00b0C for 1-2 hours.  Percent germination and shoot dry weight were evaluated for cabbage, carrot, cucumber, lettuce, oat, onion, perennial ryegrass and tomato. Soil pH, electrical conductivity (EC) and extractable phosphorus (EP), factors which can affect seed germination and early seedling growth, were determined after plant harvests.  Germination primarily was affected by soil type with few biochar effects. Shoot dry weight was increased for carrot, lettuce, oat and tomato; primarily with biochars containing PL. Soil pH and EC increased with PL, SS, 55 and most 82 treatments across soil types and plant species.  Soil EP increased substantially with SS and PL and to a lesser extent with 55 and 82 for both soils across species, and with SG pyrolyzed at 550 and 750\u00b0C soil for the Norfolk soil across species.  Thus, this rapid-test method can be an early indicator of the effects of biochar on seed germination and important soil health characteristics which can be affected by biochar and effect seed germination. \n\nThis dataset is associated with the following publication:\nOlszyk, D.M., T. Shiroyama, J.M. Novak, and M.G. Johnson. A Rapid-Test for Screening Biochar Effects on Seed Germination.   Communications in Soil Science and Plant Analysis. Taylor & Francis Group, London,  UK, 49(16): 2025-2041, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1411437",
            "keyword": [
                "feedstock",
                "temperature",
                "crop",
                "biochar",
                "soil",
                "plants",
                "remediation"
            ],
            "contactPoint": {
                "fn": "Mark Johnson",
                "hasEmail": "mailto:johnson.markg@epa.gov"
            },
            "distribution": [
                {
                    "title": "Biochar Germination Study Biochar pH EC P.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1411437/Biochar%20Germination%20Study%20Biochar%20pH%20EC%20P.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "Biochar Germ All Species For SH 053118.xls",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1411437/Biochar%20Germ%20All%20Species%20For%20SH%20053118.xls",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2017-12-06",
            "references": [
                "https://doi.org/10.1080/00103624.2018.1495726"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Legionella-biofilm dataset",
            "description": "Water quality measurements, disinfectant decay during experiments, raw data, qPCR data. \n\nThis dataset is associated with the following publication:\nBuse, H., J. Szabo, B. Morris, and I. Struewing. Chlorine and monochloramine disinfection of Legionella pneumophila colonizing copper and PVC drinking water biofilms.   APPLIED AND ENVIRONMENTAL MICROBIOLOGY. American Society for Microbiology, Washington, DC, USA,  1-33, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:060"
            ],
            "identifier": "https://doi.org/10.23719/1502624",
            "keyword": [
                "drinking water",
                "disinfection",
                "legionella",
                "Copper",
                "PVC",
                "biofilms",
                "Chlorine",
                "monochloramine"
            ],
            "contactPoint": {
                "fn": "Helen Buse",
                "hasEmail": "mailto:buse.helen@epa.gov"
            },
            "distribution": [
                {
                    "title": "Buse_LegionellaBiofilm Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502624/Buse_LegionellaBiofilm%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-09-07",
            "references": [
                "https://doi.org/10.1128/aem.02956-18"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Yaquina Bay Clam Habitat Suitability Index (HSI) Model Output",
            "description": "Using existing habitat datasets and natural-history traits, we created a Habitat Suitability Index (HSI) model in ArcGIS to determine the distribution of suitable habitat for harvested clams in Yaquina Bay.  Existing habitat datasets were used to interpolate value estimates throughout the bay for the four input habitat variables used in the model (sediment % fines, bathymetry, salinity, and burrowing shrimp presence).  Natural history traits (derived from literature) were then used to assign binary suitability values to each habitat variable for each species.  The suitability sum of these variable layers then produced an overall HSI value of 0-4 (low-high).  To validate this model, we used existing bivalve (presence/absence) data to calculate presence probabilities.  Included in this dataset are these bivalve data, along with the habitat estimates and suitability values produced by our model. \n\nThis dataset is associated with the following publication:\nLewis, N., E. Fox, and T. DeWitt. Estimating the distribution of harvested estuarine bivalves with natural-history-based habitat suitability models...   ESTUARINE, COASTAL AND SHELF SCIENCE. Elsevier Science Ltd, New York, NY, USA, 219: 453-472, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1407679",
            "keyword": [
                "harvest",
                "bathymetry",
                "salinity",
                "sediment",
                "shrimp",
                "green macroalgae",
                "ulva spp.",
                "ecosystem services",
                "behavior",
                "burial",
                "eutrophication",
                "nutrient enrichment",
                "cockle",
                "gull",
                "Oregon"
            ],
            "contactPoint": {
                "fn": "Theodore Dewitt",
                "hasEmail": "mailto:dewitt.ted@epa.gov"
            },
            "distribution": [
                {
                    "title": "HSI_YB_BayClams.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407679/HSI_YB_BayClams.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-10-24",
            "references": [
                "https://doi.org/10.1016/j.ecss.2019.02.009"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Tillamook Bay Clam Habitat Suitability Index (HSI) Model Output",
            "description": "Using existing habitat datasets and natural-history traits, we created a Habitat Suitability Index (HSI) model in ArcGIS to determine the distribution of suitable habitat for harvested clams in Tillamook Bay.  Existing habitat datasets were used to interpolate value estimates throughout the bay for the four input habitat variables used in the model (sediment % fines, bathymetry, salinity, and burrowing shrimp presence).  Natural history traits (derived from literature) were then used to assign binary suitability values to each habitat variable for each species.  The suitability sum of these variable layers then produced an overall HSI value of 0-4 (low-high).  To validate this model, we used existing bivalve (presence/absence) data to calculate presence probabilities.  Included in this dataset are these bivalve data, along with the habitat estimates and suitability values produced by our model. \n\nThis dataset is associated with the following publication:\nLewis, N., E. Fox, and T. DeWitt. Estimating the distribution of harvested estuarine bivalves with natural-history-based habitat suitability models...   ESTUARINE, COASTAL AND SHELF SCIENCE. Elsevier Science Ltd, New York, NY, USA, 219: 453-472, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1407680",
            "keyword": [
                "harvest",
                "bathymetry",
                "salinity",
                "sediment",
                "shrimp",
                "green macroalgae",
                "ulva spp.",
                "ecosystem services",
                "behavior",
                "burial",
                "eutrophication",
                "nutrient enrichment",
                "cockle",
                "gull",
                "Oregon"
            ],
            "contactPoint": {
                "fn": "Theodore Dewitt",
                "hasEmail": "mailto:dewitt.ted@epa.gov"
            },
            "distribution": [
                {
                    "title": "HSI_TB_BayClams.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407680/HSI_TB_BayClams.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-10-24",
            "references": [
                "https://doi.org/10.1016/j.ecss.2019.02.009"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Use of carbon isotopic ratios in nontargeted analysis to screen for anthropogenic compounds in complex environmental matrices",
            "description": "Carbon stable isotopic ratios. \n\nThis dataset is associated with the following publication:\nWashington, J., C. Rosal, E. Ulrich, and T. Jenkins. Use of carbon isotopic ratios in nontargeted analysis to screen for anthropogenic compounds in complex environmental matrices.   JOURNAL OF CHROMATOGRAPHY A. Elsevier Science Ltd, New York, NY, USA, 1583: 73-79, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1503074",
            "keyword": [
                "nontargeted analysis",
                "isotopic ratios",
                "anthropogenic compounds",
                "complex environmental samples"
            ],
            "contactPoint": {
                "fn": "John Washington",
                "hasEmail": "mailto:washington.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "170922 New Stable Isotopes.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503074/170922%20New%20Stable%20Isotopes.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-25",
            "references": [
                "https://doi.org/10.1016/j.chroma.2018.11.013"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Raw benthic macroinvertebrate enumeration data for ms concerning methods of taxonomic postprocessing",
            "description": "This file has a listing of benthic macroinvertebrate taxa found in samples collected from coastal waters of Isle Royale and Chequamegon Bay (both in Lake Superior) in 2012 and 2013 respectively, \n\nThis dataset is associated with the following publication:\nMeredith, C., A. Trebitz, and J. Hoffman. Post-processing of aquatic biodiversity data collected at multiple levels of resolution:  Implications for estimates of taxa richness, abundance, and rarefaction curves.   Freshwater Science. The Society for Freshwater Science, Springfield, IL,  98: 137-148, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1394626",
            "keyword": [
                "Great Lakes",
                "Aquatic invasive species",
                "aquatic macroinvertebrates",
                "taxonomy"
            ],
            "contactPoint": {
                "fn": "Anett Trebitz",
                "hasEmail": "mailto:trebitz.anett@epa.gov"
            },
            "distribution": [
                {
                    "title": "AmbiTaxa2017pub_ScienceHub_rawdata.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1394626/AmbiTaxa2017pub_ScienceHub_rawdata.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-09-25",
            "references": [
                "https://doi.org/10.1016/j.ecolind.2018.10.047"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Characterizing grassland fire activity in the Flint Hills region and air quality using satellite and ground based ambient data",
            "description": "Data sets used in the analysis presented in the manuscript \u201cCharacterizing grassland fire activity in the Flint Hills region and air quality using satellite and routine surface monitor data\u201d.  The datasets used for the analysis include data from routine monitor networks located in the central U.S., satellite fire detection data, and burn area estimates. The data supporting each of the Figures in the manuscript are provided in a file specific for that Figure, so there is one file for each Figure. Each file is in comma-separated value (csv) format and contains observation data used to generate that Figure. Meta data on what is included in each file is provided in the Data Dictionary. \n\nThis dataset is associated with the following publication:\nBaker, K., S. Koplitz, K. Foley, L. Avey, and A. Hawkins. Characterizing grassland fire activity in the Flint Hills region and air quality using satellite and routine surface monitor data.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 659: 1555-1566, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1503325",
            "keyword": [
                "emissions",
                "CMAQ",
                "Wildland Fire",
                "biomass burning",
                "air quality modeling"
            ],
            "contactPoint": {
                "fn": "Sergey Napelenok",
                "hasEmail": "mailto:napelenok.sergey@epa.gov"
            },
            "distribution": [
                {
                    "title": "Baker_A-nckf_datasets_Figures1_to_8_v3.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503325/Baker_A-nckf_datasets_Figures1_to_8_v3.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2019-01-30",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.12.427"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1503325/documents/Baker_Data_Dictionary_v3.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Meteorological input data for Cai et al. manuscript \"Development of a Semi-mechanistic allergenic pollen emission model.\"",
            "description": "This dataset consists of output from the Meteorology-Chemistry Input Processor (MCIP), which is used to prepare meteorological data in the format needed for the Community Multiscale Air Quality (CMAQ) model. The Rutgers team has created a module that simulates emissions from two species of pollen using meteorological data in this format. \n\nThis dataset is associated with the following publication:\nCai, T., Y. Zhang, X. Ren, L. Bielory, Z. Mi, C. Nolte, Y. Gao, R. Leung, and P. Georgopoulos. Development of a semi-mechanistic allergenic pollen emission model.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 653: 947-957, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1500009",
            "keyword": [
                "air quality",
                "CMAQ",
                "WRF",
                "model evaluation"
            ],
            "contactPoint": {
                "fn": "Christopher Nolte",
                "hasEmail": "mailto:nolte.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "README.txt",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1500009/README.txt",
                    "mediaType": "text/plain"
                }
            ],
            "modified": "2019-03-05",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2018.10.243"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset for Outdoor air emissions, land use, and land cover around schools on U.S. tribal lands",
            "description": "Data gathered from 35 published references (until 2016) targeting built and natural environment stressors for American Indian/Alaska Native children. \n\nThis dataset is associated with the following publication:\nBarros, N., N. Tulve, K. Bailey, and D. Heggem. Outdoor Air Emissions, Land Use, and Land Cover around Schools on Tribal Lands.   International Journal of Environmental Research and Public Health. Molecular Diversity Preservation International, Basel,  SWITZERLAND, 16(1): 36, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1429612",
            "keyword": [
                "children",
                "school",
                "American Indian/Alaska Native",
                "air pollution",
                "land use",
                "land cover"
            ],
            "contactPoint": {
                "fn": "Nirmalla Barros",
                "hasEmail": "mailto:barros.nilla@epa.gov"
            },
            "distribution": [
                {
                    "title": "EPAAirQualitySystem_TribalSchoolsOutdoorAirPollutantAnnualSummaryMeasures 02282017.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1429612/EPAAirQualitySystem_TribalSchoolsOutdoorAirPollutantAnnualSummaryMeasures%2002282017.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-03-01",
            "references": [
                "https://doi.org/10.3390/ijerph16010036"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/1429612/documents/EPAAirQualitySystem_DataDictionary_AnnualSummaryFiles%2003262018.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Source Strength Functions from Long-Term Monitoring Data and Spatially Distributed Mass Discharge Measurements",
            "description": "Source strength functions (SSF), defined as contaminant mass discharge or flux-averaged concentration from dense nonaqueous phase liquid (DNAPL) source zones as a function of time, provide a quantitative model of DNAPL source-zone behavior.  Such information is useful for making site management decisions.  We investigate the use of historic data collected during long-term monitoring (LTM) activities at a site in Rhode Island to predict the SSF based on temporal mass discharge measurements at a fixed location, as well as SSF estimation using mass discharge measurements at a fixed time from three spatially distributed control planes.  Mass discharge based on LTM data decreased from ~300 g/day in 1996 to ~70 g/day in 2012 at a control plane downgradient of the suspected DNAPL source zone, and indicates an overall decline of ~80% in 16 years.  These measurements were compared to current mass discharge measurements across three spatially distributed control planes.  Results indicate that mass discharge increased in the downgradient direction, and was ~6 g/day, ~37 g/day, and ~400 g/day at near, intermediate, and far distances from the suspected source zone, respectively.  This behavior was expected given the decreasing trend observed in the LTM data at a fixed location.  These two data sets were compared using travel time as a means to plot the data sets on a common axis.  The similarity between the two data sets gives greater confidence to the use of this combined data set for site-specific SSF estimation relative to either the sole use of LTM or spatially distributed data sets. \n\nThis dataset is associated with the following publication:\nBrooks, M.C., A.L. Wood, J. Cho, C.A.P. Williams, B. Brandon, and M.D. Annable. Source strength functions from long-term monitoring data and spatially distributed mass discharge measurements.   JOURNAL OF CONTAMINANT HYDROLOGY. Elsevier Science Ltd, New York, NY, USA, 219: 28-39, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1432673",
            "keyword": [
                "mass flux",
                "mass discharge",
                "source strength function",
                "source zone characterization",
                "passive flux meters",
                "long-term monitoring data"
            ],
            "contactPoint": {
                "fn": "Michael Brooks",
                "hasEmail": "mailto:brooks.michael@epa.gov"
            },
            "distribution": [
                {
                    "title": "SDMF-Brooks-20180330.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1432673/SDMF-Brooks-20180330.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-04-11",
            "references": [
                "https://doi.org/10.1016/j.jconhyd.2018.09.003"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Greenhouse gas emissions from lakes and reservoirs. MS in review.",
            "description": "Reported carbon dioxide, methane, and nitrous emission rates from lakes and reservoirs across the globe. \n\nThis dataset is associated with the following publication:\nDelSontro, T., J. Beaulieu, and J. Downing. Greenhouse gas emissions from lakes and impoundments: upscaling in the face of global change.   Limnology and Oceanography Letters. John Wiley & Sons, Inc., Hoboken, NJ, USA, 3(3): 64-75, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1392351",
            "keyword": [
                "Methane",
                "reservoirs",
                "lakes"
            ],
            "contactPoint": {
                "fn": "Jake Beaulieu",
                "hasEmail": "mailto:beaulieu.jake@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://figshare.com/s/c6a4133f3595b67a9816",
                    "accessURL": "https://figshare.com/s/c6a4133f3595b67a9816"
                }
            ],
            "modified": "2017-09-19",
            "references": [
                "https://doi.org/10.1002/lol2.10073"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data Set Description for Hyperspectral Imagery",
            "description": "The data set description provides a detail account of the type of data that is used within the peer-reviewed literature. The data involves special instrumentation, such as hyperspectral imaging cameras to develop thousands of pixels, which form images, like on a television screen. Other data is used to develop absorbance spectra from infrared spectrometers and compared to reference data to confirm the presence of a desired, tested chemical. \n\nThis dataset is associated with the following publication:\nBaseley, D., L. Wunderlich, G. Phillips, K. Gross, G. Perram, S. Willison, M. Magnuson, S. Lee, R. Phillips, and W. Harper Jr.. Hyperspectral Analysis for Standoff Detection of Dimethyl Methylphosphonate on Building Materials  [HS7.52.01].   JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA,  135-142, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1390104",
            "keyword": [
                "pesticides",
                "hyperspectral imagery",
                "chemical detection",
                "large-area survey"
            ],
            "contactPoint": {
                "fn": "Stuart Willison",
                "hasEmail": "mailto:willison.stuart@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data set description_A-x3g5.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390104/Data%20set%20description_A-x3g5.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2016-02-26",
            "references": [
                "https://doi.org/10.1016/j.buildenv.2016.08.028"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Supplementary material for Lee et al. 2019 Taxonomic harmonization may reveal a stronger association between diatom assemblages and total phosphorus in large datasets  ",
            "description": "Diatom data have been collected in large-scale biological assessments in the United States, such as the U.S. Environmental Protection Agency\u2019s National Rivers and Streams Assessment (NRSA). However, the effectiveness of diatoms as indicators may suffer if inconsistent taxon identifications across different analysts obscure the relationships between assemblage composition and environmental variables. To reduce these inconsistencies, we harmonized the 2008\u20132009 NRSA data from nine analysts by updating names to current synonyms and by statistically identifying taxa with high analyst signal (taxa with more variation in relative abundance explained by the analyst factor, relative to environmental variables). We then screened a subset of samples with QA/QC data and combined taxa with mismatching identifications by the primary and secondary analysts. When these combined \u201cslash groups\u201d did not reduce analyst signal, we elevated taxa to the genus level or omitted taxa in difficult species complexes. We examined the variation explained by analyst in the original and revised datasets. Further, we examined how revising the datasets to reduce analyst signal can reduce inconsistency, thereby uncovering the variation in assemblage composition explained by total phosphorus (TP), an environmental variable of high priority for water managers. To produce a revised dataset with the greatest taxonomic consistency, we ultimately made 124 slash groups, omitted 7 taxa in the small naviculoid (e.g., Sellaphora atomoides) species complex, and elevated Nitzschia, Diploneis, and Tryblionella taxa to the genus level. Relative to the original dataset, the revised dataset had more overlap among samples grouped by analyst in ordination space, less variation explained by the analyst factor, and more than double the variation in assemblage composition explained by TP. Elevating all taxa to the genus level did not eliminate analyst signal completely, and analyst remained the most important predictor for the genera Sellaphora, Mayamaea, and Psammodictyon, indicating that these taxa present the greatest obstacle to consistent identification in this dataset. Although our process did not completely remove analyst signal, this work provides a method to minimize analyst signal and improve detection of diatom association with TP in large datasets involving multiple analysts. Examination of variation in assemblage data explained by analyst and taxonomic harmonization may be necessary steps for improving data quality and the utility of diatoms as indicators of environmental variables. \n\nThis dataset is associated with the following publication:\nLee, S., I. Bishop, S. Spaulding, R. Mitchell, and L. Yuan. Taxonomic harmonization may reveal a stronger association between diatom assemblages and total phosphorus in large datasets..   ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 102: 166-174, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503373",
            "keyword": [
                "taxonomic harmonization",
                "total phosphorus",
                "phosphorus",
                "NRSA",
                "National Rivers and Streams Assessment",
                "nutrients",
                "diatoms",
                "rivers and streams"
            ],
            "contactPoint": {
                "fn": "Sylvia Lee",
                "hasEmail": "mailto:lee.sylvia@epa.gov"
            },
            "distribution": [
                {
                    "title": "Appendix B.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503373/Appendix%20B.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "Data_Dictionaries_TO25_TD01.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503373/Data_Dictionaries_TO25_TD01.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "https://www.sciencedirect.com/science/article/pii/S1470160X19300822#s0095",
                    "accessURL": "https://www.sciencedirect.com/science/article/pii/S1470160X19300822#s0095"
                },
                {
                    "title": "README_v4_508.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503373/README_v4_508.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2019-01-24",
            "references": [
                "https://doi.org/10.1016/j.ecolind.2019.01.061",
                "https://pasteur.epa.gov/uploads/10.23719/1503373/documents/R%20code%20and%20functions.zip"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "EPA Porewater Data in saltwater intrusion freshwater marsh carboon cycling MS",
            "description": "Soil pore water data (N and P chemistry data) from a field experiment examining salt water intrusion effects on freshwater tidal marshes, \n\nThis dataset is associated with the following publication:\nHerbert, E., J. Schubauer-Berigan, and C. Craft. Differential effects of chronic and acute simulated seawater intrusion on tidal freshwater marsh carbon cycling.   BIOGEOCHEMISTRY. Springer, New York, NY, USA, 138: 137-154, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1410808",
            "keyword": [
                "Salt water intrusion",
                "tidal marshes"
            ],
            "contactPoint": {
                "fn": "Joseph SchubauerBerigan",
                "hasEmail": "mailto:schubauer-berigan.joseph@epa.gov"
            },
            "distribution": [
                {
                    "title": "EPA Porewater Data in frehwater marsh carbon cycling MS.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1410808/EPA%20Porewater%20Data%20in%20frehwater%20marsh%20carbon%20cycling%20MS.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-12-04",
            "references": [
                "https://doi.org/10.1007/s10533-018-0436-z"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Datasets used in ORD-023408: A Gene Expression Biomarker Identifies Chemicals and Other Factors That Modulate Sterol Regulatory Element Binding Protein (SREBP) Highlighting Differences in Targeted Regulation of Cholesterogenic and Lipogenic Genes",
            "description": "Datasets used in ORD-023408: A Gene Expression Biomarker Identifies Chemicals and Other Factors That Modulate Sterol Regulatory Element Binding Protein (SREBP) Highlighting Differences in Targeted Regulation of Cholesterogenic and Lipogenic Genes. \n\nThis dataset is associated with the following publication:\nRooney, J., B. Chorley, and C. Corton. A gene expression biomarker identifies factors that modulate sterol regulatory element binding protein.   Computational Toxicology. Elsevier B.V., Amsterdam,  NETHERLANDS, 10: 63-77, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1407625",
            "keyword": [
                "Gene Expression Omnibus Accession Numbers",
                "sterol regulatory element binding protein",
                "microarray",
                "steatosis",
                "fatty liver disease",
                "fatty acid synthesis",
                "cholesterol synthesis"
            ],
            "contactPoint": {
                "fn": "Jon Corton",
                "hasEmail": "mailto:corton.chris@epa.gov"
            },
            "distribution": [
                {
                    "title": "Data submission for A-w3rs.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407625/Data%20submission%20for%20A-w3rs.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-08-01",
            "references": [
                "https://doi.org/10.1016/j.comtox.2018.12.007"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Puerto Rico Soil Science paper",
            "description": "data required to set up SWAT model as well as SWAT model outputs for runoff and sediment. \n\nThis dataset is associated with the following publication:\nYuan, Y., W. Hu, and G. Li. Evaluation of Soil Erosion and Sediment Yield From Ridge Watersheds Leading to Gu\u00e1nica Bay, Puerto Rico, Using the Soil and Water Assessment Tool Model.   Soil Science. Lippincott Williams & Wilkins, Philadelphia, PA, USA, 18(7): 315-325, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1390100",
            "keyword": [
                "DEM",
                "soil",
                "Weather",
                "land use",
                "SWAT",
                "soil erosion",
                "sediment yield",
                "coffee farming",
                "Puerto Rico",
                "ridge watersheds",
                "sustainability"
            ],
            "contactPoint": {
                "fn": "Yongping Yuan",
                "hasEmail": "mailto:yuan.yongping@epa.gov"
            },
            "distribution": [
                {
                    "title": "Soil_Science_Paper_Data.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1390100/Soil_Science_Paper_Data.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2016-05-09",
            "references": [
                "https://doi.org/10.1097/ss.0000000000000166",
                "https://pasteur.epa.gov/uploads/10.23719/1390100/documents/SS-15-184.pdf"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "A Drinking Water Relevant Water Chemistry Model for the Free Chlorine and Cyanuric Acid System from 5 to 35 \u00b0C",
            "description": "No data set is provided. This dataset is not publicly accessible because: All the data is contained in the manuscript and supplementary information. It can be accessed through the following means: All the data is contained in the manuscript and supplementary information. Format: All the data is contained in the manuscript and supplementary information. \n\nThis dataset is associated with the following publication:\nWahman, D., and M. Alexander. A Drinking Water Relevant Water Chemistry Model for the Free Chlorine and Cyanuric Acid System from 5 to 35 \u00b0C.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 36(3): 283-294, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1419831",
            "keyword": [
                "cyanuric acid"
            ],
            "contactPoint": {
                "fn": "David Wahman",
                "hasEmail": "mailto:wahman.david@epa.gov"
            },
            "distribution": [],
            "modified": "2018-02-09",
            "references": [
                "https://doi.org/10.1089/ees.2018.0387"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "DriLube VOC Concentrations, Pressure & Vacuum Readings and Metadata",
            "description": "There are 3 main databases.  #1 is the VOC concentrations of soil gas and indoor air samples collected over the site.  #2 is the pressure readings used to monitor the pressure differential between subslab and indoor air.  #3 is the vacuum reading used to monitor effectiveness, strength, and reach of vacuum created during the SVE operation. \n\nThis dataset is associated with the following publication:\nSchumacher, B., J. Zimmerman, C. Lutes, R. Truesdale, and C.W. Holton. Key Design Elements of Building Pressure Cycling for Evaluating Vapor Intrusion\u2014A Literature Review.   Groundwater Monitoring & Remediation. Wiley-Blackwell Publishing, Hoboken, NJ, USA, 39(1): 66-72, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1502611",
            "keyword": [
                "volatile organic compounds",
                "PCE",
                "TCE",
                "remediation",
                "soil vapor extraction"
            ],
            "contactPoint": {
                "fn": "Brian Schumacher",
                "hasEmail": "mailto:schumacher.brian@epa.gov"
            },
            "distribution": [
                {
                    "title": "SVE-VI_TO-03_VOC-Results_08-31-18.xlsx.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502611/SVE-VI_TO-03_VOC-Results_08-31-18.xlsx.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "SVE-VI_TO-03_Vacuum_Readings_08-31-18.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502611/SVE-VI_TO-03_Vacuum_Readings_08-31-18.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "SVE-VI_Datafiles_08-31-2018.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502611/SVE-VI_Datafiles_08-31-2018.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                },
                {
                    "title": "SVE-VI_TO-03_Pressure_Data_08-31-18.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502611/SVE-VI_TO-03_Pressure_Data_08-31-18.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-08-31",
            "references": [
                "https://doi.org/10.1111/gwmr.12310"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "The dataset is a table showing linear combination fitting results for arsenic and lead in three soils.",
            "description": "Table showing linear combination fitting data for arsenic and lead speciation in three soils. \n\nThis dataset is associated with the following publication:\nKastury, F., E. Smith, R.R. Karna, K.G. Scheckel, and A.L. Juhasz. Methodological factors influencing inhalation bioaccessibility of metal(loid)s in PM2.5 using simulated lung fluid.   ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 241: 930-937, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1435032",
            "keyword": [
                "lead",
                "arsenic",
                "in vitro bioaccessibility",
                "metal bioavailability",
                "synchrotron speciation",
                "PM2.5 long-term exposure",
                "Lung toxicity"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "Table 2 SciHub.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1435032/Table%202%20SciHub.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2018-02-05",
            "references": [
                "https://doi.org/10.1016/j.envpol.2018.05.094"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "LCF datatables for Cd speciation distribution",
            "description": "Linear combination datatables showing the distribution of Cd speciation upon sorption to biochar. \n\nThis dataset is associated with the following publication:\nCuj, L., M. Noerpel, K. Scheckel, and J. Ippolito. Wheat straw biochar reduces environmental cadmium bioavailability.   ENVIRONMENT INTERNATIONAL. Elsevier B.V., Amsterdam,  NETHERLANDS, 126: 69-75, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1503168",
            "keyword": [
                "BCR method",
                "Biochar (BC)",
                "Cadmium",
                "Contaminated paddy soil",
                "X-ray Absorption Spectroscopy",
                "synchrotron speciation"
            ],
            "contactPoint": {
                "fn": "Kirk Scheckel",
                "hasEmail": "mailto:scheckel.kirk@epa.gov"
            },
            "distribution": [
                {
                    "title": "LCF datatables for Cd speciation distribution.docx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503168/LCF%20datatables%20for%20Cd%20speciation%20distribution.docx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
                }
            ],
            "modified": "2018-10-15",
            "references": [
                "https://doi.org/10.1016/j.envint.2019.02.022"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data for organotypic stem cell model for human embryonic palatal fusion.",
            "description": "Cleft palate (CP) is a common birth defect, occurring in an estimated 1 in 1000 births worldwide. The secondary palate is formed by paired palatal shelves that grow toward each other, appose, attach and fuse. CP can result from disruption of any of these processes. The palatal shelves basically consist of a mesenchymal tissue core covered with a layer of epithelial cells. One of the mechanisms that can cause CP is failure of fusion, i.e., failure to remove the epithelial seam between the palatal shelves to allow the mesenchyme to merge and form a continuous palate. This process requires complex interactions between mesenchymal and epithelial cells, and signaling components such as growth factors. Epidermal growth factor (EGF) plays an important role in palate growth and differentiation, while it may impede fusion. We developed a 3D organotypic model using human mesenchymal and epithelial stem cells to mimic human embryonic palatal shelves, and tested its functional relevance by monitoring the effects of human EGF (hEGF) on proliferation and fusion. Spheroids were generated from human umbilical-derived mesenchymal stem cells (hMSCs) directed down an osteogenic lineage by culture medium and evaluated for osteogenic differentiation. Heterotypic spheroids, or organoids, were constructed by coating hMSC spheroids with MaxGel\u2122 extracellular matrix solution followed by a layer of human progenitor epithelial keratinocytes (hPEK). Organoids were incubated in co-culture medium with or without hEGF and assessed for cell proliferation and spheroid pairs were assessed for time to fusion. Osteogenic differentiation in hMSC spheroids was highest by day 13. hEGF delayed fusion of heterotypic organoids after 12 and 18 hours of contact.  hEGF increased proliferation in organoids at 4 ng/ml, and proliferation was detected in hPEKs alone on microcarrier beads, suggesting a potential mechanism for delayed fusion by hEGF. Our results show that this model of human palatal fusion consisting of a core of differentiated hMSCs with a hPEK outer layer appropriately mimics the morphology of the developing human palate and responds to hEGF as expected. Future studies will focus on using the organoid model to evaluate the effects of teratogenic chemicals on palatal fusion, and validating the results. \n\nThis dataset is associated with the following publication:\nWolf, C., D. Belair, C. Becker, K. Das, J. Schmid, and B. Abbott. Development of an organotypic stem cell model for the study of human embryonic palatal fusion.   BIRTH DEFECTS RESEARCH PART B:  DEVELOPMENTAL AND REPRODUCTIVE TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA,  1322-1334, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:000"
            ],
            "identifier": "https://doi.org/10.23719/1432766",
            "keyword": [
                "fusion",
                "stem cells",
                "cleft palate",
                "organotypic models",
                "Morphogenetic fusion",
                "palate fusion",
                "stromal cells",
                "epithelial cells",
                "cell spheroids",
                "osteogenesis"
            ],
            "contactPoint": {
                "fn": "Barbara Abbott",
                "hasEmail": "mailto:abbott.barbara@epa.gov"
            },
            "distribution": [
                {
                    "title": "Wolf et al 2018 Main Text & Suppl Figures Data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1432766/Wolf%20et%20al%202018%20Main%20Text%20%26%20Suppl%20Figures%20Data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-04-13",
            "references": [
                "https://doi.org/10.1002/bdr2.1394"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Dataset for Coarse Particulate Organic Matter Connectivity",
            "description": "Datasets include rain, stream discharge, flow duration in ephemeral tributaries, coarse particulate organic matter (leaves and wood) deposition and surrogate (Ginkgo leaves and dowel rods) export in a Central Appalachian catchment in eastern Kentucky, USA. \n\nThis dataset is associated with the following publication:\nFritz, K., G. Pond, B. Johnson, and C. Barton. Coarse particulate organic matter dynamics in ephemeral tributaries of a Central Appalachian stream network.   Ecosphere. ESA Journals,    10(3): e02654, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/10002",
            "keyword": [
                "ephemeral tributary",
                "connectivity",
                "leaf litter",
                "Wood",
                "transport",
                "storage",
                "deposition",
                "seasonality",
                "lag function"
            ],
            "contactPoint": {
                "fn": "Ken Fritz",
                "hasEmail": "mailto:fritz.ken@epa.gov"
            },
            "distribution": [
                {
                    "title": "CPOM_deposition.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/10002/CPOM_deposition.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "historic_rain.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/10002/historic_rain.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "CPOM_export.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/10002/CPOM_export.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "flowduration.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/10002/flowduration.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "networkleaf_deposited.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/10002/networkleaf_deposited.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "networkleaf_export.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/10002/networkleaf_export.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "dailyrain_ephemeralstate.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/10002/dailyrain_ephemeralstate.csv",
                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "dailyrain_discharge.csv",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/10002/dailyrain_discharge.csv",
                    "mediaType": "application/vnd.ms-excel"
                }
            ],
            "modified": "2018-12-04",
            "references": [
                "https://doi.org/10.1002/ecs2.2654",
                "https://pasteur.epa.gov/uploads/10.23719/10002/documents/ecs22654-sup-0001-appendixs1.pdf",
                "https://pasteur.epa.gov/uploads/10.23719/10002/documents/Fritz_et_al-2019-Ecosphere.pdf"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "describedBy": "https://pasteur.epa.gov/uploads/10.23719/10002/documents/EphemeralTributary_datadictionary.docx",
            "describedByType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "README_nysdoh",
            "description": "The \"dataset\" is simply a README file that contains information about the data that EPA provided to the lead authors and where to acquire the data on the EPA high-performance computing system archive.  Those data exceed 1 gigabyte in size, so they are too large to be hosted on ScienceHub. \n\nThis dataset is associated with the following publication:\nZhang, W., T. Spero, C. Nolte, V. Garcia, Z. Lin, P. Romitti, G. Shaw, S. Sheridan, M. Feldkamp, A. Woomert, S. Hwang, S. Fisher, M. Browne, Y. Hao, and S. Lin. Projected Changes in Maternal Heat Exposure During Early Pregnancy and the Associated Congenital Heart Defect Burden in the United States.   Journal of the American Heart Association (JAHA). American Heart Association, Dallas, TX, USA, 8(3): e010995, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1503525",
            "keyword": [
                "WRF",
                "regional climate modeling",
                "health burden"
            ],
            "contactPoint": {
                "fn": "Tanya Spero",
                "hasEmail": "mailto:spero.tanya@epa.gov"
            },
            "distribution": [
                {
                    "title": "nysdoh.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503525/nysdoh.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2018-05-18",
            "references": [
                "https://doi.org/10.1161/jaha.118.010995"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Market Sensitivity of Solar-Fossil Hybrid Electricity Generation to Price, Efficiency, Policy, and Fuel Projections",
            "description": "This dataset includes results from the MARKAL model. A technology that generates electricity from a combination of solar and natural gas energy, called ISCC, is evaluated. Results include electricity generation mixes and emissions projections. \n\nThis dataset is associated with the following publication:\nBrown, K., and D. Loughlin. Market Sensitivity of Solar-Fossil Hybrid Electricity Generation to Price, Efficiency, Policy, and Fuel Projections.   CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY. Springer-Verlag, New York, NY, USA, 21(3): 591-604, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1502569",
            "keyword": [
                "energy",
                "externality",
                "energy modeling"
            ],
            "contactPoint": {
                "fn": "Kristen Brown",
                "hasEmail": "mailto:brown.kristen@epa.gov"
            },
            "distribution": [
                {
                    "title": "Hybrid_PubData.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502569/Hybrid_PubData.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-09-05",
            "references": [
                "https://doi.org/10.1007/s10098-018-1659-3"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Cardiopulmonary hospitalizations and air quality in counties affected by wildfires, 2008-2010",
            "description": "The final dataset combines cardiopulmonary hospitalization data for those 65 and over using the Medicare Provider Analysis and Review (MEDPAR) files from the Center for Medicare and Medicaid Services (CMS), modeled fine particulate matter (PM2.5) concentrations from the Community Multiscale Air Quality (CMAQ) model, and monitoring site concentrations of PM2.5 from the Air Quality System (AQS). All data are aggregated to the county level and restricted to counties with wildfires recorded between 2008-2010. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Due to the presence of PII, limited data are available on request. Format: The data are stored as an R dataset (.RData) on a restricted drive. \n\nThis dataset is associated with the following publication:\nDeflorio-Barker, S., J. Crooks, J. Reyes, and A.G. Rappold. Cardiopulmonary effects of fine particulate matter exposure among older adults, during wildfire and non-wildfire periods, in U.S. 2008-2010.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 127(3): 37006, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1435439",
            "keyword": [
                "wildfire",
                "cardiopulmonary",
                "hospitalizations",
                "Medicare"
            ],
            "contactPoint": {
                "fn": "Stephanie Deflorio-Barker",
                "hasEmail": "mailto:deflorio-barker.stephanie@epa.gov"
            },
            "distribution": [],
            "modified": "2017-10-02",
            "references": [
                "https://doi.org/10.1289/ehp3860"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Measurement of kinetic parameters for biotransformation of PAHs by trout liver S9 fractions: Implications for bioaccumulation assessment",
            "description": "The dataset, which is presented as an Excel spreadsheet, contains all data which is presented as figures in Nichols et al., Measurement of kinetic parameters for biotransformation of polycyclic aromatic hydrocarbons by trout liver S9 fractions: Implications for bioaccumulation assessment, accepted for publication in Applied In Vitro Toxicology 04/2017.  Additional information if provided regarding reaction conditions used to characterize liver S9 fractions and perform PAH depletions studies. \n\nThis dataset is associated with the following publication:\nNichols, J., M. Ladd, and P. Fitzsimmons. Measurement of kinetic parameters for biotransformation of polycyclic aromatic hydrocarbons by trout liver S9 fractions: Implications for bioaccumulation assessment.   Applied In Vitro Toxicology. Mary Ann Liebert, Inc., Larchmont, NY, USA, 4(4): 365-378, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1374699",
            "keyword": [
                "rainbow trout",
                "fish",
                "biotransformation",
                "in vitro-in vivo extrapolation",
                "bioaccumulation assessment",
                "liver S9 fraction"
            ],
            "contactPoint": {
                "fn": "John Nichols",
                "hasEmail": "mailto:nichols.john@epa.gov"
            },
            "distribution": [
                {
                    "title": "S9 paper; Science Hub data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1374699/S9%20paper%3B%20Science%20Hub%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-04-18",
            "references": [
                "https://doi.org/10.1089/aivt.2017.0005"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Bioaccumulation of highly hydrophobic chemicals by Lumbriculus variegatus",
            "description": "Sediment was dosed with six highly hydrophobic chemicals with estimated log Kows ranging up to 18.3.  Sediment bioaccumulation tests with Lumbriculus variegatus were performed with the dosed sediment.  The attached dataset contains the concentrations in the organisms from the uptake and elimination portions of the test. and supporting data, e.g. lipid contents and weight change for the organisms. \n\nThis dataset is associated with the following publication:\nBurkhard, L., T. Lahren, T. Highland, R. Hockett, D. Mount, and T. Norberg-King. Bioaccumulation of highly hydrophobic chemicals by Lumbriculus variegatus.   ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY. Springer, New York, NY, USA, 76(1): 129-141, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:097"
            ],
            "identifier": "https://doi.org/10.23719/1395343",
            "keyword": [
                "oligochaete",
                "Lumbriculus variegatus",
                "bioaccumulation",
                "sediment testing",
                "sediment",
                "chemical uptake",
                "bioavailability",
                "fish dietary studies"
            ],
            "contactPoint": {
                "fn": "Lawrence Burkhard",
                "hasEmail": "mailto:burkhard.lawrence@epa.gov"
            },
            "distribution": [
                {
                    "title": "Supplementary Materials-Merged-ALL.pdf",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1395343/Supplementary%20Materials-Merged-ALL.pdf",
                    "mediaType": "application/pdf"
                }
            ],
            "modified": "2017-09-25",
            "references": [
                "https://doi.org/10.1007/s00244-018-0554-6"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Gene transcription ontogeny of hypothalamic-pituitary-thyroid axis development in early-life stage fathead minnow and zebrafish",
            "description": "Disruption of thyroid hormone signaling is a form of endocrine disruption that is of concern to both human health and ecosystems. Research is being conducted to define the biological targets chemicals may interact with to disrupt thyroid hormone signaling and the stages in development where that disruption can most readily lead to adverse effects. The present data characterize the expression of key genes associated with thyroid hormone signaling and regulation over the course of development for two small fish widely used in aquatic ecotoxicology research. These data provide baseline information that can lead to a more complete understanding of which thyroid disrupting chemicals fish may be susceptible to and at which stages in development. \n\nThis dataset is associated with the following publication:\nVergauwen, L., J. Cavallin, G. Ankley, C. Bars, I. Gabriels, E. Michiels, K. Nelson, J.  Periz-Stanacev, E. Randolph, S. Robinson, T. Saari, A. Schroeder, E. Stinckens, J. Swintek, S. Van Cruchten, E.  Verbueken, D. Villeneuve, and D. Knapen. Gene transcription ontogeny of thyroid-axis development in early-life stage fathead minnow and zebrafish.   Journal of Experimental Biology. The Company of Biologists LIMITED, Cambridge,  UK, 266: 878-1002, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1429982",
            "keyword": [
                "development",
                "adverse outcome pathway",
                "ecotoxicology",
                "endocrine disruption",
                "screening and prioritization",
                "aquatic ecosystems"
            ],
            "contactPoint": {
                "fn": "Daniel Villeneuve",
                "hasEmail": "mailto:villeneuve.dan@epa.gov"
            },
            "distribution": [
                {
                    "title": "Thyroid ontogeny_All data_Science Hub_FINAL.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1429982/Thyroid%20ontogeny_All%20data_Science%20Hub_FINAL.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-03-27",
            "references": [
                "https://doi.org/10.1016/j.ygcen.2018.05.001"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "CMAPS Dataset Coarse PM exacerbates allergic airway responses in mice.",
            "description": "The dataset contains the original data relevant for each figure or table in the cleared publication. The excel file has tabs labelled for each figure (Figures 1-4) or table (tables 1-3). Figure 5 in the paper shows representative histology figures, and so is not linked to data other than as representative of table 3 (histology). Table 1 has 3 tabs for PM collection at the CLM site, PM collection at the GTC site, and for chemistry. Table 2 is represented on 1 tab for biochemistry. Table 3 has 2 tabs for the raw histopathology data for the statistics and summary. \n\nThis dataset is associated with the following publication:\nHargrove, M.M., J. Mcgee, E. Gibbs-Flournoy, C. Wood, Y.H. Kim, I. Gilmour, and S. Gavett. Source-Apportioned Coarse Particulate Matter Exacerbates Allergic Airway Responses in Mice.   INHALATION TOXICOLOGY. Informa Healthcare USA, New York, NY, USA, 30(11): 405-415, (2018).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:094"
            ],
            "identifier": "https://doi.org/10.23719/1502509",
            "keyword": [
                "particulate matter",
                "allergy",
                "emission sources"
            ],
            "contactPoint": {
                "fn": "Stephen Gavett",
                "hasEmail": "mailto:gavett.stephen@epa.gov"
            },
            "distribution": [
                {
                    "title": "CMAPS data-ScienceHub2.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502509/CMAPS%20data-ScienceHub2.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-09-01",
            "references": [
                "https://doi.org/10.1080/08958378.2018.1542047"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Metropolitan DWDS Sequence Data Set",
            "description": "PS_GenBank.fasta file contain the sequences of the bacterial 16S rRNA-encoding gene for each representative sequence.  The sequence containing four hypervariable regions was amplified using the primer set Eub-8f and 787.\n\nPS_GenBank.xlsx file contains rows as sample and columns as entries representing the accession number (NCBI) deposited in GenBank for each representative sequence (i.e. unique sequences).\n\nPS_OTU.fasta file contain the sequences of the bacterial 16S rRNA-encoding gene for each Operational Taxonomic Unit (OTU). The sequence containing four hypervariable regions was amplified using the primer set Eub-8f and 787. \n\nThis dataset is associated with the following publication:\nRevetta , R., V. Gomez-Alvarez, T. Gerke, J. Santodomingo , and N. Ashbolt. CHANGES IN BACTERIAL COMPOSITION OF BIOFILM IN A METROPOLITAN DRINKING WATER DISTRIBUTION SYSTEM.   JOURNAL OF APPLIED MICROBIOLOGY. Blackwell Publishing, Malden, MA, USA, 121(1): 294-305, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503383",
            "keyword": [
                "microbial communities",
                "16S rRNA",
                "OTU",
                "drinking water",
                "Biofilm",
                "Microbial Structure",
                "groundwater",
                "surface water",
                "Drinking water distribution system"
            ],
            "contactPoint": {
                "fn": "Vicente Gomez-Alvarez",
                "hasEmail": "mailto:gomez-alvarez.vicente@epa.gov"
            },
            "distribution": [
                {
                    "title": "PS_GenBank.fasta.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503383/PS_GenBank.fasta.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "PS_GenBank.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503383/PS_GenBank.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "PS_OTU.fasta.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503383/PS_OTU.fasta.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2014-10-06",
            "references": [
                "https://doi.org/10.1111/jam.13150"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Metropolitan DWDS Taxonomic Lineage Abundance Data Set",
            "description": "An abundance matrix (PS_taxonomic_lineage.xlsx) contains rows as taxonomic lineage, columns as samples, and entries representing the abundance of each lineage as a ratio of all sequences obtained for each individual sample. \n\nThis dataset is associated with the following publication:\nRevetta , R., V. Gomez-Alvarez, T. Gerke, J. Santodomingo , and N. Ashbolt. CHANGES IN BACTERIAL COMPOSITION OF BIOFILM IN A METROPOLITAN DRINKING WATER DISTRIBUTION SYSTEM.   JOURNAL OF APPLIED MICROBIOLOGY. Blackwell Publishing, Malden, MA, USA, 121(1): 294-305, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503385",
            "keyword": [
                "taxonomy",
                "relative abundance",
                "drinking water",
                "Biofilm",
                "Microbial Structure",
                "groundwater",
                "surface water",
                "Drinking water distribution system"
            ],
            "contactPoint": {
                "fn": "Vicente Gomez-Alvarez",
                "hasEmail": "mailto:gomez-alvarez.vicente@epa.gov"
            },
            "distribution": [
                {
                    "title": "PS_taxonomic_lineage.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503385/PS_taxonomic_lineage.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-10-06",
            "references": [
                "https://doi.org/10.1111/jam.13150"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Resilience of Microbial Communities OTU Abundance Data Set",
            "description": "An abundance matrix (EX_OTU.xlsx) contains rows as OTU, columns as samples, and entries representing the abundance of each OTU as a ratio of all sequences obtained for each individual sample. \n\nThis dataset is associated with the following publication:\nGomez-Alvarez, V., S. Pfaller, J. Pressman, D. Wahman, and R. Revetta. Resilience of microbial communities in a simulated drinking water distribution system subjected to disturbances: role of conditionally rare taxa and potential implications for antibiotic-resistant bacteria.   Environmental Science: Water Research & Technology. Royal Society of Chemistry, Cambridge,  UK, 2: 645-657, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503391",
            "keyword": [
                "OTU",
                "relative abundance",
                "microbial communities",
                "drinking water",
                "Biofilm",
                "Antibiotic Resistance Genes",
                "nitrification"
            ],
            "contactPoint": {
                "fn": "Vicente Gomez-Alvarez",
                "hasEmail": "mailto:gomez-alvarez.vicente@epa.gov"
            },
            "distribution": [
                {
                    "title": "EX_OTU.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503391/EX_OTU.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-09-22",
            "references": [
                "https://doi.org/10.1039/c6ew00053c"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Life cycle inventory data of various unit processes in water and wastewater treatment trains and the life cycle impact assessments of different environmental performance categories.",
            "description": "LCI and LCIA for water and wastewater treatment plants. \n\nThis dataset is associated with the following publications:\nXue, X., S. Cashman, A. Gaglione, J. Mosley, L. Weiss, C. Ma, J. Cashdollar, and J. Garland. Holistic Analysis of Urban Water Systems in the Greater Cincinnati Region: (1) Life Cycle Assessment and Cost Implications.   Water Research X. Elsevier B.V., Amsterdam,  NETHERLANDS, 2: 100015, (2019).\nCashman, S., A. Gaglione, J. Mosley, L. Weiss, T. Hawkins, N. Ashbolt, J. Cashdollar , X. Xue, C. Ma , and S. Arden. Environmental and cost life cycle assessment of disinfection options for municipal drinking water treatment. U.S. Environmental Protection Agency, Washington, DC, USA, 2014.\nCashman, S., A. Gaglione, J. Mosley, L. Weiss, N. Ashbolt, T. Hawkins, J. Cashdollar , X. Xue, C. Ma , and S. Arden. Environmental and cost life cycle assessment of disinfection options for municipal wastewater treatment. U.S. Environmental Protection Agency, Washington, DC, USA, 2014.",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1407684",
            "keyword": [
                "LCA",
                "Impact assessment",
                "system analysis",
                "LCC",
                "energy expenditure and distribution",
                "Water Systems",
                "sustainability analysis",
                "Drinking water systems",
                "wastewater systems",
                "Life cycle assessment (LCA)",
                "life cycle costing",
                "life cycle impact assessment method"
            ],
            "contactPoint": {
                "fn": "Xin Ma",
                "hasEmail": "mailto:ma.cissy@epa.gov"
            },
            "distribution": [
                {
                    "title": "graphs for manuscript.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407684/graphs%20for%20manuscript.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "DWT Cost Calculations_Final_2014 09 25.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407684/DWT%20Cost%20Calculations_Final_2014%2009%2025.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "DWT_LCAResults_DraftFinal.UpdatedNG(3.31.15)(10.15.15).xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407684/DWT_LCAResults_DraftFinal.UpdatedNG%283.31.15%29%2810.15.15%29.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "WWT BaseCaseCosts.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407684/WWT%20BaseCaseCosts.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                },
                {
                    "title": "WWT LCAresults .xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1407684/WWT%20LCAresults%20.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2017-10-25",
            "references": [
                "https://doi.org/10.1016/j.wroa.2018.100015"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Edison Big Parking Lot Nutrient data.",
            "description": "The data includes nutrient concentrations for infiltrates, runoff, and rainfall during the monitoring period. \n\nThis dataset is associated with the following publication:\nRazzaghmanesh, M., and M. Borst. Long- term effects of three types of permeable pavements on nutrient infiltrate concentrations.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 670: 893-901, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1502577",
            "keyword": [
                "Permeable pavement parking lot",
                "nutrients",
                "nitrification",
                "Trend analysis",
                "stormwater runoff"
            ],
            "contactPoint": {
                "fn": "Michael Borst",
                "hasEmail": "mailto:borst.mike@epa.gov"
            },
            "distribution": [
                {
                    "title": "Edison Big Parking Lot Nutrient data.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502577/Edison%20Big%20Parking%20Lot%20Nutrient%20data.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2019-03-26",
            "references": [
                "https://doi.org/10.1016/j.scitotenv.2019.03.279"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Resilience of Microbial Communities Taxonomic Lineage Abundance Data Set",
            "description": "An abundance matrix (EX_taxonomic_lineage.xlsx) contains rows as taxonomic lineage, columns as samples, and entries representing the abundance of each lineage as a ratio of all sequences obtained for each individual sample. \n\nThis dataset is associated with the following publication:\nGomez-Alvarez, V., S. Pfaller, J. Pressman, D. Wahman, and R. Revetta. Resilience of microbial communities in a simulated drinking water distribution system subjected to disturbances: role of conditionally rare taxa and potential implications for antibiotic-resistant bacteria.   Environmental Science: Water Research & Technology. Royal Society of Chemistry, Cambridge,  UK, 2: 645-657, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503392",
            "keyword": [
                "taxonomy",
                "relative abundance",
                "microbial communities",
                "drinking water",
                "Biofilm",
                "Antibiotic Resistance Genes",
                "nitrification"
            ],
            "contactPoint": {
                "fn": "Vicente Gomez-Alvarez",
                "hasEmail": "mailto:gomez-alvarez.vicente@epa.gov"
            },
            "distribution": [
                {
                    "title": "EX_taxonomic_lineage.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503392/EX_taxonomic_lineage.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2015-09-22",
            "references": [
                "https://doi.org/10.1039/c6ew00053c"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Metropolitan DWDS OTU Abundance Data Set",
            "description": "An abundance matrix (PS_OTU.xlsx) contains rows as OTU, columns as samples, and entries representing the abundance of each OTU as a ratio of all sequences obtained for each individual sample. \n\nThis dataset is associated with the following publication:\nRevetta , R., V. Gomez-Alvarez, T. Gerke, J. Santodomingo , and N. Ashbolt. CHANGES IN BACTERIAL COMPOSITION OF BIOFILM IN A METROPOLITAN DRINKING WATER DISTRIBUTION SYSTEM.   JOURNAL OF APPLIED MICROBIOLOGY. Blackwell Publishing, Malden, MA, USA, 121(1): 294-305, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503384",
            "keyword": [
                "OTU",
                "relative abundance",
                "drinking water",
                "Biofilm",
                "Microbial Structure",
                "groundwater",
                "surface water",
                "Drinking water distribution system"
            ],
            "contactPoint": {
                "fn": "Vicente Gomez-Alvarez",
                "hasEmail": "mailto:gomez-alvarez.vicente@epa.gov"
            },
            "distribution": [
                {
                    "title": "PS_OTU.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503384/PS_OTU.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2014-10-06",
            "references": [
                "https://doi.org/10.1111/jam.13150"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": " Resilience of Microbial Communities Sequence Data Set",
            "description": "The EX_Genome_Assemblies.zip file contain the contig sequences (i.e. assembly) of fifteen isolates used for genomic and antibiotic resistance genes (ARG) analysis.\n\nEX_OTU.fasta file contain the sequences of the bacterial 16S rRNA-encoding V4 region gene (\u2248250 nt) for each Operational Taxonomic Unit (OTU). \n\nThis dataset is associated with the following publication:\nGomez-Alvarez, V., S. Pfaller, J. Pressman, D. Wahman, and R. Revetta. Resilience of microbial communities in a simulated drinking water distribution system subjected to disturbances: role of conditionally rare taxa and potential implications for antibiotic-resistant bacteria.   Environmental Science: Water Research & Technology. Royal Society of Chemistry, Cambridge,  UK, 2: 645-657, (2016).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:096"
            ],
            "identifier": "https://doi.org/10.23719/1503390",
            "keyword": [
                "microbial communities",
                "16S rRNA",
                "OTU",
                "Genomes",
                "drinking water",
                "Biofilm",
                "Antibiotic Resistance Genes",
                "nitrification"
            ],
            "contactPoint": {
                "fn": "Vicente Gomez-Alvarez",
                "hasEmail": "mailto:gomez-alvarez.vicente@epa.gov"
            },
            "distribution": [
                {
                    "title": "https://trace.ncbi.nlm.nih.gov/Traces/sra/?study=SRP069876",
                    "accessURL": "https://trace.ncbi.nlm.nih.gov/Traces/sra/?study=SRP069876"
                },
                {
                    "title": "EX_Genome_Assemblies.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503390/EX_Genome_Assemblies.zip",
                    "mediaType": "application/x-zip-compressed"
                },
                {
                    "title": "EX_OTU.fasta.zip",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1503390/EX_OTU.fasta.zip",
                    "mediaType": "application/x-zip-compressed"
                }
            ],
            "modified": "2015-09-22",
            "references": [
                "https://doi.org/10.1039/c6ew00053c"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Phenone rtER binding Vtg_Tapper_A-jm6n_data set 20171002",
            "description": "Phenones and hydroxy benzophenones are widely used as UV radiation filters, and in the manufacturing of insecticides and pharmaceuticals. Understanding the ability of these chemicals to mimic the effects of the steroid estrogen is of interest to the US Environmental Protection Agency and other international environmental organizations. The current study sequentially combined complementary in vitro (outside a living organism) rainbow trout estrogen receptor (rtER) binding and liver slice vitellogenin (Vtg) mRNA induction assays in the context of a defined ER-mediated adverse outcome pathway (AOP). Cyclic phenones, branched phenones, and hydroxybenzophenones bound to rtER with relative potency ranging from no affinity to high binding affinity of 0.11%, and many induced Vtg, an egg yolk protein, gene expression in rt liver slices. In addition, cyclohexylphenylketone which did not bind rtER binding in cytosol was biotransformed within liver tissue to a chemical that induced Vtg expression. Cyclic phenones, branched phenones and hydroxybenzophenones produced estrogen like responses in these rainbow trout in vitro assays. \n\nThis dataset is associated with the following publication:\nTapper, M., J. Denny, J. Serrano, R. Kolanczyk, B. Sheedy, G. Overland, M. Hornung, and P. Schmieder. Phenone, hydroxybenzophenone, and branched phenone estrogen receptor binding and vitellogenin agonism in rainbow trout in vitro models.   Applied In Vitro Toxicology. Mary Ann Liebert, Inc., Larchmont, NY, USA, 5(1): 62-74, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
                "020:095"
            ],
            "identifier": "https://doi.org/10.23719/1424400",
            "keyword": [
                "In vitro assay",
                "estrogen receptor",
                "vitellogenin gene expression",
                "endocrine disruption",
                "AOP"
            ],
            "contactPoint": {
                "fn": "Mark Tapper",
                "hasEmail": "mailto:tapper.mark@epa.gov"
            },
            "distribution": [
                {
                    "title": "Phenone rtER binding Vtg_Tapper_A-jm6n_data set 201810613.xlsx",
                    "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1424400/Phenone%20rtER%20binding%20Vtg_Tapper_A-jm6n_data%20set%20201810613.xlsx",
                    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                }
            ],
            "modified": "2018-03-07",
            "references": [
                "https://doi.org/10.1089/aivt.2018.0008"
            ],
            "publisher": {
                "name": "U.S. EPA Office of Research and Development (ORD)",
                "subOrganizationOf": {
                    "name": "U.S. Environmental Protection Agency",
                    "subOrganizationOf": {
                        "name": "U.S. Government"
                    }
                }
            },
            "geo": "No",
            "holdren": "Yes",
            "ORG": "ORD",
            "sourcetitle": "ScienceHub",
            "sourcefile": "https://pasteur.epa.gov/metadata.json"
        },
        {
            "title": "Data File 1: Metabolism of cyclic phenones in rainbow trout in vitro assays ",
            "description": "Files contain summary reports of chemical and Mass Spectrometry raw and analyzed data  used as basis for plot generation and text discussions in the Cyclic phenone metabolism  manuscript. File dataset includes a Definition Xcel file listing the supporting files in set. Specifically, the dataset  includes individual chemical  slice exposure Xcel data summaries for the model cyclic phenones  DPK, CBP and CPK as well as well as hepatocyte cytosol exposure data to the same chemicals. Each  file contains data organized in labelled tabs that includes General Experimental information, Quantitative and qualitative methods used to process/analyze the raw data for parent and chemical metabolites, chemical mass balances and conclusions. Power point files with the summarized data were presented in the manuscript's Supplemental data. \n\nThis dataset is associated with the following publication:\nSerrano, J., M. Tapper, R. Kolanczyk, B. Sheedy, T. Lahren, D. Hammermeister, J. Denny, M. Hornung, A. Kubatova, P. Kosian, J. Voelker, and P. Schmieder. Metabolism of cyclic phenones in rainbow trout in vitro assays.   XENOBIOTICA. Taylor & Francis, Inc., Philadelphia, PA, USA, 50(2): 115-131, (2019).",
            "accessLevel": "public",
            "rights": null,
            "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
            "bureauCode": [
                "020:00"
            ],
            "programCode": [
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            "identifier": "https://doi.org/10.23719/1502613",
            "keyword": [
                "cyclic phenones",
                "in vitro assays",
                "endocrine disruption",
                "fish liver slices",
                "estrogen receptor",
                "Vtg gene expression",
                "Metabolism",
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                "LC-MS/MS",
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            ],
            "contactPoint": {
                "fn": "Jose Serrano",
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                    "mediaType": "application/vnd.ms-excel"
                },
                {
                    "title": "CBP slice full study HUB File.xlsx",
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                },
                {
                    "title": "CBP DPK CPK cytosol HUB File.xlsx",
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            "references": [
                "https://doi.org/10.1080/00498254.2019.1596331"
            ],
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                "name": "U.S. EPA Office of Research and Development (ORD)",
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        {
            "title": "Arsenic speciation results",
            "description": "The dataset is a table that shows soil samples with corresponding total arsenic concentrations, arsenic bioavailability values, and linear combination fitting results of synchrotron speciation results. \n\nThis dataset is associated with the following publication:\nStevens, B.N., A.R. Betts, B.W. Miller, K.G. Scheckel, R.H. Anderson, K.D. Bradham, S.W. Casteel, D.J. Thomas, and N.T. Basta. Arsenic Speciation of Contaminated Soils/Solid Wastes and Relative Oral Bioavailability in Swine and Mice.   Soil Systems. MDPI AG, Basel,  SWITZERLAND, 2(2): 27, (2018).",
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