{
  "accessLevel": "public",
  "bureauCode": [
    "020:00"
  ],
  "contactPoint": {
    "fn": "Sudhakar Takkellapati",
    "hasEmail": "mailto:takkellapati.sudhakar@epa.gov"
  },
  "description": "The emission data used is based on this publication. \n\nThis dataset is associated with the following publication:\nTakkellapati, S., and M.A. Gonzalez. Application of read-across methods as a framework for the estimation of emissions from chemical processes.   Clean Technologies and Recycling. AIMS Press, Springfield, MO, USA, 3(4): 283-300, (2023).",
  "distribution": [
    {
      "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1529986/Meyer_ImprovingReliabilityOfChemicalManufactLCI_2020.pdf",
      "mediaType": "application/pdf",
      "title": "Meyer_ImprovingReliabilityOfChemicalManufactLCI_2020.pdf"
    }
  ],
  "identifier": "https://doi.org/10.23719/1529986",
  "keyword": [
    "Environmental Releases",
    "Read-across",
    "climate change",
    "emissions",
    "machine learning"
  ],
  "license": "https://pasteur.epa.gov/license/sciencehub-license.html",
  "modified": "2024-01-11",
  "programCode": [
    "020:000"
  ],
  "publisher": {
    "name": "U.S. EPA Office of Research and Development (ORD)",
    "subOrganizationOf": {
      "name": "U.S. Environmental Protection Agency",
      "subOrganizationOf": {
        "name": "U.S. Government"
      }
    }
  },
  "references": [
    "https://doi.org/10.3934/ctr.2023018"
  ],
  "rights": null,
  "title": "Read-across application for emissions estimation"
}