{"accessLevel": "public", "bureauCode": ["020:00"], "contactPoint": {"fn": "James Kelly", "hasEmail": "mailto:kelly.james@epa.gov"}, "description": "Air quality modeling for China. This dataset is not publicly accessible because: Data was generated and owned by Tsinghua University. It can be accessed through the following means: Data can be accessed from lead author at Tsinghua University: xingjia@tsinghua.edu.cn. Format: Air quality modeling data for China. Citation information for this dataset can be found in the EDG's Metadata Reference Information section and Data.gov's References section.", "distribution": [], "identifier": "https://doi.org/10.23719/1524265", "keyword": ["Atmospheric photochemistry", "Chemical transport model", "Deep learning", "Meteorology", "Ozone", "emissions"], "license": "https://pasteur.epa.gov/license/sciencehub-license-non-epa-generated.html", "modified": "2021-11-13", "programCode": ["020:000"], "publisher": {"name": "U.S. Environmental Protection Agency", "subOrganizationOf": {"name": "U.S. Government"}}, "references": ["https://dx.doi.org/10.1016/j.atmosres.2021.105919"], "rights": null, "title": "Mimicking atmospheric photochemical modeling with a deep neural network"}