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An Ensemble Learning Approach for Estimating High Spatiotemporal Resolution of Ground-Level Ozone in the Contiguous United States.
Requia, Weeberb J; Di, Qian; Silvern, Rachel; Kelly, James T; Koutrakis, Petros; Mickley, Loretta J; Sulprizio, Melissa P; Amini, Heresh; Shi, Liuhua; Schwartz, Joel.
Afiliação
  • Requia WJ; Department of Environmental Health, Harvard University, TH Chan School of Public Health, Boston, Massachusetts 02115, United States.
  • Di Q; School of Public Policy and Government, Fundação Getúlio Vargas, Brasília, Distrito Federal 72125590, Brazil.
  • Silvern R; Department of Environmental Health, Harvard University, TH Chan School of Public Health, Boston, Massachusetts 02115, United States.
  • Kelly JT; Research Center for Public Health, Tsinghua University, Beijing 100084, China.
  • Koutrakis P; Harvard University, John A. Paulson School of Engineering and Applied Sciences, Cambridge, Massachusetts 02138, United States.
  • Mickley LJ; U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, Durham, North Carolina 27709, United States.
  • Sulprizio MP; Department of Environmental Health, Harvard University, TH Chan School of Public Health, Boston, Massachusetts 02115, United States.
  • Amini H; Harvard University, John A. Paulson School of Engineering and Applied Sciences, Cambridge, Massachusetts 02138, United States.
  • Shi L; Harvard University, John A. Paulson School of Engineering and Applied Sciences, Cambridge, Massachusetts 02138, United States.
  • Schwartz J; Department of Environmental Health, Harvard University, TH Chan School of Public Health, Boston, Massachusetts 02115, United States.
Environ Sci Technol ; 54(18): 11037-11047, 2020 09 15.
Article em En | MEDLINE | ID: mdl-32808786
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ozônio / Poluentes Atmosféricos / Poluição do Ar Tipo de estudo: Prognostic_studies País/Região como assunto: America do norte Idioma: En Revista: Environ Sci Technol Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ozônio / Poluentes Atmosféricos / Poluição do Ar Tipo de estudo: Prognostic_studies País/Região como assunto: America do norte Idioma: En Revista: Environ Sci Technol Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos