An Ensemble Learning Approach for Estimating High Spatiotemporal Resolution of Ground-Level Ozone in the Contiguous United States-Reference-Cited by-同舟云学术

An Ensemble Learning Approach for Estimating High Spatiotemporal Resolution of Ground-Level Ozone in the Contiguous United States

Published:2020-08-18 Issue:18 Volume:54 Page:11037-11047
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Requia Weeberb J.¹²^ORCID,Di Qian¹³^ORCID,Silvern Rachel⁴,Kelly James T.⁵,Koutrakis Petros¹,Mickley Loretta J.⁴,Sulprizio Melissa P.⁴,Amini Heresh¹⁶^ORCID,Shi Liuhua¹⁷,Schwartz Joel¹

Affiliation:

1. Department of Environmental Health, Harvard University, TH Chan School of Public Health, Boston, Massachusetts 02115, United States

2. School of Public Policy and Government, Fundação Getúlio Vargas, Brasília, Distrito Federal 72125590, Brazil

3. Research Center for Public Health, Tsinghua University, Beijing 100084, China

4. Harvard University, John A. Paulson School of Engineering and Applied Sciences, Cambridge, Massachusetts 02138, United States

5. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, Durham, North Carolina 27709, United States

6. Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 1165, Denmark

7. Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia 30322, United States

Funder

National Institute of Environmental Health Sciences

Health Effects Institute

U.S. Environmental Protection Agency

National Institute on Aging

Office of the Director

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry