Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors-Reference-Cited by-同舟云学术

Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors

Published:2016-03-24 Issue:7 Volume:50 Page:3762-3772
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

van Donkelaar Aaron¹,Martin Randall V.¹²,Brauer Michael³,Hsu N. Christina⁴,Kahn Ralph A.⁴,Levy Robert C.⁴,Lyapustin Alexei⁴⁵,Sayer Andrew M.⁴⁵,Winker David M.⁶

Affiliation:

1. Department of Physics and Atmospheric Science, Dalhousie University, Halifax, N.S. Canada

2. Harvard-Smithsonian Center for Astrophysics, Cambridge, Massachusetts 02138, United States

3. School of Population and Public Health, The University of British Columbia, 2206 East Mall, Vancouver, British Columbia V6T1Z3, Canada

4. NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, United States

5. Goddard Earth Sciences Technology and Research, Universities Space Research Association, Greenbelt, Maryland 20771, United States

6. NASA Langley Research Center, Hampton, Virginia 23665, United States

Funder

Government of Canada

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.5b05833

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4. A new hybrid spatio-temporal model for estimating daily multi-year PM2.5 concentrations across northeastern USA using high resolution aerosol optical depth data

5. Estimating Ground-Level PM2.5 in China Using Satellite Remote Sensing

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