| Literature DB >> 32491847 |
Melanie S Hammer1,2, Aaron van Donkelaar1,2, Chi Li2,3, Alexei Lyapustin4,5, Andrew M Sayer4,5, N Christina Hsu4, Robert C Levy4, Michael J Garay6, Olga V Kalashnikova6, Ralph A Kahn4, Michael Brauer7,8, Joshua S Apte9, Daven K Henze10, Li Zhang11,12, Qiang Zhang13,14, Bonne Ford15, Jeffrey R Pierce15, Randall V Martin1,2,16.
Abstract
Exposure to outdoor fine particulate matter (PM2.5) is a leading risk factor for mortality. We develop global estimates of annual PM2.5 concentrations and trends for 1998-2018 using advances in satellite observations, chemical transport modeling, and ground-based monitoring. Aerosol optical depths (AODs) from advanced satellite products including finer resolution, increased global coverage, and improved long-term stability are combined and related to surface PM2.5 concentrations using geophysical relationships between surface PM2.5 and AOD simulated by the GEOS-Chem chemical transport model with updated algorithms. The resultant annual mean geophysical PM2.5 estimates are highly consistent with globally distributed ground monitors (R2 = 0.81; slope = 0.90). Geographically weighted regression is applied to the geophysical PM2.5 estimates to predict and account for the residual bias with PM2.5 monitors, yielding even higher cross validated agreement (R2 = 0.90-0.92; slope = 0.90-0.97) with ground monitors and improved agreement compared to all earlier global estimates. The consistent long-term satellite AOD and simulation enable trend assessment over a 21 year period, identifying significant trends for eastern North America (-0.28 ± 0.03 μg/m3/yr), Europe (-0.15 ± 0.03 μg/m3/yr), India (1.13 ± 0.15 μg/m3/yr), and globally (0.04 ± 0.02 μg/m3/yr). The positive trend (2.44 ± 0.44 μg/m3/yr) for India over 2005-2013 and the negative trend (-3.37 ± 0.38 μg/m3/yr) for China over 2011-2018 are remarkable, with implications for the health of billions of people.Entities:
Year: 2020 PMID: 32491847 DOI: 10.1021/acs.est.0c01764
Source DB: PubMed Journal: Environ Sci Technol ISSN: 0013-936X Impact factor: 9.028