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7273282 
Journal Article 
Global estimates and long-term trends of fine particulate matter concentrations (1998-2018) 
Hammer, MS; van Donkelaar, A; Li, C; Lyapustin, A; Sayer, AM; Hsu, NC; Levy, RC; Garay, MJ; Kalashnikova, OV; Kahn, RA; Brauer, M; Apte, JS; Henze, DK; Zhang, L; Zhang, Q; Ford, B; Pierce, JR; Martin, RV 
2020 
1 
Environmental Science & Technology
ISSN: 0013-936X
EISSN: 1520-5851 
54 
13 
7879-7890 
English 
32491847 
WOS:000548584900019 
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 (R-2 = 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 (R-2 = 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 mu g/m(3)/yr), Europe (-0.15 +/- 0.03 mu g/m(3)/yr), India (1.13 +/- 0.15 mu g/m(3)/yr), and globally (0.04 +/- 0.02 mu g/m(3)/yr). The positive trend (2.44 +/- 0.44 mu g/m(3)/yr) for India over 2005-2013 and the negative trend (-3.37 +/- 0.38 mu g/m(3)/yr) for China over 2011-2018 are remarkable, with implications for the health of billions of people. 
Color; Algorithms; Testing and assessment; Aerosols; Particulate matter 
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