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Monthly Global Estimates of Fine Particulate Matter and Their Uncertainty
Author(s) -
Aaron van Donkelaar,
Melanie S. Hammer,
Liam Bindle,
Michael Bräuer,
J. R. Brook,
M. J. Garay,
N. Christina Hsu,
О. В. Калашникова,
Ralph A. Kahn,
Colin Lee,
R. C. Levy,
Alexei Lyapustin,
A. M. Sayer,
Randall V. Martin
Publication year - 2021
Publication title -
environmental science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.851
H-Index - 397
eISSN - 1520-5851
pISSN - 0013-936X
DOI - 10.1021/acs.est.1c05309
Subject(s) - environmental science , particulates , aerosol , climatology , satellite , air quality index , east asia , atmospheric sciences , chemical transport model , population , meteorology , physical geography , geography , geology , demography , ecology , archaeology , aerospace engineering , china , sociology , engineering , biology
Annual global satellite-based estimates of fine particulate matter (PM 2.5 ) are widely relied upon for air-quality assessment. Here, we develop and apply a methodology for monthly estimates and uncertainties during the period 1998-2019, which combines satellite retrievals of aerosol optical depth, chemical transport modeling, and ground-based measurements to allow for the characterization of seasonal and episodic exposure, as well as aid air-quality management. Many densely populated regions have their highest PM 2.5 concentrations in winter, exceeding summertime concentrations by factors of 1.5-3.0 over Eastern Europe, Western Europe, South Asia, and East Asia. In South Asia, in January, regional population-weighted monthly mean PM 2.5 concentrations exceed 90 μg/m 3 , with local concentrations of approximately 200 μg/m 3 for parts of the Indo-Gangetic Plain. In East Asia, monthly mean PM 2.5 concentrations have decreased over the period 2010-2019 by 1.6-2.6 μg/m 3 /year, with decreases beginning 2-3 years earlier in summer than in winter. We find evidence that global-monitored locations tend to be in cleaner regions than global mean PM 2.5 exposure, with large measurement gaps in the Global South. Uncertainty estimates exhibit regional consistency with observed differences between ground-based and satellite-derived PM 2.5 . The evaluation of uncertainty for agglomerated values indicates that hybrid PM 2.5 estimates provide precise regional-scale representation, with residual uncertainty inversely proportional to the sample size.

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