| Literature DB >> 30215246 |
Crystal L Weagle1,2, Graydon Snider2, Chi Li2, Aaron van Donkelaar2, Sajeev Philip2,3, Paul Bissonnette2, Jaqueline Burke2, John Jackson2, Robyn Latimer2, Emily Stone2, Ihab Abboud4, Clement Akoshile5, Nguyen Xuan Anh6, Jeffrey Robert Brook7, Aaron Cohen8, Jinlu Dong9, Mark D Gibson10, Derek Griffith11, Kebin B He9, Brent N Holben12, Ralph Kahn12, Christoph A Keller13,14, Jong Sung Kim15, Nofel Lagrosas16, Puji Lestari17, Yeo Lik Khian18, Yang Liu19, Eloise A Marais20, J Vanderlei Martins21, Amit Misra22, Ulfi Muliane17, Rizki Pratiwi17, Eduardo J Quel23, Abdus Salam24, Lior Segev25, Sachchida N Tripathi22, Chien Wang18, Qiang Zhang9, Michael Brauer26, Yinon Rudich25, Randall V Martin1,2,27.
Abstract
Exposure to ambient fine particulate matter (PM2.5) is a leading risk factor for the global burden of disease. However, uncertainty remains about PM2.5 sources. We use a global chemical transport model (GEOS-Chem) simulation for 2014, constrained by satellite-based estimates of PM2.5 to interpret globally dispersed PM2.5 mass and composition measurements from the ground-based surface particulate matter network (SPARTAN). Measured site mean PM2.5 composition varies substantially for secondary inorganic aerosols (2.4-19.7 μg/m3), mineral dust (1.9-14.7 μg/m3), residual/organic matter (2.1-40.2 μg/m3), and black carbon (1.0-7.3 μg/m3). Interpretation of these measurements with the GEOS-Chem model yields insight into sources affecting each site. Globally, combustion sectors such as residential energy use (7.9 μg/m3), industry (6.5 μg/m3), and power generation (5.6 μg/m3) are leading sources of outdoor global population-weighted PM2.5 concentrations. Global population-weighted organic mass is driven by the residential energy sector (64%) whereas population-weighted secondary inorganic concentrations arise primarily from industry (33%) and power generation (32%). Simulation-measurement biases for ammonium nitrate and dust identify uncertainty in agricultural and crustal sources. Interpretation of initial PM2.5 mass and composition measurements from SPARTAN with the GEOS-Chem model constrained by satellite-based PM2.5 provides insight into sources and processes that influence the global spatial variation in PM2.5 composition.Entities:
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Year: 2018 PMID: 30215246 DOI: 10.1021/acs.est.8b01658
Source DB: PubMed Journal: Environ Sci Technol ISSN: 0013-936X Impact factor: 9.028