Global Sources of Fine Particulate Matter: Interpretation of PM2.5 Chemical Composition Observed by SPARTAN using a Global Chemical Transport Model

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 gl...

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Bibliographic Details
Main Authors: Weagle, Crystal L, Lagrosas, Nofel, co-authors, 39
Format: text
Published: Archīum Ateneo 2018
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Online Access:https://archium.ateneo.edu/manila-observatory/1
https://pubs.acs.org/doi/10.1021/acs.est.8b01658
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Institution: Ateneo De Manila University
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Summary: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.