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

Crystal L. Weagle, Graydon Snider, Chi Li, Aaron van Donkelaar, Sajeev Philip, Paul Bissonnette, Iaqueline Burke, John Jackson, Robyn Latimer, Emily Stone, Ihab Abboud, Clement Akoshile, Nguyen Xuan Nguyen Xuan Anh, Jeffrey Robert Brook, Aaron Cohen, Jinlu Dong, Mark D. Gibson, Derek Griffith, Kebin B. He, Brent N. HolbenRalph Kahn, Christoph A. Keller, Jong Sung Kim, Nofel Lagrosas, Puji Lestari, Yeo Lik Khian, Yang Liu, Eloise A. Marais, J. Vanderlei Martins, Amit Misra, Ulfi Muliane, Rizki Pratiwi, Eduardo J. Quel, Abdus Salam, Lior Segey, Sachchida N. Tripathi, Chien Wang, Qiang Zhang, Michael Brauer, Yinon Rudich, Randall Martin

Research output: Contribution to journalArticlepeer-review

Abstract

Exposure to ambient fine particulate matter (PM 2.5) is a leading risk factor for the global burden of disease. However, uncertainty remains about PM 2.5 sources. We use a global chemical transport model (GEOS-Chem) simulation for 2014, constrained by satellite-based estimates of PM 2.5 to interpret globally dispersed PM 2.5 mass and composition measurements from the ground-based surface particulate matter network (SPARTAN). Measured site mean PM 2.5 composition varies substantially for secondary inorganic aerosols (2.4-19.7 μg/m 3), mineral dust (1.9-14.7 μg/m 3), residual/organic matter (2.1-40.2 μg/m 3), and black carbon (1.0-7.3 μg/m 3). 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/m 3), industry (6.5 μg/m 3), and power generation (5.6 μg/m 3) are leading sources of outdoor global population-weighted PM 2.5 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 PM 2.5 mass and composition measurements from SPARTAN with the GEOS-Chem model constrained by satellite-based PM 2.5 provides insight into sources and processes that influence the global spatial variation in PM 2.5 composition.

Original languageEnglish
Pages (from-to)11670-11681
Number of pages12
JournalEnvironmental Science & Technology
Volume52
Issue number20
DOIs
StatePublished - 16 Oct 2018

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • Environmental Chemistry

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