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, Jaqueline Burke, John Jackson, Robyn Latimer, Emily Stone, Ihab Abboud, Clement Akoshile, 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 Segev, Sachchida N. Tripathi, Chien Wang, Qiang Zhang, Michael Brauer, Yinon Rudich, Randall V. Martin

Research output: Contribution to journalArticlepeer-review

156 Citations (Scopus)

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.

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

Bibliographical note

Funding Information:
SPARTAN is an IGAC-endorsed activity (www.igacproject. org). The National Sciences and Engineering Research Council of Canada supported this work. Crystal Weagle was partially supported by the Nova Scotia Research and Innovation Graduate Scholarship. Sachchida Tripathi acknowledges the Indo-UK joint project (Grant no. DST/INT/UK/P-144/ 2016), UKIERI, and is thankful to DST for the financial support. Yinon Rudich acknowledges support from the Israel Science Foundation (Grant No. 236/16) and from the Environmental Health Fund (Israel). We are grateful to the numerous SPARTAN site operators for their careful measurements presented here.

Publisher Copyright:
© 2018 American Chemical Society.

ASJC Scopus Subject Areas

  • General Chemistry
  • Environmental Chemistry

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