Atmospheric Chemistry and Physics (Nov 2021)

Changes in PM<sub>2.5</sub> concentrations and their sources in the US from 1990 to 2010

  • K. Skyllakou,
  • P. G. Rivera,
  • B. Dinkelacker,
  • E. Karnezi,
  • E. Karnezi,
  • I. Kioutsioukis,
  • C. Hernandez,
  • P. J. Adams,
  • S. N. Pandis,
  • S. N. Pandis

DOI
https://doi.org/10.5194/acp-21-17115-2021
Journal volume & issue
Vol. 21
pp. 17115 – 17132

Abstract

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Significant reductions in emissions of SO2, NOx, volatile organic compounds (VOCs), and primary particulate matter (PM) took place in the US from 1990 to 2010. We evaluate here our understanding of the links between these emissions changes and corresponding changes in concentrations and health outcomes using a chemical transport model, the Particulate Matter Comprehensive Air Quality Model with Extensions (PMCAMx), for 1990, 2001, and 2010. The use of the Particle Source Apportionment Algorithm (PSAT) allows us to link the concentration reductions to the sources of the corresponding primary and secondary PM. The reductions in SO2 emissions (64 %, mainly from electric-generating units) during these 20 years have dominated the reductions in PM2.5, leading to a 45 % reduction in sulfate levels. The predicted sulfate reductions are in excellent agreement with the available measurements. Also, the reductions in elemental carbon (EC) emissions (mainly from transportation) have led to a 30 % reduction in EC concentrations. The most important source of organic aerosol (OA) through the years according to PMCAMx is biomass burning, followed by biogenic secondary organic aerosol (SOA). OA from on-road transport has been reduced by more than a factor of 3. On the other hand, changes in biomass burning OA and biogenic SOA have been modest. In 1990, about half of the US population was exposed to annual average PM2.5 concentrations above 20 µg m−3, but by 2010 this fraction had dropped to practically zero. The predicted changes in concentrations are evaluated against the observed changes for 1990, 2001, and 2010 in order to understand whether the model represents reasonably well the corresponding processes caused by the changes in emissions.