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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 13, issue 3 | Copyright
Atmos. Chem. Phys., 13, 1311-1327, 2013
https://doi.org/10.5194/acp-13-1311-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 01 Feb 2013

Research article | 01 Feb 2013

Characterization of coarse particulate matter in the western United States: a comparison between observation and modeling

R. Li1,2, C. Wiedinmyer1, K. R. Baker3, and M. P. Hannigan2 R. Li et al.
  • 1National Center for Atmospheric Research, 1850 Table Mesa Drive, Boulder, CO, USA
  • 2Department of Mechanical Engineering, University of Colorado, Boulder, CO, USA
  • 3Office of Air Quality, Planning, and Standards (OAQPS), United States Environmental Protection Agency, Research Triangle Park, NC, USA

Abstract. We provide a regional characterization of coarse particulate matter (PM10–2.5) spanning the western United States based on the analysis of measurements from 50 sites reported in the US EPA Air Quality System (AQS) and two state agencies. We found that the observed PM10–2.5 concentrations show significant spatial variability and distinct spatial patterns, associated with the distributions of land use/land cover and soil moisture. The highest concentrations were observed in the southwestern US, where sparse vegetation, shrublands or barren lands dominate with lower soil moistures, whereas the lowest concentrations were observed in areas dominated by grasslands, forest, or croplands with higher surface soil moistures. The observed PM10–2.5 concentrations also show variable seasonal, weekly, and diurnal patterns, indicating a variety of sources and their relative importance at different locations. The observed results were compared to modeled PM10–2.5 concentrations from an annual simulation using the Community Multiscale Air Quality modeling system (CMAQ) that has been designed for regulatory or policy assessments of a variety of pollutants including PM10, which consists of PM10–2.5 and fine particulate matter (PM2.5). The model under-predicts PM10–2.5 observations at 49 of 50 sites, among which 14 sites have annual observation means that are at least five times greater than model means. Model results also fail to reproduce their spatial patterns. Important sources (e.g. pollen, bacteria, fungal spores, and geogenic dust) were not included in the emission inventory used and/or the applied emissions were greatly under-estimated. Unlike the observed patterns that are more complex, modeled PM10–2.5 concentrations show the similar seasonal, weekly, and diurnal pattern; the temporal allocations in the modeling system need improvement. CMAQ does not include organic materials in PM10–2.5; however, speciation measurements show that organics constitute a significant component. The results improve our understanding of sources and behavior of PM10–2.5 and suggest avenues for future improvements to models that simulate PM10–2.5 emissions, transport and fate.

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