References

ACPD

Atmospheric Chemistry and Physics Discussions

ACPD

1680-7375

Copernicus GmbH

Göttingen, Germany

10.5194/acpd-12-11445-2012

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

¹ ² Wiedinmyer

¹ Baker

K. R.

³ Hannigan

M. P.

National Center for Atmospheric Research, 1850 Table Mesa Drive, Boulder, CO, USA

Department of Mechanical Engineering, University of Colorado, Boulder, CO, USA

Office of Air Quality, Planning, and Standards (OAQPS), United States Environmental Protection Agency, Research Triangle Park, NC, USA

03 05 2012

12 5 11445 11484

This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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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 reporting 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. To obtain insights for regional PM10–2.5 modeling, the observed results were also 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 were not included in the emission inventory used and/or the applied emissions were greatly under-estimated. Unlike observations, the modeled concentrations show similar seasonal, weekly, and diurnal pattern across the entire domain. CMAQ does not include organics in PM10–2.5, which recent measurements show to be a significant component. The results of the analysis 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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