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| Titel |
Characterization of coarse particulate matter in the western United States: a comparison between observation and modeling |
| VerfasserIn |
R. Li, C. Wiedinmyer, K. R. Baker, M. P. Hannigan |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 13, no. 3 ; Nr. 13, no. 3 (2013-02-01), S.1311-1327 |
| Datensatznummer |
250017631
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| Publikation (Nr.) |
 copernicus.org/acp-13-1311-2013.pdf |
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| Zusammenfassung |
| 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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