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| Titel |
10-year spatial and temporal trends of PM2.5 concentrations in the southeastern US estimated using high-resolution satellite data |
| VerfasserIn |
X. Hu, L. A. Waller, A. Lyapustin, Y. Wang, Y. Liu |
| 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 ; 14, no. 12 ; Nr. 14, no. 12 (2014-06-25), S.6301-6314 |
| Datensatznummer |
250118834
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| Publikation (Nr.) |
 copernicus.org/acp-14-6301-2014.pdf |
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| Zusammenfassung |
| Long-term PM2.5 exposure has been associated with
various adverse health outcomes. However, most ground monitors are located
in urban areas, leading to a potentially biased representation of true
regional PM2.5 levels. To facilitate epidemiological studies, accurate
estimates of the spatiotemporally continuous distribution of PM2.5
concentrations are important. Satellite-retrieved aerosol optical depth
(AOD) has been increasingly used for PM2.5 concentration estimation due
to its comprehensive spatial coverage. Nevertheless, previous studies
indicated that an inherent disadvantage of many AOD products is their coarse
spatial resolution. For instance, the available spatial resolutions of the
Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle
Imaging SpectroRadiometer (MISR) AOD products are 10 and 17.6 km,
respectively. In this paper, a new AOD product with 1 km spatial resolution
retrieved by the multi-angle implementation of atmospheric correction
(MAIAC) algorithm based on MODIS measurements was used. A two-stage model
was developed to account for both spatial and temporal variability in the
PM2.5–AOD relationship by incorporating the MAIAC AOD, meteorological
fields, and land use variables as predictors. Our study area is in the
southeastern US centered at the Atlanta metro area, and data from 2001 to
2010 were collected from various sources. The model was fitted annually, and
we obtained model fitting R2 ranging from 0.71 to 0.85, mean prediction error (MPE) from 1.73
to 2.50 μg m−3, and root mean squared prediction error (RMSPE) from 2.75 to 4.10 μg m−3. In
addition, we found cross-validation R2 ranging from 0.62 to 0.78, MPE
from 2.00 to 3.01 μg m−3, and RMSPE from
3.12 to 5.00 μg m−3, indicating a good agreement between the estimated and observed
values. Spatial trends showed that high PM2.5 levels occurred in urban
areas and along major highways, while low concentrations appeared in rural
or mountainous areas. Our time-series analysis showed that, for the 10-year
study period, the PM2.5 levels in the southeastern US have decreased
by ~20%. The annual decrease has been relatively steady
from 2001 to 2007 and from 2008 to 2010 while a significant drop occurred
between 2007 and 2008. An observed increase in PM2.5 levels in year
2005 is attributed to elevated sulfate concentrations in the study area in
warm months of 2005. |
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