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| Titel |
Development of PM2.5 source impact spatial fields using a hybrid source apportionment air quality model |
| VerfasserIn |
C. E. Ivey, H. A. Holmes, Y. T. Hu, J. A. Mulholland, A. G. Russell |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 8, no. 7 ; Nr. 8, no. 7 (2015-07-20), S.2153-2165 |
| Datensatznummer |
250116458
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| Publikation (Nr.) |
 copernicus.org/gmd-8-2153-2015.pdf |
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| Zusammenfassung |
| An integral part of air quality management is knowledge of the impact of
pollutant sources on ambient concentrations of particulate matter (PM).
There is also a growing desire to directly use source impact estimates in
health studies; however, source impacts cannot be directly measured. Several
limitations are inherent in most source apportionment methods motivating the
development of a novel hybrid approach that is used to estimate source
impacts by combining the capabilities of receptor models (RMs) and chemical transport models (CTMs). The hybrid CTM–RM method calculates adjustment
factors to refine the CTM-estimated impact of sources at monitoring sites
using pollutant species observations and the results of CTM sensitivity
analyses, though it does not directly generate spatial source impact fields.
The CTM used here is the Community Multiscale Air Quality (CMAQ) model, and
the RM approach is based on the chemical mass balance (CMB) model. This work
presents a method that utilizes kriging to spatially interpolate
source-specific impact adjustment factors to generate revised CTM source
impact fields from the CTM–RM method results, and is applied for January
2004 over the continental United States. The kriging step is evaluated using
data withholding and by comparing results to data from alternative networks.
Data withholding also provides an estimate of method uncertainty. Directly
applied (hybrid, HYB) and spatially interpolated (spatial hybrid, SH) hybrid
adjustment factors at withheld observation sites had a correlation
coefficient of 0.89, a linear regression slope of 0.83 ± 0.02, and an
intercept of 0.14 ± 0.02. Refined source contributions reflect current
knowledge of PM emissions (e.g., significant differences in biomass burning
impact fields). Concentrations of 19 species and total PM2.5 mass
were reconstructed for withheld observation sites using HYB and SH
adjustment factors. The mean concentrations of total PM2.5 at
withheld observation sites were 11.7 (± 8.3), 16.3 (± 11), 8.59
(± 4.7), and 9.2 (± 5.7) μg m−3 for the
observations, CTM, HYB, and SH predictions, respectively. Correlations
improved for concentrations of major ions, including nitrate (CMAQ–DDM (decoupled direct method):
0.404, SH: 0.449), ammonium (CMAQ–DDM: 0.454, SH: 0.492), and sulfate
(CMAQ–DDM: 0.706, SH: 0.730). Errors in simulated concentrations
of metals were reduced considerably: 295 % (CMAQ–DDM) to 139 % (SH) for
vanadium; and 1340 % (CMAQ–DDM) to 326 % (SH) for manganese. Errors in simulated concentrations of some metals are expected to remain
given the uncertainties in source profiles. Species concentrations were
reconstructed using SH results, and the error relative to
observed concentrations was greatly reduced as compared to CTM-simulated
concentrations. Results demonstrate that the hybrid method along with a
spatial extension can be used for large-scale, spatially resolved source
apportionment studies where observational data are spatially and temporally
limited. |
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