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| Titel |
Photochemical grid model implementation and application of VOC, NOx, and O3 source apportionment |
| VerfasserIn |
R. H. F. Kwok, K. R. Baker, S. L. Napelenok, G. S. Tonnesen |
| 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. 1 ; Nr. 8, no. 1 (2015-01-29), S.99-114 |
| Datensatznummer |
250116032
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| Publikation (Nr.) |
 copernicus.org/gmd-8-99-2015.pdf |
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| Zusammenfassung |
| For the purposes of developing optimal emissions control strategies,
efficient approaches are needed to identify the major sources or groups of
sources that contribute to elevated ozone (O3) concentrations.
Source-based apportionment techniques implemented in photochemical grid
models track sources through the physical and chemical processes important
to the formation and transport of air pollutants. Photochemical model source
apportionment has been used to track source impacts of specific sources,
groups of sources (sectors), sources in specific geographic areas, and
stratospheric and lateral boundary inflow on O3. The implementation and
application of a source apportionment technique for O3 and its
precursors, nitrogen oxides (NOx) and volatile organic compounds (VOCs),
for the Community Multiscale Air Quality (CMAQ) model are described here.
The Integrated Source Apportionment Method (ISAM) O3 approach is a
hybrid of source apportionment and source sensitivity in that O3
production is attributed to precursor sources based on O3 formation
regime (e.g., for a NOx-sensitive regime, O3 is apportioned to
participating NOx emissions). This implementation is illustrated by
tracking multiple emissions source sectors and lateral boundary inflow.
NOx, VOC, and O3 attribution to tracked sectors in the application
are consistent with spatial and temporal patterns of precursor emissions.
The O3 ISAM implementation is further evaluated through comparisons of
apportioned ambient concentrations and deposition amounts with those derived
from brute force zero-out scenarios, with correlation coefficients ranging
between 0.58 and 0.99 depending on specific combination of target species
and tracked precursor emissions. Low correlation coefficients occur for
chemical regimes that have strong nonlinearity in O3 sensitivity,
which demonstrates different functionalities between source apportionment
and zero-out approaches, where appropriate use depends on whether source
attribution or source sensitivity is desired. |
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