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Titel |
Influence of satellite-derived photolysis rates and NOx emissions on Texas ozone modeling |
VerfasserIn |
W. Tang, D. S. Cohan, A. Pour-Biazar, L. N. Lamsal, A. T. White, X. Xiao, W. Zhou, B. H. Henderson, B. F. Lash |
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 ; 15, no. 4 ; Nr. 15, no. 4 (2015-02-16), S.1601-1619 |
Datensatznummer |
250119433
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Publikation (Nr.) |
copernicus.org/acp-15-1601-2015.pdf |
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Zusammenfassung |
Uncertain photolysis rates and emission inventory impair the accuracy of
state-level ozone (O3) regulatory modeling. Past studies have
separately used satellite-observed clouds to correct the model-predicted
photolysis rates, or satellite-constrained top-down NOx emissions to
identify and reduce uncertainties in bottom-up NOx emissions. However,
the joint application of multiple satellite-derived model inputs to improve
O3 state implementation plan (SIP) modeling has rarely been explored.
In this study, Geostationary Operational Environmental Satellite (GOES)
observations of clouds are applied to derive the photolysis rates, replacing
those used in Texas SIP modeling. This changes modeled O3
concentrations by up to 80 ppb and improves O3 simulations by reducing
modeled normalized mean bias (NMB) and normalized mean error (NME) by up to
0.1. A sector-based discrete Kalman filter (DKF) inversion approach is
incorporated with the Comprehensive Air Quality Model with extensions
(CAMx)–decoupled direct method (DDM) model to adjust Texas NOx
emissions using a high-resolution Ozone Monitoring Instrument (OMI) NO2
product. The discrepancy between OMI and CAMx NO2 vertical column
densities (VCDs) is further reduced by increasing modeled NOx lifetime
and adding an artificial amount of NO2 in the upper troposphere. The
region-based DKF inversion suggests increasing NOx emissions by
10–50% in most regions, deteriorating the model performance in predicting
ground NO2 and O3, while the sector-based DKF inversion tends to
scale down area and nonroad NOx emissions by 50%, leading to a
2–5 ppb decrease in ground 8 h O3 predictions. Model performance in
simulating ground NO2 and O3 are improved using sector-based
inversion-constrained NOx emissions, with 0.25 and 0.04 reductions in
NMBs and 0.13 and 0.04 reductions in NMEs, respectively. Using both
GOES-derived photolysis rates and OMI-constrained NOx emissions
together reduces modeled NMB and NME by 0.05, increases the model
correlation with ground measurement in O3 simulations, and makes O3
more sensitive to NOx emissions in the O3 non-attainment areas. |
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