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| Titel |
Climate-forced air-quality modeling at the urban scale: sensitivity to model resolution, emissions and meteorology |
| VerfasserIn |
K. Markakis, M. Valari, O. Perrussel, O. Sanchez, C. Honore |
| 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. 13 ; Nr. 15, no. 13 (2015-07-14), S.7703-7723 |
| Datensatznummer |
250119896
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| Publikation (Nr.) |
 copernicus.org/acp-15-7703-2015.pdf |
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| Zusammenfassung |
| While previous research helped to identify and prioritize the sources of
error in air-quality modeling due to anthropogenic emissions and spatial
scale effects, our knowledge is limited on how these uncertainties affect
climate-forced air-quality assessments. Using as reference a 10-year model
simulation over the greater Paris (France) area at 4 km resolution and
anthropogenic emissions from a 1 km resolution bottom-up inventory, through
several tests we estimate the sensitivity of modeled ozone and PM2.5
concentrations to different potentially influential factors with a
particular interest over the urban areas. These factors include the model
horizontal and vertical resolution, the meteorological input from a climate
model and its resolution, the use of a top-down emission inventory, the
resolution of the emissions input and the post-processing coefficients used
to derive the temporal, vertical and chemical split of emissions. We show
that urban ozone displays moderate sensitivity to the resolution of
emissions (~ 8 %), the post-processing method (6.5 %) and
the horizontal resolution of the air-quality model (~ 5 %),
while annual PM2.5 levels are particularly sensitive to changes in
their primary emissions (~ 32 %) and the resolution of the
emission inventory (~ 24 %). The air-quality model
horizontal and vertical resolution have little effect on model predictions
for the specific study domain. In the case of modeled ozone concentrations,
the implementation of refined input data results in a consistent decrease
(from 2.5 up to 8.3 %), mainly due to inhibition of the titration rate
by nitrogen oxides. Such consistency is not observed for PM2.5. In
contrast this consistency is not observed for PM2.5. In addition we use
the results of these sensitivities to explain and quantify the discrepancy
between a coarse (~ 50 km) and a fine (4 km) resolution
simulation over the urban area. We show that the ozone bias of the coarse
run (+9 ppb) is reduced by ~ 40 % by adopting a higher
resolution emission inventory, by 25 % by using a post-processing
technique based on the local inventory (same improvement is obtained by
increasing model horizontal resolution) and by 10 % by adopting the annual
emission totals of the local inventory. The bias of PM2.5
concentrations follows a more complex pattern, with the positive values
associated with the coarse run (+3.6 μg m−3), increasing or
decreasing depending on the type of the refinement. We conclude that in the
case of fine particles, the coarse simulation cannot selectively incorporate
local-scale features in order to reduce its error. |
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