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| Titel |
Inverse modelling of the spatial distribution of NOx emissions on a continental scale using satellite data |
| VerfasserIn |
I. B. Konovalov, M. Beekmann, A. Richter, J. P. Burrows |
| 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 ; 6, no. 7 ; Nr. 6, no. 7 (2006-05-24), S.1747-1770 |
| Datensatznummer |
250003886
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| Publikation (Nr.) |
 copernicus.org/acp-6-1747-2006.pdf |
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| Zusammenfassung |
| The recent important developments in satellite measurements of the
composition of the lower atmosphere open the challenging
perspective to use such measurements as independent information on
sources and sinks of atmospheric pollutants. This study explores
the possibility to improve estimates of gridded NOx
emissions used in a continental scale chemistry transport model
(CTM), CHIMERE, by employing measurements performed by the GOME
and SCIAMACHY instruments. We set-up an original inverse modelling
scheme that not only enables a computationally efficient
optimisation of the spatial distribution of seasonally averaged
NOx emissions (during summertime), but also allows
estimating uncertainties in input data and a priori emissions. The
key features of our method are (i) replacement of the CTM by a set
of empirical models describing the relationships between
tropospheric NO2 columns and NOx emissions with
sufficient accuracy, (ii) combination of satellite data for
tropospheric NO2 columns with ground based measurements of
near surface NO2 concentrations, and (iii) evaluation of
uncertainties in a posteriori emissions by means of a special
Bayesian Monte-Carlo experiment which is based on random sampling
of errors of both NO2 columns and emission rates. We have
estimated the uncertainty in a priori emissions based on the EMEP
emission inventory to be about 1.9 (in terms of geometric standard
deviation) and found the uncertainty in a posteriori emissions
obtained from our inverse modelling scheme to be significantly
lower (about 1.4). It is found also that a priori NOx
emission estimates are probable to be persistently biased in many
regions of Western Europe, and that the use of a posteriori
emissions in the CTM improves the agreement between the modelled
and measured data. |
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