Inverse modelling of the spatial distribution of NOx emissions on a continental scale using satellite data

[摘要] The recent important developments in satellite measurements of thecomposition of the lower atmosphere open the challengingperspective to use such measurements as independent information onsources and sinks of atmospheric pollutants. This study exploresthe possibility to improve estimates of gridded NO_xemissions used in a continental scale chemistry transport model(CTM), CHIMERE, by employing measurements performed by the GOMEand SCIAMACHY instruments. We set-up an original inverse modellingscheme that not only enables a computationally efficientoptimisation of the spatial distribution of seasonally averagedNO_x emissions (during summertime), but also allowsestimating uncertainties in input data and a priori emissions. Thekey features of our method are (i) replacement of the CTM by a setof empirical models describing the relationships betweentropospheric NO₂ columns and NO_x emissions withsufficient accuracy, (ii) combination of satellite data fortropospheric NO₂ columns with ground based measurements ofnear surface NO₂ concentrations, and (iii) evaluation ofuncertainties in a posteriori emissions by means of a specialBayesian Monte-Carlo experiment which is based on random samplingof errors of both NO₂ columns and emission rates. We haveestimated the uncertainty in a priori emissions based on the EMEPemission inventory to be about 1.9 (in terms of geometric standarddeviation) and found the uncertainty in a posteriori emissionsobtained from our inverse modelling scheme to be significantlylower (about 1.4). It is found also that a priori NO_xemission estimates are probable to be persistently biased in manyregions of Western Europe, and that the use of a posterioriemissions in the CTM improves the agreement between the modelledand measured data.

[学科分类] 大气科学