dorsal/arxiv
View SchemaThe use of satellite and ground based measurements for estimating and reducing uncertainties in the spatial distribution of emissions of nitrogen oxides
| Authors | I. B. Konovalov, M. Beekmann, A. Richter, J. P. Burrows |
|---|---|
| Categories | |
| ArXiv ID | physics/0612144 |
| URL | https://arxiv.org/abs/physics/0612144 |
Abstract
We explore possibilities of improving the spatial structure of NOx emissions employed in a continental scale chemistry transport model (CTM) by using satellite measurements of nitrogen dioxide and ground-based observations of near surface ozone. In this study, we combine the tropospheric NO2 columns derived from SCIAMACHY measurements, the data from the EMEP ozone-monitoring network and the calculations performed with the CHIMERE CTM in the framework of an advanced inverse modelling scheme. All data used in the study correspond to the period of June-August 2003. The main distinctive feature of our inversion scheme is that, in contrast to more common inverse modelling approaches, the magnitudes of uncertainties in the input data are not explicitly predefined but rather estimated consistently with the a posteriori emissions as a result of the inversion. While the tropospheric NO2 columns are used for fitting the spatial distribution of the emission parameters of the model, the ozone observations are only used to estimate the averaged levels of uncertainties in a priori emissions. We use our method in order to estimate and to reduce uncertainties in the gridded (with the resolution of 1 degree) NOx emission data for Europe, Middle East and Northern Africa. It is found that the a priori emission estimates used in the standard version of CHIMERE are probably biased in several regions. On average, the uncertainties in total NOx emissions are estimated to be about 1.7 in terms of the geometric standard deviation in Europe and about 2.1 outside of Europe. The corrected emission estimates provide better agreement of the modelled results with observations for both NO2 columns and near surface concentrations of ozone.
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"abstract": "We explore possibilities of improving the spatial structure of NOx emissions\nemployed in a continental scale chemistry transport model (CTM) by using\nsatellite measurements of nitrogen dioxide and ground-based observations of\nnear surface ozone. In this study, we combine the tropospheric NO2 columns\nderived from SCIAMACHY measurements, the data from the EMEP ozone-monitoring\nnetwork and the calculations performed with the CHIMERE CTM in the framework of\nan advanced inverse modelling scheme. All data used in the study correspond to\nthe period of June-August 2003. The main distinctive feature of our inversion\nscheme is that, in contrast to more common inverse modelling approaches, the\nmagnitudes of uncertainties in the input data are not explicitly predefined but\nrather estimated consistently with the a posteriori emissions as a result of\nthe inversion. While the tropospheric NO2 columns are used for fitting the\nspatial distribution of the emission parameters of the model, the ozone\nobservations are only used to estimate the averaged levels of uncertainties in\na priori emissions. We use our method in order to estimate and to reduce\nuncertainties in the gridded (with the resolution of 1 degree) NOx emission\ndata for Europe, Middle East and Northern Africa. It is found that the a priori\nemission estimates used in the standard version of CHIMERE are probably biased\nin several regions. On average, the uncertainties in total NOx emissions are\nestimated to be about 1.7 in terms of the geometric standard deviation in\nEurope and about 2.1 outside of Europe. The corrected emission estimates\nprovide better agreement of the modelled results with observations for both NO2\ncolumns and near surface concentrations of ozone.",
"arxiv_id": "physics/0612144",
"authors": [
"I. B. Konovalov",
"M. Beekmann",
"A. Richter",
"J. P. Burrows"
],
"categories": [
"physics.ao-ph",
"physics.data-an"
],
"title": "The use of satellite and ground based measurements for estimating and reducing uncertainties in the spatial distribution of emissions of nitrogen oxides",
"url": "https://arxiv.org/abs/physics/0612144"
},
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