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A model inter-comparison study focussing on episodes with elevated PM10 concentrations
AbstractFive three-dimensional chemical transport models of different complexity were applied to Central Europe to assess the ability of models to reproduce PM10 concentrations under highly polluted conditions. The participating models were the French CHIMERE model, the Dutch LOTOS-EUROS model, as well as the REM-CALGRID, the EURAD and the LM–MUSCAT models from Germany. In the selected 80-day period, observed PM10 daily mean concentrations reached values well above 50μgm−3 on many days in large parts of Northern Germany. This model evaluation shows that there is an increasing underestimation of primary and secondary species with increasing observed PM10. The high PM levels were observed under stagnant weather conditions, which are difficult to simulate with either prognostic or diagnostic, interpolation-based meteorological models. Thus, it is quite likely that uncertainties in PM emissions and incomplete process sub-modules each separately account for only a portion of the underestimation of high PM. Uncertainties in key boundary layer parameters, which can differ by a factor of two or more between the models, represent an additional source of error—both as direct sources of error through the transporting meteorological fields and indirect sources of error through the physico-chemical modules which rely on key boundary layer parameters.
A model inter-comparison study focussing on episodes with elevated PM10 concentrations
AbstractFive three-dimensional chemical transport models of different complexity were applied to Central Europe to assess the ability of models to reproduce PM10 concentrations under highly polluted conditions. The participating models were the French CHIMERE model, the Dutch LOTOS-EUROS model, as well as the REM-CALGRID, the EURAD and the LM–MUSCAT models from Germany. In the selected 80-day period, observed PM10 daily mean concentrations reached values well above 50μgm−3 on many days in large parts of Northern Germany. This model evaluation shows that there is an increasing underestimation of primary and secondary species with increasing observed PM10. The high PM levels were observed under stagnant weather conditions, which are difficult to simulate with either prognostic or diagnostic, interpolation-based meteorological models. Thus, it is quite likely that uncertainties in PM emissions and incomplete process sub-modules each separately account for only a portion of the underestimation of high PM. Uncertainties in key boundary layer parameters, which can differ by a factor of two or more between the models, represent an additional source of error—both as direct sources of error through the transporting meteorological fields and indirect sources of error through the physico-chemical modules which rely on key boundary layer parameters.
A model inter-comparison study focussing on episodes with elevated PM10 concentrations
Stern, R. (author) / Builtjes, P. (author) / Schaap, M. (author) / Timmermans, R. (author) / Vautard, R. (author) / Hodzic, A. (author) / Memmesheimer, M. (author) / Feldmann, H. (author) / Renner, E. (author) / Wolke, R. (author)
Atmospheric Environment ; 42 ; 4567-4588
2008-01-28
22 pages
Article (Journal)
Electronic Resource
English
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