Investigating impacts of chemistry and transport model formulation on model performance at European scale

The CAMx and CHIMERE chemistry and transport models were applied over Europe for the year 2006 in the framework of the AQMEII inter-comparison exercise. Model simulations used the same input data set thus allowing model performance evaluation to focus on differences related to model chemistry and physics. Model performance was investigated according to different conditions, such as monitoring station classification and geographical features. An improved evaluation methodology, based on the Wilcoxon statistical test, was implemented to provide objectivity in the comparison of model performance. The models demonstrated similar geographical variations in model performance with just a few exceptions. Both models displayed great performance variability from region to region and within the same region for NO2 and PM10. Station type is relevant mainly for pollutants directly influenced by low level emission sources, such as NO2 and PM10. The analysis of the differences between CAMx and CHIMERE results revealed that both physical and chemical processes influenced the model performance. Particularly, differences in vertical diffusion coefficients (Kz) and 1st layer wind speed can affect the surface concentration of primary compounds, especially for stable conditions. Differently, differences in the vertical profiles of Kz strongly influenced the impact of aloft sources on ground level concentrations of both primary pollutants such as SO2 as well as PK10 compounds. CAMx showed stronger photochemistry than CHIMERE giving rise to higher ozone concentrations that agreed better with observations. Nonetheless, in some areas the more effective photochemistry showed by CAMx actually compensated for an underestimation in the background concentration. Finally, PM10 performance was rather poor for both models in most regions. CAMx performed always better than CHIMERE in terms of bias, while CHIMERE score for correlation was always higher than CAMx. As already mentioned, vertical mixing is one cause of such discrepancies in correlation. Differently, the stronger underestimation experienced by CHIMERE was mainly influenced by temporal smoothing of the boundary conditions, underestimation of low level emissions (mainly related to fires) and more intense depletion by wet deposition. (C) 2012 Elsevier Ltd. All rights reserved.