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 PM10 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.