Articles | Volume 8, issue 1
https://doi.org/10.5194/gmd-8-21-2015
https://doi.org/10.5194/gmd-8-21-2015
Model evaluation paper
 | 
14 Jan 2015
Model evaluation paper |  | 14 Jan 2015

High-resolution air quality simulation over Europe with the chemistry transport model CHIMERE

E. Terrenoire, B. Bessagnet, L. Rouïl, F. Tognet, G. Pirovano, L. Létinois, M. Beauchamp, A. Colette, P. Thunis, M. Amann, and L. Menut

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Cited articles

Altshuller, A. P.: Atmospheric concentrations and distributions of chemical substances, in: the Acidic Deposition Phenomenon and its Effects, US Environmental Protection Agency, Washington, DC, 1982.
Amann, M., Bertok, I., Borken-Kleefeld, J., Cofala, J., Heyes, C., Höglund-Isaksson, L., Klimont, Z., Nguyen, B., Posch, M., Rafaj, P., Sandler, R., Schöpp, W., Wagner, F., and Winiwarter, W.: Cost-effective control of air quality and greenhouse gases in Europe: Modeling and policy applications, Environ. Model. Softw., 26, 1489–1501, 2011.
Amato, F., Pandolfi, M., Escrig, A., Querol, X., Alastuey, A., Pey, J., Perez, N., and Hopke, P. K.: Quantifying road dust resuspension in urban environment by Multilinear Engine: A comparison with PMF2, Atmos. Environ., 43, 2770–2780, 2009.
Ansari, A. S. and Pandis, S. N.: Response of Inorganic PM to Precursor Concentrations, Environ. Sci. Technol., 32, 2706–2714, 1998.
Appel, K. W., Gilliam, R. C., Davis, N., and Zubrow, A.: Overview of the Atmospheric Model Evaluation Tool (AMET) v1.1 for evaluating meteorological and air quality models, Environ. Model. Softw., 26, 434–443, 2011.
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Short summary
The model reproduces the temporal variability of NO2, O3, PM10, PM2.5 better at rural than urban background stations. The fractional biases show that the model performs slightly better at RB sites than at UB sites for NO2, O3 and PM10. At UB sites, CHIMERE reproduces PM2.5 better than PM10. This is primarily the result of an underestimation of coarse particulate matter (PM) associated with uncertainties on SOA chemistry and their precursor emissions, dust and sea salt.