International audienceAerosol modeling is a challenging scientific problem aimed at improving our knowledge in the many complex processes involved in multiphase chemistry and transport. Correct simulations of aerosols are also required in order to elaborate particle emission reduction strategies. The CHIMERE chemistry transport model (Atmos. Environ. 35 (2001) 6277) has been improved to account for particle transport, formation, deposition at the European scale. The aerosol model accounts both for inorganic (NO3−, SO42−, NH4+) and organic species of primary or secondary origin. Secondary organic aerosols from biogenic and anthropogenic gas precursors are partitioned into gas and particulate phases through a temperature dependent partition coefficient. The modeling approach is presented in this paper with preliminary simulation results over Europe. Comparisons with available data at background stations give acceptable results on PM10, with correlation coefficients usually exceeding 0.5 and normalized errors in the 30–80% range in many regions. However, results on sulfate, nitrate and ammonium species display less correct error statistics. Comparisons on sulfate concentrations give normalized errors in the range 30–80% in summer and less correct in winter. Temporal correlation coefficients usually range from 0.30 to 0.70. Nitrate concentrations are better simulated during winter than during summer. Difficulties in simulating heterogeneous and aqueous phase processes could explain model deficiencies. Moreover, temperature dependence of gas/particle partitioning processes for nitrate, ammonium and secondary organic species could mainly explain the seasonal variability of biases. Model deficiencies are observed in Southern countries, certainly due to natural dust emissions and resuspended particles. Finally, sea salts seems to have a quite significant influence on error statistics in coastal areas

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1] For the first time, the long-term evaluation of an operational real-time air quality forecasting and analysis system is presented, using error statistics over 3 consecutive years. This system, called PREV'AIR, is the French air quality forecasting and monitoring system. It became operational in 2003 as a result of a cooperation between several public organizations. The system forecasts and analyzes air quality throughout Europe, with a zoom over France, for regulatory pollutants: ozone (O 3 ), particulate matter with diameter smaller than 10 mm (PM 10 ), and nitrogen dioxide (NO 2 ). The ability of PREV'AIR to forecast, up to 3 days ahead, photochemical and particle pollution over the domains considered is demonstrated: daily ozone maxima forecasts correlate with observations with 0.75-0.85 mean coefficients; U.S. Environmental Protection Agency acceptance criteria relative to the forecast accuracy for high concentrations and daily maxima are met for more than 90% of the measurement sites. For NO 2 and PM 10 , the performance corresponds to the state of the art. The contribution of weather forecast errors to air quality predictability is addressed: ozone daily maxima forecast errors are not dominated by meteorological forecast errors; for rural stations, only 6% (15% and 25%, respectively) of the error variance is due to meteorological forecast errors on the first 24 (48 and 72, respectively) hours. The Model Output Statistics procedure, implemented in PREV'AIR, is proved to improve ozone forecasts, especially when photochemical pollution episodes occur. The PREV'AIR real-time analysis procedure, based on a kriging method, provides an accurate and comprehensive description of surface ozone fields over France. Citation: Honoré, C., et al. (2008), Predictability of European air quality: Assessment of 3 years of operational forecasts and analyses by the PREV'AIR system,