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A 9 yr air quality simulation is conducted from 2000 to 2008 over Europe using the Polyphemus/Polair3D chemical-transport model (CTM) and then evaluated against the measurements of the European Monitoring and Evaluation Programme (EMEP). <br><br> The spatial distribution of PM_2.5 over Europe shows high concentrations over northern Italy (36 μg m⁻³) and some areas of Eastern Europe, France, and Benelux, and low concentrations over Scandinavia, Spain, and the easternmost part of Europe. PM_2.5 composition differs among regions. <br><br> The operational evaluation shows satisfactory model performance for ozone (O₃). PM_2.5, PM₁₀, and sulfate (SO₄⁼) meet the performance goal of Boylan and Russell (2006). Nitrate (NO₃^&minus;) and ammonium (NH₄⁺) are overestimated, although NH₄⁺ meets the performance criterion. The correlation coefficients between simulated and observed data are 63% for O₃, 57% for PM₁₀, 59% for PM_2.5, 57% for SO₄⁼, 42% for NO₃^&minus;, and 58% for NH₄⁺. The comparison with other recent 1 yr model simulations shows that all models overestimate nitrate. The performance of PM_2.5, sulfate, and ammonium is comparable to that of the other models. <br><br> The dynamic evaluation shows that the response of PM_2.5 to changes in meteorology differs depending on location and the meteorological variable considered. Wind speed and precipitation show a strong negative day-to-day correlation with PM_2.5 and its components (except for sea salt, which shows a positive correlation), which tends towards 0 as the day lag increases. On the other hand, the correlation coefficient is near constant for temperature, for any day lag and PM_2.5 species, but it may be positive or negative depending on the species and, for sulfate, depending on the location. The effects of precipitation and wind speed on PM_2.5 and its components are better reproduced by the model than the effects of temperature. This is mainly due to the fact that temperature has different effects on the PM_2.5 components, unlike precipitation and wind speed, which impact most of the PM_2.5 components in the same way. <br><br> These results suggest that state-of-the-science air quality models reproduce satisfactorily the effect of meteorology on PM_2.5 and therefore are suitable to investigate the effects of climate change on particulate air quality, although uncertainties remain concerning semivolatile PM_2.5 components.