This paper presents regional scale simulations aiming to assess the sensitivity of future air quality under anticipated climate change, with a focus on near-surface ozone (O 3 ) and particulate matter with a diameter < 10 µm (PM 10 ). Constant anthropogenic emissions and biogenic emissions varying with climate were used. The modelling was carried out with regional climate models coupled to Chemical Transport Models for 3 decadal time slices, under the IPCC A1B scenario, in both coarse (50 km) and high (10 km) resolution for Europe and for targeted domains of Central-Eastern Europe (CEE), respectively. Two modelling systems were applied: the RegCM/ CAMx and ALADINClimate/CMAQ driven by ECHAM5 and ARPEGE global climate models, respectively. A comprehensive 'operational' evaluation of the performance of modelling systems driven by re-analysis of ECMWF ERA-40 fields was carried out for one full year. Our modelling systems fulfilled the fractional bias (FB) and fractional error (FE) skill criteria and the benchmark of index of agreement (IA) for maximum daily running 8 h mean O 3 , with FBs ranging from + 4 to −11%, FEs of 14 to 31% and IAs of 0.63 to 0.87. The models' performance for annual, winter and daily mean PM 10 was weaker, with FBs of −3 to −49% and FEs of 38 to 66%, but skill criteria for PM were met. Those results justified the use of proposed modelling systems for future time projections. The simulated changes in climate has rather weak impacts on the air quality of the mid-century (2041−2050). For the end-century (2091−2100), our study shows an increase in summer mean O 3 and a decrease in annual mean PM 10 in CEE. The main climate factors responsible for projected changes were an increase in summer temperature and a decrease in summer precipitation for O 3 , and an increase in winter precipitation for PM 10 .

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The present study evaluates the National Aeronautics Space Administration (NASA) Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset that provides statistically downscaled CMIP5 historical and future climate projections of the daily precipitation sum and extreme temperatures at high spatial resolution. A multimodel ensemble from all 21 available models is composed and compared against gridded observations from E-OBS. The study is performed over Southeast Europe for the whole time span of the historical period of NEX-GDDP 1950–2005. The performance of the NEX-GDDP data was evaluated at multiple time scales such as annual, seasonal, monthly, and daily. The skill of the multimodel ensemble to reproduce the interannual variability, as well as the long-term trend, is also evaluated. Moreover, key climate indices of the Expert Team on Climate Change Detection and Indices (ETCCDI), derived from the ensemble extreme temperatures and precipitation are superimposed on their counterparts based on the reference dataset E-OBS. Findings of the performed research indicate that NEX-GDDP parameters are in good agreement with the reference over the considered period on monthly, seasonal and annual scales which agrees with the outcomes from similar studies for other parts of the world. There are also no systematic differences in the pattern of the biases of the minimum and maximum temperature. Generally, the multimodel ensemble reproduces the extreme temperatures significantly better than the precipitation sum. The analysis reveals also the nonnegligible inefficiency of the NEX-GDDP ensemble to reproduce the long-term trend of the considered parameters as well as the climate extremes expressed with the ETCCDI indices.