Ozone and particulate matter have an adverse impact on the health of humans and other organisms. Their concentrations depend not only on emissions but also on meteorological conditions. In a changing climate, their ambient concentrations are therefore expected to change. However, even the sign of the changes is still highly uncertain, especially for particulate matter. Due to the complex interaction of meteorology and air quality, which is different for different species, and would ideally include feedback mechanisms, the best approach to study the effect of climate change is to use an air quality model that is coupled to a regional climate model, and analyse simulations that are performed with the coupled models. This study presents the coupling between the regional climate model RACMO and the regional chemistry transport model LOTOS-EUROS and first results for the present-day climate. The coupling consisted of a one-way coupling in which LOTOS-EUROS was able to read the meteorological fields form RACMO, furthermore LOTOS-EUROS was adapted to run in parallel, using openMP and a faster heterogeneous chemisty routine (EQsam instead of Isorropia). First of all, the report shows that the coupled system works and that runs can be performed within an acceptable amount of computation time. First, a RACMO run was performed for 1989-2009 using ERA-interim fields at the boundaries, and coupled to a LOTOS-EUROS run. A comparison of this meteorology with ECMWF analysis meteorology for 2003-2007 showed that for variables that are important for air quality, namely daily maximum temperature, daily average wind speed and wind direction, the correlation was very good with minor biases. Only for rain, which is also highly important, the correlation was poor, but annual totals were comparable. Rain is notably difficult to model and due to its discrete character small mismatches already lead to poor correlations. From a comparison of modelled air quality with observed concentrations for LOTOS-EUROS runs with ECMWF meteorology and with the downscaled RACMO-ERA_interim meteorology for the years 2003-2007, it followed that in general, modelled concentrations are correlated with observed concentrations for both runs and that their dependency on wind, temperature and rain is comparable. However, some biases were found in both runs. Ozone is underpredicted for high temperatures. Nitrate and ammonium are too sensitive to high temperatures and not sensitive enough for low temperatures and tend to be underestimated, even more so in the RACMO-LOTOS-EUROS run with EQsam. Sulfate is underestimated but its temperature dependency seems to be represented correctly. For black carbon and sea salt, no validation could be done due to a lack of observations. Finally, a run with LOTOS-EUROS using RACMO-downscaled ECHAM5r3 A1B climate scenario meteorology was performed for 1970-2060. In the present report, a preliminary analysis was done, restricted to 2003-2007. This already revealed differences in the meteorology: when using the climate scenario there were overall lower daily maximum temperatures, higher wind speeds and more rain, resulting in lower ozone and particulate matter concentrations. The period of 5 years is too short for a solid bias characterization of the meteorology and will be extended to the full ERA-interim period (1989-2009) to get more reliable estimates. This will be done in a follow-up of the present project, together with the analysis of the climate run for our target period: the climate in 2050.