Chemical transport models (CTM) are powerful tools to assess the health risk of population exposure to atmospheric pollutants. CTM simulations can cover large areas and provide quantitative estimates of air pollution concentrations. This is especially useful in areas where surface measurements are scarce and satellite data are acquired at low frequencies (limited to almost clear skies). However, the performance of these models is strongly dependent on the available input data. As partners in the project “Arctic Community Resilience to Boreal Environmental Change: Assessing Risks from Fire and Diseases” (ACRoBEAR), we have used the MATCH CTM, developed by the Swedish Meteorological and Hydrological Institute—SMHI, to assess the risk associated with forest fire smoke plumes. The work presented focuses on model runs for Europe from June to August 2018. The model domain covered all parts of Europe with major fires during that period, and extended well beyond the Arctic Circle. Two fire emissions inventories were used—the Copernicus GFAS product, with 0.1° × 0.1° horizontal resolution, and the FINNv2.2–NCAR inventory, with a finer spatial resolution (1 km × 1 km). The impacts of wildfire-related particulate matter on the extinction coefficient and tropospheric ozone concentrations were tested with the MATCH model. The model results are sensitive to the correction of the photolysis rate with the extinction coefficient impacting the simulated near-surface ozone concentrations by up to 50 µg m-3, on an hourly basis.