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Monitoring aerosols over wide areas is important for the assessment of the population's exposure to health relevant particulate matter (PM). Satellite observations of aerosol optical depth (AOD) can contribute to the improvement of highly needed analyzed and forecasted distributions of PM when combined with a model and ground-based observations. In this paper, we evaluate the contribution of column AOD observations from a future imager on a geostationary satellite by performing an Observing System Simulation Experiment (OSSE). In the OSSE simulated imager, AOD observations and ground-based PM observations are assimilated in the chemistry transport model LOTOS-EUROS to assess the added value of the satellite observations relative to the value of ground-based observations. Results show that in highly polluted situations, the imager AOD observations improve analyzed and forecasted PM2.5 concentrations even in the vicinity of simultaneously incorporated ground-based PM observations. The added value of the proposed imager is small when considering monthly averaged PM distributions. This is attributed to relatively large errors in the imager AODs in case of background aerosol loads coupled to the fact that the imager AODs are column values and an indirect estimate of PM. In the future, model improvements and optimization of the assimilation system should be achieved for better handling of situations with aerosol plumes above the boundary layer and satellite observations containing aerosol profile information. With the suggested improvements, the developed OSSE will form a powerful tool for determining the added value of future missions and defining requirements for planned satellite observations.