Abstract: This paper explores hourly spatial-temporal variations in the sources of, and exposure to, traffic-related Particulate Matter (PM) for the city of Vienna in Austria. Using a calibrated large-scale micro-simulation model, MATSim, we replicate the city's daily mobility patterns that are determined by the location of facilities, road network configuration, origin and destination, and choice of travel modes. We show that there are significant variations in PM exposures by location type (home, workplaces, educational institutions, leisure activities, etc.), that are determined by hourly traffic volume, road network density, and distance to roads. Further exploring variations in exposure by Socioeconomic Status (SES), we show that car owners, that cause the highest emissions, are the least exposed. Additionally, we find that certain SES groups, for example, women, single persons, as well as those living in or near the city center or near the Gürtel, have an above-average exposure. Finally, we explore the role of Shared Electric Vehicles (SEVs), that are introduced as an extension to the public transport system and show that they have significant potential to improve urban air quality; however, not all SES groups benefit equally.