The spatial-temporal exposure to traffic-related Particulate Matter emissions

The paper simulates the spatial variations in the sources of, and exposure to, traffic-related PM10 emissions for the city of Vienna, Austria. Using an extended and calibrated MATSim micro-simulation model, we reproduce agent-level mobility patterns for a representative day. Street-level PM10 emissions, mostly from cars, are extrapolated for the entire city to estimate concentration and exposure levels at hourly intervals. We show that exposure levels exceed the recommended 50 mu g/m3 threshold between peak travel hours at home, education, and work locations. Among different socioeconomic status (SES) groups, urban, single, 15 years and younger, and those living near the city center face high exposure levels, while car users, that cause a majority of the emissions, are relatively less exposed. Finally, we show that Shared Autonomous Electric Vehicles (SAEVs) reduce PM10 emissions, but the benefits are not homogeneously distributed across the different SES groups.