The Spatial-temporal Distribution of Exposure to Traffic-related Particulate Matter Emissions in Vienna
The paper simulates hourly 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 and track the use of different travel modes and time spent at different location types. Hourly street-level PM10 emissions, mostly caused by cars, are extrapolated for the entire city. Simulations show high exposures during morning and evening travel peaks, especially at work, education, and home locations that also exceed the recommended 50 μg/m3 threshold. Among various socioeconomic status (SES) groups, urban, single, and those living near the city center face above-average exposures, while car users, which cause 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 different SES groups.