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

Asjad Naqvi, Stefanie Peer, Johannes Müller, Markus Straub

Research output: Contribution to journalArticlepeer-review


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 μg/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.
Original languageEnglish
Article number103899
Number of pages21
JournalTransportation Research Part D: Transport and Environment
Publication statusPublished - 2023

Research Field

  • Former Research Field - Integrated Digital Urban Planning


  • MATSim model for Vienna
  • Austria
  • Traffic-related PM10 emissions
  • Concentration versus exposure
  • SES exposure inequality
  • Shared Autonomous Electric Vehicles


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