Agent-Based Modeling and Simulation for Urban Air Quality Assessment

Urban pollution poses a pressing environmental challenge, with substantial impacts on public health, particularly in urban areas. This paper presents a original approach that integrates vehicle-specific emission factors, derived from real-time traffic data, into an agent-based transport modeling framework. We introduce an emission calculation tool, augmented by supplementary data from HBEFA, incorporated into the MATSim environment to simulate multi-agent transport dynamics. The comprehensive MATSim scenario, encompassing digital road networks and public transportation systems, is generated through the Eqasim pipeline. This pipeline ensures a dependable pathway from initial data inputs to the completion of transport simulations. We apply this methodology in the real-world context of Calais, France, modeling pollutants such as NO \(_2\) , PM10, and PM2.5. This modeling effort generates emission maps that illustrate the results, offering valuable insights for emission analysis. Furthermore, our approach provides critical information for decision-makers involved in managing and assessing urban air quality, thus contributing to more informed environmental policies and interventions.