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Communication Dans Un Congrès Année : 2024

Agent-Based Modeling and Simulation for Urban Air Quality Assessment

Résumé

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.
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Dates et versions

hal-04447553 , version 1 (08-02-2024)

Identifiants

  • HAL Id : hal-04447553 , version 1

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Neda Mashhadi, Cyril Fonlupt, Matthieu Puigt, Gilles Roussel, Sébastien Verel. Agent-Based Modeling and Simulation for Urban Air Quality Assessment. 7 th International Conference on Logistics Operations Management: Smart Sustainable and Green Logistics, May 2024, Marrakech (Maroc), Morocco. ⟨hal-04447553⟩
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