Multi-Scale Comparison of Modeling Chains for Traffic-Related Air Pollutant Exposure Assessment

Abstract

Exposure to traffic-related air pollution is a major health concern in metropolitan areas. Decision-makers need reliable methodological supports to estimate exposure and evaluate strategies for reducing it. Modeling traffic conditions, estimating vehicle emissions, and measuring pollutant concentrations are key to providing detailed spatio-temporal estimations of pollutants. However, the coupling of traffic with emission models remains a significant source of uncertainty. This paper aims to establish the pertinent scale of modelling in an urban context. We compared emissions from two widely used European models (COPERT and HBEFA) using traffic conditions assessed by the microscopic traffic model Symuvia and the agent-based model MATSim. Outputs were aggregated at the trip level, street level, and square-cells grid, with the first aggregation serving as a benchmark. Our findings indicate that MATSim+COPERT and Symuvia+HBEFA produce more consistent results, driven primarily by the route assignment algorithm and emission models, providing a solid foundation for exposure estimation.

Keywords: Emission model, Symuvia, MATSim, Exposure, Traffic-related air pollution, Traffic simulation