Urban scale modelling of NO2, ultrafine particles, metal components in particulate matter in Augsburg, Germany, for health applications

This study employs a high-resolution modeling framework to quantify traffic-derived contributions to air pollution exposure in Augsburg, Germany, integrating a multi-scale model chain with agent-based population dynamics for exposure assessment. The microscale PALM4U model is driven by a customized WRF4PALM tool for a dynamic driver (meteorology, chemistry and aerosol) and utilizes a customized SALSA+SIMPLE mechanism with a source-tagging scheme. This enhancement explicitly isolates pollutants from road traffic, enabling direct attribution of NO₂, ultrafine particles (UFP), and trace metals within PM₂.₅ to vehicular emissions.

A novel aspect of the workflow is the integration of an agent-based model (ABM), which is informed by population mobility and activity data from the KORA (Kooperative Gesundheitsforschung in der Region Augsburg) cohort in Augsburg. The ABM simulates detailed spatiotemporal trajectories of individuals, providing dynamic urban emissions and enabling the reconstruction of personalized exposure profiles. The coupled PALM-ABM system overlays high-resolution, time-resolved exposure metrics such as inhaled dose and peak concentrations for traffic-attributable pollutants.

The model’s accuracy is rigorously evaluated through a multi-scale validation approach. First, simulated city-wide concentration fields are compared with the measurements from regulatory air quality stations in Augsburg and detailed pollutant speciation data from the Joint Environmental Exposure Center (JEEC) measurement station. Second, spatial patterns are assessed against satellite observations (e.g., TROPOMI NO₂ vertical columns) to ensure consistency at the urban-to-regional scale.

This integrated framework provides unprecedented, source-resolved insights into the contribution of traffic to personal air pollution exposure in a real urban environment. It quantifies the dominant influence of traffic on NO₂ and UFP concentrations at the street scale, while also explaining the trace metals in PM₂.₅. The robust multi-source validation spanning ground stations, specialized monitoring, and satellite data ensures the reliability of both the meteorological-chemistry model and the exposure reconstruction. This methodology establishes the health-oriented urban air quality management and for evaluating the effectiveness of traffic-related emission reduction strategies.