Evaluating the effects of urban morphology and emissions on urban air quality using a CFD model

This study investigates how urban morphology and pollutant emissions influence near-surface meteorology and the spatial distributions of CO, NO₂, O₃, and PM_2.5 in Songdo, Incheon, Republic of Korea. We use a fine-scale air quality modeling framework that couples computational fluid dynamics with atmospheric chemistry, driven by mesoscale meteorological and chemical fields and high-resolution emissions developed using a top-down approach. Model performance is evaluated against meteorological observations and multi-site air quality measurements within the study area. To examine the determinants of spatial variability, the domain is divided into subzones and statistical analyses are applied to relate simulated surface concentrations to emissions and building morphology parameters, including building surface fraction and occlusivity. Surface concentrations show the strongest associations with emissions for CO, NO₂, and O₃, whereas occlusivity exhibits the strongest association with PM_2.5. Notably, systematic concentration differences are observed even under comparable emission levels, highlighting the influence of morphology on ventilation and near-surface pollutant accumulation. The findings suggest that preserving wind corridors and allocating open spaces, particularly in high-rise districts, can enhance ventilation and reduce pollutant buildup. This work supports urban planning and air quality management and provides a basis for future exposure and environmental health analyses.