Assessing the impacts of urban morphology and emissions on city-scale air quality using a CFD model coupled to chemistry.

This study proposes a fine-scale urban air quality assessment framework to examine how building morphological parameters (BMPs; building surface fraction, BSF, and occlusivity, OCC) modulate near-surface meteorology, and how the combined effects of BMPs and pollutant emissions shape the distributions of CO, NO2, O3, and PM2.5. The framework employs a Fine-scale Air-Quality Simulation Unit (FASU) that integrates a computational fluid dynamics model coupled with a chemistry module, mesoscale background meteorological and concentration fields, and high-resolution top-down emissions. It is applied to a heterogeneous urban area in Incheon, South Korea, where FASU performance is evaluated against observations from a meteorological station and multiple air pollutant monitoring sites. To diagnose spatial controls, the 6 km × 6 km domain is partitioned into 36 subzones, and multiple linear regression is applied to relate subzone-mean surface concentrations to emissions and BMPs. Because near-surface wind speed is strongly correlated with BSF and OCC, it is excluded from the predictor set to avoid multicollinearity, and BMPs are used as morphological proxies for ventilation. Surface concentrations are most strongly associated with emissions for CO, NO2, and O3, whereas OCC exhibits the strongest association with PM2.5. Even with comparable emissions, differences in BMPs yield systematic concentration differences, underscoring the role of urban morphology in modulating near-surface air quality. Results show that wind corridors and open spaces, especially in high-rise districts, enhance ventilation and reduce pollutant accumulation. The framework and findings help identify morphology- and emission-driven hotspots and inform urban planning and air quality management in dense districts.