Simulation of PM₁₀ and PM_2.5 Pollutant Dispersion Based on Urban Morphology and the Computational Fluid Dynamics (CFD) Method

Abstract. Air pollution is one of the most serious environmental problems in large cities, particularly in developing countries, where it has escalated into a major crisis that endangers public health. To better understand and manage this issue, Computational Fluid Dynamics (CFD) provides an effective tool for analyzing airflow and pollutant dispersion in complex urban settings. This study aims to examine how urban morphology affects ventilation efficiency and pollutant dispersion using three-dimensional (3D) modeling integrated with CFD simulation. The case study focuses on Mashhad, Iran’s second-largest metropolis, within a 300-meter radius of the Avini Air Quality Monitoring Station. First, a detailed 3D model of the study area was created using geospatial building data, including height and geometry. Then, the dispersion of PM₂.₅ and PM₁₀ particles was simulated in the CFD environment based on actual air quality data and prevailing wind conditions. The Residence Time Index (RTI) was calculated to represent the ability of the built environment to retain pollutants. Model validation was performed through comparison with results from a reference study, confirming good agreement and reliability. The findings indicate that areas with higher building density and lower wind velocity tend to trap more pollutants, leading to increased particle accumulation. Variations in building height and differences between PM₁₀ and PM₂.₅ behavior also influence dispersion patterns. Overall, integrating 3D urban modeling with CFD analysis provides a robust approach to understanding pollutant dynamics in urban areas and supports sustainable planning strategies aimed at improving air quality.