Assessment of Traffic-Related Air Pollution in Kirkuk City, Iraq Using Python-Based AERMOD and GIS

Urban air pollution poses significant health and environmental concerns in rapidly developing cities such as Kirkuk, Iraq. This study examines the spatial distribution and intensity of PM2.5, NOx, and CO along the Kirkuk-Baghdad Road using AERMOD integrated with Python-based GIS tools. Emission rates were calculated from vehicle counts, speeds, and emission factors during the peak traffic hours of 8-10 AM and 5-7 PM. The model incorporated meteorological data, terrain characteristics, and emission sources to simulate pollutant dispersion patterns. The results revealed that pollutant concentrations near traffic hotspots frequently exceeded the proposed limits. Peak concentrations reached 125 μg/m³ for PM2.5 at K-B R16, 21 ppm for CO, and 1.00 ppm for NOx at K-B R18. Heavy-duty vehicles, especially trucks and motorcycles, contributed significantly to elevated concentrations. Weather conditions and topography influenced dispersion patterns substantially. Python-based spatial analysis facilitated efficient processing of traffic and monitoring data, enabling visualization of pollution hotspots and comprehensive mapping across the study area. This research demonstrates the value of integrated GIS-AERMOD approaches for urban air quality assessment and provides insights for traffic management and emission-reduction strategies to protect public health.