A Mathematical Model for PM2.5 Prediction based on Vehicle Density and Wind Speed in Samphanthawong district, Bangkok

Abstract

Bangkok frequently experiences concerning levels of air pollution, particularly during its dry season. This pollution is primarily driven by emissions from vehicles, agricultural burning in nearby regions, industrial activities, and construction dust, all exacerbated by unfavorable weather conditions that trap pollutants. Samphanthawong District, especially Yaowarat, consistently grapples with severe PM2.5 pollution during this period. Our research emphasizes the critical role of meteorological factors, such as wind speed and natural ventilation, in dispersing urban pollutants. While the simulation model proved stable and its computational results were not significantly affected by the chosen time step, it highlighted a major issue: PM2.5 concentrations in Samphanthawong decrease very slowly due to light winds and inadequate airflow. Therefore, to effectively manage air pollution in this area, additional measures are needed to improve ventilation or directly reduce PM2.5 sources, as natural factors alone cannot achieve rapid pollutant reduction.