AERMOD in Air Pollution Modeling for Complex Environment: A Comprehensive Review of Global and Regional Applications, Technological Integrations, Health Risk Assessments, and Policy Implications

Purpose: AERMOD, developed by the U.S. Environmental Protection Agency, is a widely used regulatory model for estimating ground-level pollutant concentrations. This narrative review evaluates its applications, integrations, and limitations based on previous literature. Methodology: Articles were selected from Scopus, Web of Science, and ScienceDirect using thematic relevance across six domains: urban and industrial dispersion, GIS and meteorological integration, health risk assessment, model comparison, regulatory compliance, and technological innovation. Findings: AERMOD’s Gaussian plume structure and planetary boundary layer parameterization supports accurate modeling of pollutants such as PM₂.₅, NO₂, SO₂, and CO. Its integration with GIS, AERMET, and WRF improves spatial visualization and meteorological fidelity. In Southeast Asia, particularly Malaysia, AERMOD has been used in exposure studies, environmental impact assessments, and policy enforcement despite data limitations. Emerging trends include the use of artificial intelligence (AI) and machine learning to enhance model performance in complex terrains and data-scarce regions. Comparative studies show AERMOD performs well in steady-state scenarios but has limitations in modeling secondary pollutants and non-uniform topography. Research Implication: Overall, AERMOD remains a scientifically credible and policy-relevant model. To meet future air quality and climate challenges, further advancements should focus on hybrid modeling, AI integration, and real-time monitoring inputs. These improvements will enhance AERMOD’s role in urban air quality management and sustainable environmental planning.