Assessment of Aermod and Adms for Nox Dispersion Modeling With a Combination of Line and Point Sources Publisher



Rezaali M¹ ; Fouladifard R^{2, 3} ; Oshaughnessy P⁴ ; Naddafi K^{5, 6} ; Karimi A⁷ Show Affiliations
Source: Stochastic Environmental Research and Risk Assessment Published:2025

Abstract

Atmospheric dispersion models use mathematical equations to calculate pollution concentrations in the receiving environment; however, there can be variations in the accuracy of a pollutant’s calculated concentration among different models due to the nature of the modeling environment and limitations on computational complexities. In this study two types of popular Gaussian pollution dispersion models, AERMOD and ADMS, were investigated to analyze their behavior under specific conditions. Initially, both models were simulated for point and line sources of emission. Subsequently, their output results were compared with passive samplers placed for varying periods (2 weeks, 2 months, and 3 months) at modeled receptor locations. The results indicated that both models underestimate the passive sampler results. However, AERMOD’s underestimation was found to be more than ADMS’s, resulting in ADMS performing slightly better. Additionally, to study the effectiveness of input parameters such as surface characteristics and solar insolation, a relative sensitivity analysis was conducted under two different atmospheric conditions: convective mixing dominance (CMD) and mechanical mixing dominance (MMD). It was found that AERMOD was relatively more sensitive to surface roughness, especially in MMD conditions than to albedo, surface moisture, and solar insolation. Both models were somewhat insensitive to albedo and Bowen, and solar insolation; however, in CMD conditions, AERMOD was more sensitive to these sunlight-related parameters. Also, both models were more sensitive to surface roughness than other input parameters. The results emphasize the importance of selecting precise parameters, particularly surface roughness, with more care for AERMOD than for the ADMS model. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.