AUTHOR=Demirarslan Kazım O. 

TITLE=Effects of topographic variables on traffic-related pollutant concentrations: comparison of AERMOD and CAL3QHCR models

JOURNAL=Frontiers in Environmental Science

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2025.1577330

DOI=10.3389/fenvs.2025.1577330

ISSN=2296-665X

ABSTRACT=IntroductionThis study examines the spatial dispersion of traffic-related pollutants (CO, NOx, and PM10) along a major highway corridor that connects the Eastern Black Sea Region with northern Türkiye. The primary objective is to compare the performance of two atmospheric dispersion models—AERMOD and CAL3QHCR—and to evaluate how topographic variables influence their outputs.MethodsDispersion simulations were performed using AERMOD and CAL3QHCR under identical meteorological and traffic input scenarios. Model predictions were compared using Spearman’s rank correlation coefficient and validated against observational data from ten air quality monitoring stations. Fractional Bias (FB) and Normalized Mean Square Error (NMSE) were employed as statistical performance metrics.ResultsBoth models estimated higher pollutant concentrations near highways, but AERMOD consistently predicted higher maximum values (CO: 0.78 ppm; NOx: 1.48 ppm; PM10: 26.59 μg/m3). CAL3QHCR produced lower estimates (CO: 0.20 ppm; NOx: 0.09 ppm; PM10: 2.70 μg/m3), yet it showed better agreement with observed CO and NOx concentrations. Correlation analysis indicated strong negative correlations between pollutant levels and elevation (e.g., CO: r = −0.87). Both models captured the spatial decline in concentrations with increasing distance from the road, particularly within the first kilometer.DiscussionAERMOD was found to overpredict pollutant concentrations, while CAL3QHCR yielded closer estimates for CO and NOx. However, both models exhibited poor performance in simulating PM10, as indicated by high NMSE values and consistent underestimation. These findings highlight the significance of topography in dispersion modeling and the necessity of model calibration for PM-based assessments.