Predictive Modeling of Traffic-Related Air Pollution in Urban Areas: Insights from Road Mid-Block Sections

Document Type : Original Research Paper

Authors

1 Department of Civil Engineering, Marri Laxman Reddy Institute of Technology and Management, Hyderabad-500043, India

2 Department of Civil Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India

10.22059/poll.2025.396065.2951

Abstract

Roads and highways are vital to a nation's economic and social development. However, the surge in transportation demand has led to heightened vehicular emissions, particularly at urban mid-block sections. This study presents predictive models for estimating pollutant concentrations of CO, HCHO, TVOCs, PM₂.₅, and PM10 a Green House Gas (GHG) CO2 based on traffic flow and vehicle type data collected across 18 urban mid-blocks in Warangal, Tirupati, and Vijayawada. Three models such as MLR, SVR, and ANN were developed, with ANN achieving the highest performance (R² > 0.90 for all pollutants). Peak concentrations of CO (1180 ppm) and PM₂.₅ (over 100 µg/m³) were observed during evening hours (7–8 PM), coinciding with traffic volumes exceeding 4000 PCU/hr. A strong correlation (R² > 0.7) between traffic volume and pollutant levels was confirmed across all models. These findings provide actionable insights for urban transport planners to forecast and mitigate traffic-related air pollution at mid-block sections in similar urban environments.

Keywords

Main Subjects

References

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Pollution
Volume 11, Issue 4
October 2025
Pages 1473-1488

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