Dynamic Modeling of Urban Passenger Car Emissions in Metropolitan Tehran Based on VSP and the IVE Model

Document Type : Original Research Paper

Authors

Environmental Engineering Department, Shahid Beheshti University, Tehran, Iran

10.22059/poll.2025.395271.2934

Abstract

Urban air pollution caused by light-duty passenger vehicles poses critical environmental and public health challenges in megacities like Tehran. In this study, we dynamically estimated vehicular emissions by collecting second-by-second speed and acceleration data from 16 representative routes, including 2 residential, 8 urban, and 6 highway segments, across metropolitan Tehran. We integrated the Vehicle Specific Power (VSP) method with the International Vehicle Emissions (IVE) model to assess real-time emission patterns across four time intervals (08:00, 12:00, 16:00, and 23:00). Our measurements showed that average speeds ranged from 14.0 to 25.97 km/h in residential areas, 10.62 to 42.13 km/h in urban corridors, and 16.43 to 67.15 km/h on highways. We found that VSP values predominantly fell within bins 8–14, reflecting acceleration-intensive and stop-and-go traffic during peak hours. We estimated emissions per kilometer as follows: CO (0.47–0.57 g), NOₓ (0.11–0.23 g), CO₂ (240.7–411.5 g), VOC (0.13–0.19 g), and NMVOC (0.12–0.18 g). During peak hours, emissions increased by 40–50% compared to off-peak periods, correlating with VSP clustering around bins 8–10, while smoother traffic conditions (VSP ≥12) during off-peak hours reduced emissions. This study is among the first in the region to combine second-by-second VSP profiles with the IVE model to produce high-resolution, time-resolved urban emission estimates. Our findings highlight how dynamic traffic modeling can help policymakers design smart traffic signal systems, manage congestion, and improve air quality policies tailored to real-time conditions in megacities. 

Keywords

Main Subjects


Alipourmohajer, S., Rashidi, Y. and Atabi, F. (2019). Verification of IVE Model for SAIPA Co. Fleet Emission. Pollution, 5(2); 235-245.
Atuyambe, L.M., Arku, R.E., Naidoo, N., Kapwata, T., Asante, K.P., Cissé, G., Simane, B., Wright, C.Y. and Berhane, K. (2024). The health impacts of air pollution in the context of changing climate in Africa: A narrative review with recommendations for action. Ann. Glob. Health, 90(1); 76.
Avenue in Panama City, Panama. (2024). E3S Web of Conferences (ICFEE 2024).
Azevedo, J.A.H., Cassiano, D.R. and Bertoncini, B.V. (2024). Real driving cycles and emissions for urban freight transport. Front. Big Data, 7; 1375455.
Chaudhry, S.K. and Elumalai, S.P. (2024). Assessment of sustainable school transport policies on vehicular emissions using the IVE model. J. Clean. Prod., 434; 140437.
Coelho, M.C., Frey, H.C., Rouphail, N.M., Zhai, H. and Pelkmans, L. (2009). Assessing methods for comparing emissions from gasoline and diesel light-duty vehicles based on instantaneous emissions data. Sci. Total Environ., 408(2); 336–345.
Coelho, M.C., Frey, H.C., Rouphail, N.M., Zhai, H. and Pelkmans, L. (2009). Assessing methods for comparing emissions from gasoline and diesel light-duty vehicles based on microscale measurements. Transp. Res. Part D, 14(2); 91–99.
Davison, J., Rose, R.A., Farren, N.J., Wagner, R.L., Murrells, T.P. and Carslaw, D.C. (2021). Verification of a national emission inventory and influence of on-road vehicle manufacturer-level emissions. Environ. Sci. Technol., 55(8); 4452–4461.
Demetriou, E. and Hadjistassou, C. (2022). Lowering mortality risks in urban areas by containing atmospheric pollution. Environ. Res., 211; 113096.
Development and Application of IVE (Part 3: Developing Countries Team) (2024). E3S Web of Conferences.
Fernandes, P., Bandeira, J., Silva, C.M. and Coelho, M.C. (2021). Comparison of models to predict NOₓ and CO₂ emissions based on real-world driving parameters. Sci. Total Environ., 765; 144391.
Frey, H.C. et al. (2022). Characterizing determinants of near-road ambient air quality for an urban intersection and a freeway site. Health Effects Inst. Res. Rep., 207; 1–73.
Ghaffarpasand, O., Alipourmohajer, M. and Rashidi, Y. (2021). Evaluation of VSP-based driving behavior on emission estimates using the IVE model.
Hao, J., Yang, Z., Zhang, R., Ma, Z., Liu, J., Bi, H. and Guo, D. (2024). Crosstalk between heredity and environment in myopia: An overview. Heliyon, 10(8); e29715.
Jiang, Z., Wu, L., Niu, H., Jia, Z., Qi, Z., Liu, Y., Zhang, Q., Wang, T., Peng, J. and Mao, H. (2024). Investigating the impact of high-altitude on vehicle carbon emissions: A comprehensive on-road driving study. Sci. Total Environ., 918; 170671.
Jiménez-Palacios, L. (1999). Vehicle specific power: A useful parameter for remote sensing and emission studies. 9th CRC On-Road Vehicle Emissions Workshop, San Diego, USA.
Khazini, L., Jamshidi Kaljahi, M. and Blond, N. (2019). Investigation of emission levels and dispersion patterns of pollutants from vehicles in Tabriz city. Civ. Environ. Eng. J., 49(96); 23–34.
Liu, H., Guensler, R., Lu, H., Xu, Y., Xu, X. and Rodgers, M.O. (2019). MOVES-Matrix for high-performance on-road energy and running emission rate modeling applications. J. Air Waste Manag. Assoc., 69(12); 1415–1428.
Müller, T., Schneider, A. and Braun, M. (2025). Integration of real-time floating car data with COPERT 5.6 for dynamic urban emission modeling in Germany. Environ. Sci. Technol., 59(2); 1456–1472.
Saberiyansani, M., Rashidi, Y. and Hashemi, S.H. (2024). Comparison of the real emissions of domestic passenger cars with the IVE model. Environ. Sci., 22(1); 39–52.
Saberiyansani, M., Rashidi, Y. and Hashemi, S.H. (2025). Comparative analysis of COPERT and IVE models in road transport emission assessment. Sustain. Earth Trends, 5(3); 25–35.
Saud, B. and Paudel, G. (2018). The threat of ambient air pollution in Kathmandu, Nepal. J. Environ. Public Health, 2018; 1504591.
Sikder, M., Wang, C., Yao, X., Huai, X., Wu, L., KwameYeboah, F., Wood, J., Zhao, Y. and Dou, X. (2022). The integrated impact of GDP growth, industrialization, energy use, and urbanization on CO₂ emissions in developing countries: Evidence from the panel ARDL approach. Sci. Total Environ., 837; 155795.
Singh, A., Sharma, P. and Kaur, G. (2023). Assessment of vehicular emissions in New Delhi using real-world VSP-based analysis. Transp. Res. Part D, 115; 103565.
Szopińska, K. et al. (2022). Verification of the perception of the local community concerning air quality using ADMS-Roads modeling. Int. J. Environ. Res. Public Health, 19(17); 10908.
The IVE Model. (n.d.). International Vehicle Emissions Model.
United States Environmental Protection Agency (USEPA). (2002). Comprehensive Modal Emission Model (CMEM) User’s Guide (EPA420-R-02-007). Office of Transportation and Air Quality.
Valdes-Montenegro, A., Gonzalez-Olivardia, F., Thepanondh, S. and Pinzón-Acosta, C. (2024). Estimation of on-road mobile emissions based on the vehicle technology in a high-traffic avenue in Panama City, Panama. E3S Web Conf., 530; 01003.
Valdes-Montenegro, D., Gómez, R. and Ortega, M. (2024). Adapting the IVE model for emission estimates in Panama City. Urban Clim., 49; 101770.
Viteri, M., Guevara, M. and Espinosa, L. (2023). Evaluation of truck-related CO hotspots using the IVE model in Quito, Ecuador. Environ. Monit. Assess., 195(3); 243.
Viteri, R., Borge, R., Paredes, M. and Pérez, M.A. (2023). A high-resolution vehicular emissions inventory for Ecuador using the IVE modelling system. Chemosphere, 315; 137634.
Wiston, M. (2017). Status of air pollution in Botswana and significance to air quality and human health. J. Health Pollut., 7(15); 8–17.
Zhang, L., Huang, Y. and Wu, Q. (2025). Spatiotemporal vehicle emission prediction in megacities using hybrid IVE-LSTM models: A case study of Shanghai. Atmos. Environ., 312; 119921.
Zhong, H., Chen, K., Liu, C., Zhu, M. and Ke, R. (2024). Models for predicting vehicle emissions: A comprehensive review. Sci. Total Environ., 923; 171324.
Zhou, Y., Li, H. and Zhang, Y. (2022). Dynamic emission modeling based on driving patterns in Shanghai. J. Environ. Sci., 112; 245–253.