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Model Development for the Real-World Emission Factor Measurement of On-Road Vehicles Under Heterogeneous Traffic Conditions: An Empirical Analysis in Shanghai

Author

Listed:
  • Yu Liu

    (State Key Laboratory of Water Pollution Control and Green Resource Recycling, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China)

  • Wenwen Jiang

    (The Key Laboratory of Road and Traffic Engineering, Ministry of Education, College of Transportation, Tongji University, Shanghai 201804, China)

  • Xiaoqiang Zhang

    (State Key Laboratory of Water Pollution Control and Green Resource Recycling, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China)

  • Tsehaye Adamu Andualem

    (State Key Laboratory of Water Pollution Control and Green Resource Recycling, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China)

  • Ping Wang

    (The Key Laboratory of Road and Traffic Engineering, Ministry of Education, College of Transportation, Tongji University, Shanghai 201804, China)

  • Ying Liu

    (State Key Laboratory of Water Pollution Control and Green Resource Recycling, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China)

Abstract

Global warming is attributed to anthropogenic emissions of CO 2 and the contribution from the transport sector is significant. Estimating on-road vehicle CO 2 emission factors is essential for guiding carbon-reduction efforts in transportation. In order to accurately calculate carbon emission factors from vehicles, this study built a multi-scenario model for open, semi-enclosed, and enclosed road environments based on Fick’s second law and the law of conservation of mass. During the model optimization phase, it was found that the model’s applicability domain effectively encompassed most urban roadway scenarios, making it suitable for estimating urban traffic CO 2 emissions. The spatiotemporal heterogeneity analysis of field measurements indicated that this method can effectively distinguish variations in CO 2 emission factors across different road types and time periods. The method proposed in this study offers an effective solution for the real-time monitoring of large-scale on-road vehicle carbon emissions.

Suggested Citation

  • Yu Liu & Wenwen Jiang & Xiaoqiang Zhang & Tsehaye Adamu Andualem & Ping Wang & Ying Liu, 2025. "Model Development for the Real-World Emission Factor Measurement of On-Road Vehicles Under Heterogeneous Traffic Conditions: An Empirical Analysis in Shanghai," Sustainability, MDPI, vol. 17(17), pages 1-20, September.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:17:p:8014-:d:1743252
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    References listed on IDEAS

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    1. Ying Chen & Zhigang Du & Fangtong Jiao & Shuyang Zhang, 2022. "Optimal Speed Model of Urban Underwater Tunnel Based on CO 2 Emissions Factor," Sustainability, MDPI, vol. 14(15), pages 1-16, August.
    2. Xiaojian Hu & Nuo Chen & Nan Wu & Bicheng Yin, 2021. "The Potential Impacts of Electric Vehicles on Urban Air Quality in Shanghai City," Sustainability, MDPI, vol. 13(2), pages 1-12, January.
    3. Tsiakmakis, Stefanos & Fontaras, Georgios & Ciuffo, Biagio & Samaras, Zissis, 2017. "A simulation-based methodology for quantifying European passenger car fleet CO2 emissions," Applied Energy, Elsevier, vol. 199(C), pages 447-465.
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