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

Yu Liu, Wenwen Jiang, Xiaoqiang Zhang, Tsehaye Adamu Andualem, Ping Wang () and Ying Liu ()
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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

Sustainability, 2025, vol. 17, issue 17, 1-20

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.

Keywords: emission factors; on-road measurement; Shanghai; CO 2; traffic emissions (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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