Proceedings of the 2024 3rd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2024)

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Analysis of Transportation Carbon Emissions in Xinjiang Based on the Carbon Emission Factor Method for Load Weights

Authors
Wei Tian1, 2, Yanseng Gao3, Yuqi Zheng3, Na Li1, 2, Xiaomin Dai3, 4, *
1Xinjiang Jiaotou Maintenance Group Co. Ürümqi, Xinjiang, 830002, China
2Engineering Technology and Transportation Industry in Arid Desert Areas, Urumqi, Xinjiang, 830001, China
3School of Traffic and Transportation Engineering, Xinjiang University, Ürümqi, Xinjiang, 830017, China
4Xinjiang Key Laboratory of Green Construction and Maintenance of Transportation Infrastructure and Intelligent Traffic Control, Xinjiang, 830017, China
*Corresponding author. Email: xmdai@xju.edu.cn
Corresponding Author
Xiaomin Dai
Available Online 31 August 2024.
DOI
10.2991/978-94-6463-490-7_49How to use a DOI?
Keywords
Carbon emission factor method; carbon emission; load capacity
Abstract

This study analyzes the carbon emissions of trucks at the Xinjiang G30 Yandun Toll Station using the ‘Carbon Emission Factor Corresponding to Load Weight’ measurement method. The Analysis includes a comparison of emissions between different types of trucks and at different times over a year. The Analysis reveals that heavy-duty trucks are the most significant source of carbon emissions, accounting for 90% and 97% of the total number of vehicles and carbon emissions, respectively. March has the highest growth rate, while June has the highest carbon emissions. This study provides data to support the region's development of a low-carbon economy. This is important for responding to the dual-carbon policy and developing a green economy.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2024 3rd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2024)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
31 August 2024
ISBN
978-94-6463-490-7
ISSN
2589-4919
DOI
10.2991/978-94-6463-490-7_49How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Wei Tian
AU  - Yanseng Gao
AU  - Yuqi Zheng
AU  - Na Li
AU  - Xiaomin Dai
PY  - 2024
DA  - 2024/08/31
TI  - Analysis of Transportation Carbon Emissions in Xinjiang Based on the Carbon Emission Factor Method for Load Weights
BT  - Proceedings of the 2024 3rd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2024)
PB  - Atlantis Press
SP  - 445
EP  - 458
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-490-7_49
DO  - 10.2991/978-94-6463-490-7_49
ID  - Tian2024
ER  -