Volume 24 Issue 4
Aug.  2024
Turn off MathJax
Article Contents
Article Navigation >  Journal of Traffic and Transportation Engineering  > 2024  >  24(4): 104-116
Next Previous
CHEN Tao, LI Xiao-yang, CHEN Bin. Decoupling effect and peak prediction of carbon emission in transportation industry under dual-carbon target[J]. Journal of Traffic and Transportation Engineering, 2024, 24(4): 104-116. doi: 10.19818/j.cnki.1671-1637.2024.04.008
Citation: CHEN Tao, LI Xiao-yang, CHEN Bin. Decoupling effect and peak prediction of carbon emission in transportation industry under dual-carbon target[J]. Journal of Traffic and Transportation Engineering, 2024, 24(4): 104-116. doi: 10.19818/j.cnki.1671-1637.2024.04.008
shu

Decoupling effect and peak prediction of carbon emission in transportation industry under dual-carbon target

doi: 10.19818/j.cnki.1671-1637.2024.04.008
  • 1.

    School of Automobile, Chang'an University, Xi'an 710064, Shaanxi, China

  • 2.

    Institute of Transportation Development Strategy and Planning of Sichuan Province, Chengdu 610001, Sichuan, China

Funds:

National Natural Science Foundation of China 51978075

Transportation Science and Technology Project of Sichuan Province 2021-ZL-02

More Information
  • Author Bio:

    CHEN Tao(1974-), male, professor, PhD, chentao@chd.edu.cn

  • Received Date: 2024-02-20
    Available Online: 2024-09-26
  • Publish Date: 2024-08-28
    Abstract
  • To help the transportation industry achieve the strategic development goals of carbon peaking and carbon neutrality, the change trend and influencing factors of carbon emission in China's transportation industry were analyzed from two perspectives of historical verification and future prediction. The logarithmic mean Divisia index (LMDI) model was used to decompose the influencing factors of CO2 emission change in China's transportation industry from 2000 to 2020. The decoupling state of carbon emission and economic development in the industry and the driving factors of decoupling were analyzed by combining the Tapio decoupling model. The decomposition results of influencing factors were used as the basis for the selection of the indicators in the scenario analysis method, and the variations of prediction indicators under different scenarios were set. A prediction model of stochastic impacts by regression on population, affluence, and technology (STIRPAT) was constructed by using ridge regression. Analysis results show that the total CO2 emission exhibits an increasing trend year by year during the study period, with a cumulative increase of 694 million tons from 2000 to 2020. The decrease in transportation intensity is the main inhibiting factor for the increase in carbon emission, with a cumulative effect of -626 million tons. The growth of per capita GDP is the most important factor promoting the increase in carbon emission, and the cumulative effect is 1 294 million tons. The energy consumption is still dominated by fossil fuels, and the energy structure is not significantly optimized. The decoupling index of industrial carbon emission is in a stable decline stage, and the decoupling state improves, mainly manifesting in three states, such as the expansion negative decoupling, growth connection, and weak decoupling. The optimization of energy structure is the most potential factor to help the decoupling. In the future, the carbon emission in China's transportation industry will rapidly grow at first, slow down near the peak, reach a plateau for a short period after the peak, and finally decline. In the baseline, pessimistic, and optimistic scenarios, the peak CO2 emission in China's transportation industry will occur in 2040, 2045, and 2035, respectively, with peaks of about 1.210 billion, 1.263 billion, and 1.130 billion tons, respectively.

     

    • FullText(HTML)
  • loading
    • References(41)
  • [1]
    BP Amoco. BP statistical review of world energy 2022|71st edition[R]. London: BP Amoco, 2022.
    [2]
    GUO Ming-yuan, CHEN Shao-li, ZHANG Jing, et al. Environment Kuznets curve in transport sector's carbon emission: evidence from China[J]. Journal of Cleaner Production, 2022, 371: 133504. doi: 10.1016/j.jclepro.2022.133504
    [3]
    IPCC. Climate change 2022 mitigation of climate change[R]. Geneva: IPCC, 2022.
    [4]
    LI Xiao-yi, TAN Xiao-yu, WU Rui, et al. Paths for carbon peak and carbon neutrality in transport sector in China[J]. Strategic Study of CAE, 2021, 23(6): 15-21. (in Chinese)
    [5]
    LI Xiao-dong, ZHU Chen. Summary of research on account of carbon emission in building industry and analysis of its influential factors[J]. Journal of Safety and Environment, 2020, 20(1): 317-327. (in Chinese)
    [6]
    CHEN Tao, LI Xiao-yang, CHEN Bin. Decomposition of influencing factors and peak prediction of carbon emissions in China[J]. Journal of Safety and Environment, 2024, 24(1): 396-406. (in Chinese)
    [7]
    LIU Ji-yi, HUANG Fu-you, CHEN Bin. Research on influencing factors and emission reduction strategies of carbon emission in transportation industry[J]. Highway, 2023, 68(5): 252-259. (in Chinese)
    [8]
    WANG Jing-tian, MA Xiao-ming. Research progress of low-carbon transportation and its enlightenment[J]. Ecological Economy, 2021, 37(5): 57-64. (in Chinese)
    [9]
    LIU Man-zhi, ZHANG Xi-xi, ZHANG Meng-ya, et al. Influencing factors of carbon emissions in transportation industry based on C-D function and LMDI decomposition model: China as an example[J]. Environmental Impact Assessment Review, 2021, 90: 106623. doi: 10.1016/j.eiar.2021.106623
    [10]
    LU Jian-feng, FU Hui, WANG Xiao-xia. Research on the impact of regional transportation emissions efficiency factors[J]. Journal of Transportation Systems Engineering and Information Technology, 2016, 16(2): 25-30. (in Chinese)
    [11]
    DU Qiang, SUN Qiang, YANG Qi, et al. Path analysis method of driving factors of carbon emissions for Chinese transportation industry[J]. Journal of Traffic and Transportation Engineering, 2017, 17(2): 143-150. (in Chinese) https://transport.chd.edu.cn/article/id/201702016
    [12]
    SUN Hua-ping, HU Ling-xiang, GENG Yong, et al. Uncovering impact factors of carbon emissions from transportation sector: evidence from China's Yangtze River Delta Area[J]. Mitigation and Adaptation Strategies for Global Change, 2020, 25: 1423-1437. doi: 10.1007/s11027-020-09934-1
    [13]
    WANG Jing-tian, MA Xiao-ming. Influencing factors of carbon emissions from transportation in China: empirical analysis based on two-level econometrics method[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2021, 57(6): 1133-1142. (in Chinese)
    [14]
    TAPIO P. Towards a theory of decoupling: degrees of decoupling in the EU and the case of road traffic in Finland between 1970 and 2001[J]. Transport Policy, 2005, 12(2): 137-151. doi: 10.1016/j.tranpol.2005.01.001
    [15]
    LI Rong-rong, LI Le-jia, WANG Qiang. The impact of energy efficiency on carbon emissions: evidence from the transportation sector in Chinese 30 provinces[J]. Sustainable Cities and Society, 2022, 82: 103880. doi: 10.1016/j.scs.2022.103880
    [16]
    LYU Jing-ye, LI Jue. Research on the decoupling effect, driving factors and forecast of China's carbon emissions[J]. Environmental Science and Technology, 2022, 45(2): 210-220. (in Chinese)
    [17]
    PAN Xun-zhang, WANG Hai-lin, WANG Li-ning, et al. Decarbonization of China's transportation sector: in light of national mitigation toward the Paris Agreement goals[J]. Energy, 2018, 155: 853-864. doi: 10.1016/j.energy.2018.04.144
    [18]
    ZHU Xiao-ping, LI Rong-rong. An analysis of decoupling and influencing factors of carbon emissions from the transportation sector in the Beijing-Tianjin-Hebei Area, China[J]. Sustainability, 2017, 9: 722. doi: 10.3390/su9050722
    [19]
    HU Huai-min, ZUO Wei, XU Shi-yuan. Decoupling effect and driving factors of transportation energy carbon emission in Yangtze River Economic Belt[J]. Resources and Environment in the Yangtze Basin, 2022, 31(4): 862-877. (in Chinese)
    [20]
    WANG Hai-lin, OU Xun-min, ZHANG Xi-liang. Mode, technology, energy consumption, and resulting CO2 emissions in China's transport sector up to 2050[J]. Energy Policy, 2017, 109: 719-733. doi: 10.1016/j.enpol.2017.07.010
    [21]
    HUANG Zhi-hui, JI Liang, YIN Jie, et al. Peak pathway of China's road traffic carbon emissions[J]. Research of Environmental Sciences, 2022, 35(2): 385-393. (in Chinese)
    [22]
    YUAN Zhi-Yi, LI Zhen-yu, KANG Li-ping, et al. A review of low-carbon measurements and transition pathway of transport sector in China[J]. Climate Change Research, 2021, 17(1): 27-35. (in Chinese)
    [23]
    LIU Qiang, GU A-lun, TENG Fei, et al. Peaking China's CO2 emissions: trends to 2030 and mitigation potential[J]. Energies, 2017, 10(2): 209. doi: 10.3390/en10020209
    [24]
    BAUMGÄRTNER N, DEUTZ S, REINERT C, et al. Life-cycle assessment of sector-coupled national energy systems: environmental impacts of electricity, heat, and transportation in Germany till 2050[J]. Frontiers in Energy Research, 2021, 9: 621502. doi: 10.3389/fenrg.2021.621502
    [25]
    LI Xiao-Yi, WU Rui. Research on greenhouse gas emissions accounting boundaries and calculating method of the transport sector[J]. Climate Change Research, 2023, 19(1): 84-90. (in Chinese)
    [26]
    ZHU Chang-zheng, WANG Meng, YANG Ya-rong. Analysis of the influencing factors of regional carbon emissions in the Chinese transportation industry[J]. Energies, 2020, 13(5): 1100. doi: 10.3390/en13051100
    [27]
    LU Jian-feng, HAN Shuang, KANG Jia-hua. Driving factor decomposition analysis of carbon emissions for regional transportation[J]. Journal of Transportation Engineering and Information, 2016, 14(2): 56-62. (in Chinese)
    [28]
    ZHU Chang-zheng, YANG Sha, LIU Peng-bo. Study on the factors influencing on the carbon emissions of Shaanxi Province's transportation industry in China[J]. Sustainability, 2022, 14(14): 8610. doi: 10.3390/su14148610
    [29]
    LU Sheng-rong, JIANG Hui-yuan, LIU Yao. Regional disparities and influencing factors of CO2 emission in transportation industry[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(1): 32-39. (in Chinese)
    [30]
    JIANG Rui, WU Peng, WU Cheng-ke. Driving factors behind energy-related carbon emissions in the U.S. road transport sector: a decomposition analysis[J]. International Journal of Environmental Research and Public Health, 2022, 19: 2321. doi: 10.3390/ijerph19042321
    [31]
    LI Lin-na. Structure and influencing factors of CO2 emissions from transport sector in three major metropolitan regions of China: estimation and decomposition[J]. Transportation, 2019, 46: 1245-1269. doi: 10.1007/s11116-017-9827-6
    [32]
    ZHANG Hong-jun, WANG Li-ning, CHEN Wen-ying. Decomposition analysis of CO2 emissions from road and rail transport systems[J]. Journal of Tsinghua University (Science and Technology), 2017, 57(4): 443-448. (in Chinese)
    [33]
    YANG Shao-hua, ZHANG Yu-quan, GENG Yong. An LMDI-based investigation of the changes in carbon emissions of the transportation sector in the Yangtze River Economic Belt[J]. China Environmental Science, 2022, 42(10): 4817-4826. (in Chinese)
    [34]
    YU Jie, DA Ya-bin, OUYANG Bin. Analysis of carbon emission changes in China's transportation industry based on LMDI decomposition method[J]. China Journal of Highway and Transport, 2015, 28(10): 112-119. (in Chinese)
    [35]
    YU Ya-dong, ZHOU Li, ZHOU Wen-ji, et al. Decoupling environmental pressure from economic growth on city level: the case study of Chongqing in China[J]. Ecological Indicators, 2017, 75: 27-35. doi: 10.1016/j.ecolind.2016.12.027
    [36]
    CHEN Wei-gong, YAN Sheng-hua. The decoupling relationship between CO2 emissions and economic growth in the Chinese mining industry under the context of carbon neutrality[J]. Journal of Cleaner Production, 2022, 379(1): 134692.
    [37]
    JIANG Ke-jun, HE Chen-min, ZHU Song-li, et al. Transport scenarios for China and the role of electric vehicles under global 2 ℃/1.5 ℃ targets[J]. Energy Economics, 2021, 103: 105172. doi: 10.1016/j.eneco.2021.105172
    [38]
    LIU Wei, CHEN Yan-bin. Economic development between the two centenary goals: tasks, challenges and strategies[J]. Social Sciences in China, 2021(3): 86-102. (in Chinese)
    [39]
    LIU Jian-guo, ZHU Yue-zhong, TIAN Zhi-yu. Research on path of Chinese transportation decarbonization under carbon neutralization goal[J]. Energy of China, 2021, 43(5): 6-12. (in Chinese)
    [40]
    LIU Jian-guo, ZHU Yue-zhong, JI Shi-yu. Path selection of "de-oiling" of Chinese transportation industry under double carbon goal[J]. China Economic and Trade Herald, 2021(17): 38-40. (in Chinese)
    [41]
    PAN Chong-chao, WANG Bo-wen, HOU Xiao-wang, et al. Carbon peak path of the Chinese iron and steel industry based on the LMDI-STIRPAT model[J]. Chinese Journal of Engineering, 2023, 45(6): 1034-1044. (in Chinese)
    • Relative Articles
    • Supplements(0)
    • Cited By

Catalog

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (533) PDF downloads(54) Cited by()
    Related

    Copyright《Journal of Traffic and Transportation Engineering》编辑部陕ICP备05001904号-1

    Address ：Editorial Department of Journal of Traffic and Transportation Engineering, Chang 'an University, Middle Section of South Second Ring Road, Xi 'an, Shaanxi（710064） Tel：029-82334388 Email：jygc@chd.edu.cn

    All visit:Today's visit:

    Supported by: Beijing Renhe Information Technology Co. Ltd    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return