Research on the Influencing Factors and Decoupling State of Carbon Emissions in China’s Transportation Industry
Abstract
:1. Introduction
2. Literature Review
3. Materials and Methods
3.1. CO2 Emission Measurement
3.2. Decomposition Model of CO2 Emission Influencing Factors
3.2.1. C-D Production Function
3.2.2. LMDI Model Based on the C-D Production Function
- represents the carbon emission intensity of the i-th energy in year t.
- represents the proportion of the i-th energy consumption in year t.
- represents the unit consumption level of transportation (energy consumption per unit of turnover).
- represents transportation intensity.
- At represents the level of technology in year t, Kt represents the capital input in year t and Lt represents the labor input in year t, respectively.
3.3. Decoupling Model for CO2 Emissions
3.4. Data Source
4. Results
4.1. Results of CO2 Emission Changes
4.2. Decomposition Results of Influencing Factors
4.3. Results of the Decoupling Effect Analysis
5. Discussion
6. Conclusions and Suggestions
6.1. Conclusions
6.2. Suggestions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Net Zero by 2050—A Roadmap for the Global Energy Sector. Available online: iea.blob.core.windows.net/assets/deebef5d-0c34-4539-9d0c-10b13d840027/NetZeroby2050-ARoadmapfortheGlobalEnergySector_CORR.pdf (accessed on 22 March 2023).
- Birol, D.F. World Energy Outlook 2022. Available online: iea.blob.core.windows.net/assets/830fe099-5530-48f2-a7c1-11f35d510983/WorldEnergyOutlook2022.pdf (accessed on 22 March 2023).
- Progress on the Implementation of China’s Nationally Determined Contributions. 2022. Available online: https://unfccc.int/sites/default/files/NDC/2022-11/Progress%20of%20China%20NDC%202022.pdf (accessed on 22 March 2023).
- Xu, H.C.; Li, Y.L.; Zheng, Y.J.; Xu, X.B. Analysis of spatial associations in the energy-carbon emission efficiency of the transportation industry and its influencing factors: Evidence from China. Environ. Impact Assess. Rev. 2022, 97, 106905. [Google Scholar]
- Li, R.R.; Li, L.J.; Wang, Q. The impact of energy efficiency on carbon emissions: Evidence from the transportation sector in Chinese 30 provinces. Sust. Cities Soc. 2022, 82, 103880. [Google Scholar]
- Vivien, F.R.; Céline, G. Transportation infrastructures in a low carbon world: An evaluation of investment needs and their determinants. Transport. Res. Part D Transport Environ. 2019, 17, 203–219. [Google Scholar]
- Dong, F.; Hua, Y.F.; Yu, B.L. Peak Carbon Emissions in China: Status, Key Factors and Countermeasures—A Literature Review. Sustainability 2018, 10, 2895. [Google Scholar]
- Wang, C.; Cai, W.J.; Lu, X.D.; Chen, J.N. CO2 mitigation scenarios in China’s road transport sector. Energy Conv. Manag. 2007, 48, 2110–2118. [Google Scholar] [CrossRef]
- Zhu, C.Z.; Wang, M.; Yang, Y.R. Analysis of the Influencing Factors of Regional Carbon Emissions in the Chinese Transportation Industry. Energies 2020, 13, 1100. [Google Scholar]
- Su, K.; Lee, C.M. When will China achieve its carbon emission peak? A scenario analysis based on optimal control and the STIRPAT model. Ecol. Indic. 2020, 112, 106138. [Google Scholar]
- Mi, Z.F.; Wei, Y.M.; Wang, B.; Meng, J.; Liu, Z.; Shan, Y.L.; Liu, J.R.; Guan, D.B. Socioeconomic impact assessment of China’s CO2 emissions peak prior to 2030. J. Clean. Prod. 2017, 142, 2227–2236. [Google Scholar]
- Xu, X.B.; Xu, H.C. The Driving Factors of Carbon Emissions in China’s Transportation Sector: A Spatial Analysis. Front. Energy Res. 2021, 9, 664046. [Google Scholar]
- Ma, X.J.; Fan, Y.J.; Shi, F.; Song, Y.Q.; He, Y. Research on the relation of Economy-Energy-Emission (3E) system: Evidence from heterogeneous energy in China. Environ. Sci. Pollut. Res. 2022, 29, 62592–62610. [Google Scholar]
- Guo, M.Y.; Meng, J. Exploring the driving factors of carbon dioxide emission from transport sector in Beijing-Tianjin-Hebei region. J. Clean. Prod. 2019, 226, 692–705. [Google Scholar]
- Wang, S.J.; Liu, X.P.; Zhou, C.S.; Hu, J.C.; Ou, J.P. Examining the impacts of socioeconomic factors, urban form, and transportation networks on CO2 emissions in China’s megacities. Appl. Energy 2017, 185, 189–200. [Google Scholar]
- Zhu, C.Z.; Yang, S.; Liu, P.B. Study on the Factors Influencing on the Carbon Emissions of Shaanxi Province’s Transportation Industry in China. Sustainability 2022, 14, 8610. [Google Scholar]
- Li, L. Structure and influencing factors of CO2 emissions from transport sector in three major metropolitan regions of China: Estimation and decomposition. Transportation 2019, 46, 1245–1269. [Google Scholar] [CrossRef]
- Jing, Q.L.; Liu, H.Z.; Yu, W.Q.; He, X. The impact of public transportation on carbon emissions—From the perspective of energy consumption. Sustainability 2022, 14, 6248. [Google Scholar] [CrossRef]
- Liu, Q.; Gu, A.L.; Teng, F.; Song, R.P.; Chen, Y. Peaking China’s CO2 Emissions: T rends to 2030 and Mitigation Potential. Energies 2017, 10, 209. [Google Scholar] [CrossRef]
- Sun, H.P.; Hu, L.X.; Geng, Y.; Yang, G.C. Uncovering impact factors of carbon emissions from transportation sector: Evidence from China’s Yangtze River Delta Area. Mitig. Adapt. Strateg. Glob. Chang. 2020, 25, 1423–1437. [Google Scholar] [CrossRef]
- Lin, B.Q.; Nelson, I.B. Influencing factors on carbon emissions in China transport industry. A new evidence from quantile regression analysis. J. Clean. Prod. 2017, 150, 175–187. [Google Scholar]
- Yu, Y.; Dai, Y.Q.; Xu, L.Y.; Zheng, H.Z.; Wu, W.H.; Chen, L. A multi-level characteristic analysis of urban agglomeration energy-related carbon emission: A case study of the Pearl River Delta. Energy 2023, 263, 125651. [Google Scholar] [CrossRef]
- Du, K.R.; Xie, C.P.; Ouyang, X.L. A comparison of carbon dioxide (CO2) emission trends among provinces in China. Renew. Sustain. Energ. Rev. 2017, 73, 19–25. [Google Scholar]
- Petri, T. Towards a theory of decoupling: Degrees of decoupling in the EU and the case of road traffic in Finland between 1970 and 2001. Transp. Policy 2005, 12, 137–151. [Google Scholar]
- Wang, Q.; Jiang, R. Is China’s economic growth decoupled from carbon emissions? J. Clean. Prod. 2019, 225, 1194–1208. [Google Scholar]
- Xie, P.J.; Gong, N.Y.; Sun, F.H.; Li, P.; Pan, X.Y. What factors contribute to the extent of decoupling economic growth and energy carbon emissions in China? Energy Policy 2023, 173, 113416. [Google Scholar]
- Pan, X.Z.; Wang, H.L.; Wang, L.N.; Chen, W.Y. Decarbonization of China’s transportation sector: In light of national mitigation toward the Paris Agreement goals. Energy 2018, 155, 853–864. [Google Scholar]
- Zhu, X.P.; Li, R.R. An analysis of decoupling and influencing factors of carbon emissions from the transportation sector in the Beijing-Tianjin-Hebei area, China. Sustainability 2017, 9, 722. [Google Scholar]
- Liu, M.Z.; Zhang, X.X.; Zhang, M.Y.; Feng, Y.Q.; Liu, Y.J.; Wen, J.X.; Liu, L.Y. Influencing factors of carbon emissions in transportation industry based on C–D function and LMDI decomposition model: China as an example. Environ. Impact Assess. Rev. 2021, 90, 106623. [Google Scholar]
- Lu, Q.Y.; Chai, J.; Wang, S.Y.; Zhang, Z.G.; Sun, X.J.C. Potential energy conservation and CO2 emissions reduction related to China’s road transportation. J. Clean. Prod. 2020, 245, 118892. [Google Scholar]
- Lin, D.T.; Zhang, L.Y.; Chen, C.; Lin, Y.Y.; Wang, J.K.; Qiu, R.Z.; Hu, X.S. Clean Technologies and Environmental Policy. Clean Technol. Environ. Policy 2019, 21, 1307–1322. [Google Scholar]
- Cai, J.; Ma, S.Y.; Ji, H.M.; Jiang, W.Y.; Bai, Z.R. Spatial–temporal characteristics and decoupling effects of China’s transportation CO2 emissions. Environ. Sci. Pollut. Res. 2022, 30, 32614–32627. [Google Scholar]
- Zhang, L.L.; Long, R.Y.; Chen, H.; Geng, J.C. A review of China’s road traffic carbon emission. J. Clean. Prod. 2019, 207, 569–581. [Google Scholar]
- Zhang, X.; Zhao, X.R.; Jiang, Z.J.; Shao, S. How to achieve the 2030 CO2 emission-reduction targets for China’s industrial sector: Retrospective decomposition and prospective trajectories. Glob. Environ. Chang. 2017, 44, 83–97. [Google Scholar]
- Wang, Q.; Li, R.R. Journey to burning half of global coal: Trajectory and drivers of China’s coal use. Renew. Sustain. Energ. Rev. 2016, 58, 341–346. [Google Scholar]
- Du, Y.; Liu, Y.; Hossain, M.A.; Chen, S. The decoupling relationship between China’s economic growth and carbon emissions from the perspective of industrial structure. Chin. J. Popul. Resour. Environ. 2022, 20, 49–58. [Google Scholar]
- Chen, W.G.; Yan, S.H. The decoupling relationship between CO2 emissions and economic growth in the Chinese mining industry under the context of carbon neutrality. J. Clean. Prod. 2022, 379, 134692. [Google Scholar]
- Ou, X.M.; Yuan, Z.Y. Development Paths for China’s Transport Sector under the Carbon Neutrality Goal. Chin. J. Urban. Env. Stu. 2022, 10, 2250010. [Google Scholar] [CrossRef]
- Jiang, X.T.; Su, M.; Li, R.R. Investigating the Factors Influencing the Decoupling of Transport-Related Carbon Emissions from Turnover Volume in China. Sustainability 2018, 10, 3034. [Google Scholar] [CrossRef] [Green Version]
- Lin, B.Q.; Xie, C.P. Reduction potential of CO2 emissions in China’s transport industry. Renew. Sustain. Energ. Rev. 2014, 33, 689–700. [Google Scholar] [CrossRef]
- Wang, W.J.; Wang, J.X. Determinants investigation and peak prediction of CO2 emissions in China’s transport sector utilizing bio-inspired extreme learning machine. Environ. Sci. Pollut. Res. 2021, 28, 55535–55553. [Google Scholar]
- Jiang, R.; Zhou, Y.L.; Li, R.R. Moving to a Low-Carbon Economy in China: Decoupling and Decomposition Analysis of Emission and Economy from a Sector Perspective. Sustainability 2018, 10, 978. [Google Scholar] [CrossRef] [Green Version]
- Xiong, S.Q.; Yuan, Y.; Zhang, C.L. Achievement of carbon peak goals in China’s road transport—Possibilities and pathways. J. Clean. Prod. 2023, 388, 135894. [Google Scholar]
- Aqib, Z.; Faryal, M.; Mao, G.Z.; Yu, Y.J.; András, S. The carbon neutrality feasibility of worldwide and in China’s transportation sector by E-car and renewable energy sources before 2060. J. Energy Storage 2023, 61, 106696. [Google Scholar]
- Jiang, R.; Wu, P.; Wu, C.K. Driving Factors behind Energy-Related Carbon Emissions in the U.S. Road Transport Sector: A Decomposition Analysis. Int. J. Environ. Res. Public Health 2022, 19, 2321. [Google Scholar] [CrossRef] [PubMed]
- Li, Y.; Du, Q.; Lu, X.R.; Wu, J.; Han, X. Relationship between the development and CO2 emissions of transport sector in China. Transport. Res. Part D Transport Environ. 2019, 74, 1–14. [Google Scholar]
- Guo, M.Y.; Chen, S.L.; Zhang, J.; Meng, J. Environment Kuznets Curve in transport sector’s carbon emission: Evidence from China. J. Clean. Prod. 2022, 371, 133504. [Google Scholar]
- Wang, H.L.; Ou, X.M.; Zhang, X.L. Mode, technology, energy consumption, and resulting CO2 emissions in China’s transport sector up to 2050. Energy Policy 2017, 109, 719–733. [Google Scholar] [CrossRef]
- Liu, M.Z.; Wang, J.F.; Wen, J.X.; He, G.; Wu, J.X.; Chen, H.Y.; Yang, X.T. Carbon Emission and Structure Analysis of Transport Industry Based on Input-output Method: China as an Example. Sustain. Prod. Consump. 2022, 33, 168–188. [Google Scholar]
- Li, R.; Sun, T. Research on Measurement of Regional Differences and Decomposition of Influencing Factors of Carbon Emissions of China’s Logistics Industry. Pol. J. Environ. Stud. 2021, 30, 3137–3150. [Google Scholar]
- Tobias, H.; Hendrik, S. Decarbonizing Transport in the European Union: Emission Performance Standards and the Perspectives for a European Green Deal. Sustainability 2020, 12, 8381. [Google Scholar]
Carbon Emissions from the Transportation Industry | Increase in Carbon Emissions from 1990 to 2019 | |||
---|---|---|---|---|
Emission (Million t) | Proportion of World Transportation Carbon Emissions | Proportion of the Country’s Total Carbon Emissions | ||
China | 1233 | 15.00% | 12.43% | 819% |
USA | 1757 | 21.37% | 37.03% | 23% |
Japan | 201 | 2.44% | 19.00% | −5% |
EU | 932 | 11.34% | 31.14% | 23% |
Germany | 160 | 1.95% | 19.63% | 1% |
France | 126 | 1.53% | 42.71% | 12% |
UK | 118 | 1.44% | 34.40% | 3% |
Sweden | 16 | 0.19% | 48.48% | −20% |
Decoupling Classification | Decoupling State | ∆C | ∆GDP | Meaning | |
---|---|---|---|---|---|
Decoupling | Strong decoupling | <0 | >0 | < 0 | The economy is growing, but carbon emissions are falling |
Weak decoupling | >0 | >0 | 0 ≤ < 0.8 | The economy is growing faster than carbon emissions | |
Recessive decoupling | <0 | <0 | > 1.2 | The rate of economic decline is less than the rate of reduction in carbon emissions | |
Coupling | Expansive coupling | >0 | >0 | 0.8 ≤ ≤ 1.2 | Economic growth is increasing at the same rate as carbon emissions |
Recessive coupling | <0 | <0 | 0.8 ≤ ≤ 1.2 | Economic recession and carbon emissions decrease at comparable rates | |
Negative decoupling | Expansive negative decoupling | >0 | >0 | > 1.2 | The rate of economic growth is less than the rate of increase in carbon emissions |
Weak negative decoupling | <0 | <0 | 0 ≤ < 0.8 | Economic recession is faster than carbon emission reduction | |
Strong negative decoupling | >0 | <0 | < 0 | Economic recession and increased carbon emissions |
Year | ∆Ces | ∆Cet | ∆Ctg | ∆At | ∆Kt | ∆Lt | ∆C |
---|---|---|---|---|---|---|---|
2000–2001 | 140.71 | −305.76 | −1002.08 | 729.91 | 2748.67 | −555.09 | 890.87 |
2001–2002 | −393.01 | −990.52 | −773.74 | −535.93 | 3252.35 | −286.31 | 1481.13 |
2002–2003 | 1022.94 | −2298.22 | −103.69 | −7143.89 | 3768.52 | 5073.47 | 4862.48 |
2003–2004 | −699.98 | −2238.93 | 3072.66 | −477.66 | 6500.45 | −146.13 | 5512.78 |
2004–2005 | −1179.05 | −3581.49 | 40.04 | 167.00 | 5676.68 | −222.58 | 4176.33 |
2005–2006 | 75.10 | −2189.66 | −1460.81 | 1590.06 | 4383.63 | 22.39 | 3619.84 |
2006–2007 | 458.64 | −1893.94 | −2516.76 | 6867.89 | 1802.55 | 131.89 | 4446.00 |
2007–2008 | −277.07 | 681.21 | −1604.65 | 3366.48 | 2587.49 | −10.05 | 1823.28 |
2008–2009 | 364.87 | 7398.49 | 4702.64 | −12,028.78 | 11,243.71 | 1295.02 | 1995.98 |
2009–2010 | 437.61 | −3032.30 | 1074.71 | 480.27 | 7131.55 | −103.43 | 6831.04 |
2010–2011 | 901.26 | 5684.21 | −2348.18 | 4657.40 | 4218.30 | 959.07 | 6493.91 |
2011–2012 | −791.16 | −1595.12 | −57.63 | 5777.47 | 170.11 | 71.40 | 5851.40 |
2012–2013 | 215.79 | −579.63 | −9438.08 | −1934.24 | 3739.03 | 5242.47 | 5223.45 |
2013–2014 | −367.53 | −676.08 | −1202.92 | 1176.24 | 5802.62 | 416.54 | 2792.64 |
2014–2015 | −541.87 | 1689.20 | −6787.85 | 1633.68 | 4237.01 | −196.57 | 4028.61 |
2015–2016 | 868.48 | −3939.74 | −2956.53 | 2234.98 | 4820.42 | −100.58 | 3271.65 |
2016–2017 | 1180.41 | −9313.22 | −5590.56 | 944.75 | 10,026.26 | −159.42 | 5821.81 |
2017–2018 | 1640.37 | −305.76 | −4490.04 | 9955.88 | 634.47 | −2469.00 | 4595.61 |
2018–2019 | 1210.02 | −990.52 | −7327.35 | 5151.07 | 307.28 | −294.54 | 735.68 |
2019–2020 | 1026.10 | −2298.22 | 2287.12 | −11,149.10 | 6927.11 | −234.66 | −5083.17 |
Cumulative | 5292.64 | −9313.22 | −36,483.71 | 11,463.49 | 89,978.23 | 8433.89 | 69,371.32 |
Year | t1 | t2 | t3 | t4 | t5 | t6 | T |
---|---|---|---|---|---|---|---|
2000–2001 | 0.046 | −0.386 | −0.330 | 0.240 | 0.905 | −0.183 | 0.293 |
2001–2002 | −0.159 | 0.088 | −0.313 | −0.217 | 1.315 | −0.116 | 0.599 |
2002–2003 | 0.634 | 1.391 | −0.064 | −4.427 | 2.335 | 3.144 | 3.013 |
2003–2004 | −0.118 | −0.463 | 0.520 | −0.081 | 1.100 | −0.025 | 0.932 |
2004–2005 | −0.206 | −0.053 | 0.007 | 0.029 | 0.991 | −0.039 | 0.729 |
2005–2006 | 0.012 | −0.161 | −0.237 | 0.258 | 0.712 | 0.004 | 0.588 |
2006–2007 | 0.049 | −0.247 | −0.270 | 0.737 | 0.194 | 0.014 | 0.477 |
2007–2008 | −0.045 | −0.361 | −0.259 | 0.543 | 0.417 | −0.002 | 0.294 |
2008–2009 | 0.725 | −7.118 | 9.346 | −23.906 | 22.346 | 2.574 | 3.967 |
2009–2010 | 0.058 | −0.290 | 0.142 | 0.064 | 0.944 | −0.014 | 0.904 |
2010–2011 | 0.089 | −0.188 | −0.233 | 0.461 | 0.418 | 0.095 | 0.643 |
2011–2012 | −0.131 | 0.113 | −0.010 | 0.959 | 0.028 | 0.012 | 0.971 |
2012–2013 | 0.030 | 1.037 | −1.323 | −0.271 | 0.524 | 0.735 | 0.732 |
2013–2014 | −0.048 | −0.398 | −0.158 | 0.154 | 0.762 | 0.055 | 0.367 |
2014–2015 | −0.095 | 0.992 | −1.184 | 0.285 | 0.739 | −0.034 | 0.703 |
2015–2016 | 0.122 | −0.225 | −0.416 | 0.315 | 0.678 | −0.014 | 0.460 |
2016–2017 | 0.106 | −0.052 | −0.503 | 0.085 | 0.902 | −0.014 | 0.524 |
2017–2018 | 0.198 | −0.082 | −0.543 | 1.203 | 0.077 | −0.298 | 0.556 |
2018–2019 | 0.229 | 0.320 | −1.387 | 0.975 | 0.058 | −0.056 | 0.139 |
2019–2020 | −0.229 | 0.881 | −0.511 | 2.493 | −1.549 | 0.052 | 1.137 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Li, X.-Y.; Chen, T.; Chen, B. Research on the Influencing Factors and Decoupling State of Carbon Emissions in China’s Transportation Industry. Sustainability 2023, 15, 11871. https://doi.org/10.3390/su151511871
Li X-Y, Chen T, Chen B. Research on the Influencing Factors and Decoupling State of Carbon Emissions in China’s Transportation Industry. Sustainability. 2023; 15(15):11871. https://doi.org/10.3390/su151511871
Chicago/Turabian StyleLi, Xiao-Yang, Tao Chen, and Bin Chen. 2023. "Research on the Influencing Factors and Decoupling State of Carbon Emissions in China’s Transportation Industry" Sustainability 15, no. 15: 11871. https://doi.org/10.3390/su151511871