IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v86y2020ics0140988319304256.html
   My bibliography  Save this article

The Energy-conservation and Emission-reduction Paths of Industrial sectors: Evidence from Chinas 35 industrial sectors

Author

Listed:
  • Li, Xiaoyan
  • Xu, Hengzhou

Abstract

Accurately estimating and formulating the paths of energy-conservation and emission-reduction for industrial sectors is of great significance for the coordinated development of economic growth and environment in China. In this study, considering the influences of short- and long-term energy rebound effects, we estimated the energy-conservation and emission-reduction potential of China's 35 industrial sectors and formulated the implementation paths. Our results show that: (1) under a long-term energy rebound effect impact, for the resource-intensive, labor-intensive, and capital-intensive industries, the industrial sectors with the greatest energy-conservation potential are the manufacture of tobacco, manufacture of textile, wearing apparel and accessories, and the manufacture of general purpose machinery, with cumulative energy-conservations of 14.41, 25.67, and 11.455%, respectively. The industrial sectors with the greatest emission-reduction potential are the extraction of petroleum and natural gas, mining and processing of non-ferrous metal ores, and the manufacture of chemical fibers, with cumulative emission-reductions of 23.54, 35.42, and 22.14%, respectively. (2) Under a short-term energy rebound effect impact, for resource-intensive, labor-intensive, and capital-intensive industries, the industrial sectors with the greatest energy-conservation potential are the manufacture of tobacco, manufacture of textile and manufacture of medicines, with cumulative energy-conservations of 23.56, 28.65, and 15.36%, respectively. The industrial sectors with the greatest emission-reduction potential are the manufacture of tobacco, mining and processing of ferrous metal ores, and smelting and pressing of non-ferrous metals, with cumulative emission-reductions of 27.88, 38.48, and 33.28%, respectively. (3) There are three paths for energy-conservation and emission-reduction for the industrial sectors: the unilateral breakthrough, gradual improvement, that promotes advantages and accounts for disadvantages, and leap forward path. For industrial sectors with a high energy consumption and low carbon emissions, the gradual improvement path that promotes advantages and accounts for disadvantages is suitable. For industrial sectors with low energy consumption and high carbon emissions, the unilateral breakthrough path is suitable. For industrial sectors with high energy consumption and carbon emissions, the leap forward path is suitable. (4) The impacts of investment bias and factor market distortion should be considered when formulating energy-conservation and emission-reduction policies. Our results can provide a theoretical basis for the formulation of energy-conservation and emissions-reduction objectives and policies for China's 35 industrial sectors.

Suggested Citation

  • Li, Xiaoyan & Xu, Hengzhou, 2020. "The Energy-conservation and Emission-reduction Paths of Industrial sectors: Evidence from Chinas 35 industrial sectors," Energy Economics, Elsevier, vol. 86(C).
  • Handle: RePEc:eee:eneeco:v:86:y:2020:i:c:s0140988319304256
    DOI: 10.1016/j.eneco.2019.104628
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988319304256
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2019.104628?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fare, Rolf & Grosskopf, Shawna, 1996. "Productivity and intermediate products: A frontier approach," Economics Letters, Elsevier, vol. 50(1), pages 65-70, January.
    2. Matthews, Kent, 2013. "Risk management and managerial efficiency in Chinese banks: A network DEA framework," Omega, Elsevier, vol. 41(2), pages 207-215.
    3. Yu, Shiwei & Zheng, Shuhong & Li, Xia & Li, Longxi, 2018. "China can peak its energy-related carbon emissions before 2025: Evidence from industry restructuring," Energy Economics, Elsevier, vol. 73(C), pages 91-107.
    4. Yi, Su & Xiao-li, An, 2018. "Application of threshold regression analysis to study the impact of regional technological innovation level on sustainable development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 27-32.
    5. Rahman, Mohammad Mafizur & Kashem, Mohammad Abul, 2017. "Carbon emissions, energy consumption and industrial growth in Bangladesh: Empirical evidence from ARDL cointegration and Granger causality analysis," Energy Policy, Elsevier, vol. 110(C), pages 600-608.
    6. Yang, Mian & Yang, Fuxia & Sun, Chuanwang, 2018. "Factor market distortion correction, resource reallocation and potential productivity gains: An empirical study on China's heavy industry sector," Energy Economics, Elsevier, vol. 69(C), pages 270-279.
    7. Ouyang, Xiaoling & Sun, Chuanwang, 2015. "Energy savings potential in China's industrial sector: From the perspectives of factor price distortion and allocative inefficiency," Energy Economics, Elsevier, vol. 48(C), pages 117-126.
    8. Burtt, D. & Dargusch, P., 2015. "The cost-effectiveness of household photovoltaic systems in reducing greenhouse gas emissions in Australia: Linking subsidies with emission reductions," Applied Energy, Elsevier, vol. 148(C), pages 439-448.
    9. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    10. Yan, Zheming & Ouyang, Xiaoling & Du, Kerui, 2019. "Economy-wide estimates of energy rebound effect: Evidence from China's provinces," Energy Economics, Elsevier, vol. 83(C), pages 389-401.
    11. Li, Jianglong & Lin, Boqiang, 2017. "Rebound effect by incorporating endogenous energy efficiency: A comparison between heavy industry and light industry," Applied Energy, Elsevier, vol. 200(C), pages 347-357.
    12. Wu, Ya & Zhang, Li, 2017. "Evaluation of energy saving effects of tiered electricity pricing and investigation of the energy saving willingness of residents," Energy Policy, Elsevier, vol. 109(C), pages 208-217.
    13. Dong, Kangyin & Sun, Renjin & Hochman, Gal & Li, Hui, 2018. "Energy intensity and energy conservation potential in China: A regional comparison perspective," Energy, Elsevier, vol. 155(C), pages 782-795.
    14. Wei, Taoyuan & Liu, Yang, 2017. "Estimation of global rebound effect caused by energy efficiency improvement," Energy Economics, Elsevier, vol. 66(C), pages 27-34.
    15. Cantore, Nicola & Calì, Massimiliano & Velde, Dirk Willem te, 2016. "Does energy efficiency improve technological change and economic growth in developing countries?," Energy Policy, Elsevier, vol. 92(C), pages 279-285.
    16. Bye, Brita & Fæhn, Taran & Rosnes, Orvika, 2018. "Residential energy efficiency policies: Costs, emissions and rebound effects," Energy, Elsevier, vol. 143(C), pages 191-201.
    17. Li, Ke & Lin, Boqiang, 2018. "How to promote energy efficiency through technological progress in China?," Energy, Elsevier, vol. 143(C), pages 812-821.
    18. Cecilio Mar-Molinero & Diego Prior & Maria-Manuela Segovia & Fabiola Portillo, 2014. "On centralized resource utilization and its reallocation by using DEA," Annals of Operations Research, Springer, vol. 221(1), pages 273-283, October.
    19. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    20. Li, Ke & Jiang, Zhujun, 2016. "The impacts of removing energy subsidies on economy-wide rebound effects in China: An input-output analysis," Energy Policy, Elsevier, vol. 98(C), pages 62-72.
    21. Zhang, Yue-Jun & Peng, Hua-Rong & Su, Bin, 2017. "Energy rebound effect in China's Industry: An aggregate and disaggregate analysis," Energy Economics, Elsevier, vol. 61(C), pages 199-208.
    22. Zhang, Yu & Zhang, Sufang, 2018. "The impacts of GDP, trade structure, exchange rate and FDI inflows on China's carbon emissions," Energy Policy, Elsevier, vol. 120(C), pages 347-353.
    23. Zhang, Jiangshan & Lin Lawell, C.-Y. Cynthia, 2017. "The macroeconomic rebound effect in China," Energy Economics, Elsevier, vol. 67(C), pages 202-212.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Wei & You, Jianmin & Lin, Weiwen, 2021. "Internet plus and China industrial system's low-carbon development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    2. Xiaoyan Li & Hengzhou Xu, 2020. "Effect of local government decision‐making competition on carbon emissions: Evidence from China's three urban agglomerations," Business Strategy and the Environment, Wiley Blackwell, vol. 29(6), pages 2418-2431, September.
    3. Xu, Mengmeng & Tan, Ruipeng & He, Xinju, 2022. "How does economic agglomeration affect energy efficiency in China?: Evidence from endogenous stochastic frontier approach," Energy Economics, Elsevier, vol. 108(C).
    4. Li, Xiaoyan, 2020. "Design of energy-conservation and emission-reduction plans of China’s industry: Evidence from three typical industries," Energy, Elsevier, vol. 209(C).
    5. He, Yong & Liao, Nuo & Lin, Kunrong, 2021. "Can China's industrial sector achieve energy conservation and emission reduction goals dominated by energy efficiency enhancement? A multi-objective optimization approach," Energy Policy, Elsevier, vol. 149(C).
    6. Zhen, Wei & Qin, Quande & Miao, Lu, 2023. "The greenhouse gas rebound effect from increased energy efficiency across China's staple crops," Energy Policy, Elsevier, vol. 173(C).
    7. Yan, Junna & Su, Bin, 2020. "What drive the changes in China's energy consumption and intensity during 12th Five-Year Plan period?," Energy Policy, Elsevier, vol. 140(C).
    8. Jin, Baoling & Han, Ying & Kou, Po, 2023. "Dynamically evaluating the comprehensive efficiency of technological innovation and low-carbon economy in China's industrial sectors," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    9. Zhang, Jie & Zhang, Ke & Zhao, Feng, 2020. "Research on the regional spatial effects of green development and environmental governance in China based on a spatial autocorrelation model," Structural Change and Economic Dynamics, Elsevier, vol. 55(C), pages 1-11.
    10. Liu, Yang & Zhang, Congrui & Xu, Xiaochuan & Ge, Yongxiang & Ren, Gaofeng, 2022. "Assessment of energy conservation potential and cost in open-pit metal mines: Bottom-up approach integrated energy conservation supply curve and ultimate pit limit," Energy Policy, Elsevier, vol. 163(C).
    11. Wang, Xiaoling & Zhang, Tianyue & Nathwani, Jatin & Yang, Fangming & Shao, Qinglong, 2022. "Environmental regulation, technology innovation, and low carbon development: Revisiting the EKC Hypothesis, Porter Hypothesis, and Jevons’ Paradox in China's iron & steel industry," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    12. Ma, Ruiyang & Lin, Boqiang, 2023. "Digitalization and energy-saving and emission reduction in Chinese cities: Synergy between industrialization and digitalization," Applied Energy, Elsevier, vol. 345(C).
    13. Šubová, Nikola, 2022. "The Contribution of Energy Use and Production to Greenhouse Gas Emissions: Evidence from the Agriculture of European Countries," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 14(3), September.
    14. Yu Cai & Haiyan Duan & Zhiqiang Luo & Zhiyuan Duan & Xian’en Wang, 2022. "Dynamic Driving Mechanism of Dual Structural Effects on the Correlation between Economic Growth and CO 2 Emissions: Evidence from a Typical Transformation Region," IJERPH, MDPI, vol. 19(7), pages 1-17, March.
    15. Wei Zhen & Quande Qin & Lei Jiang, 2022. "Heterogeneous Domestic Intermediate Input-Related Carbon Emissions in China’s Exports," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 81(3), pages 453-479, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiaoyan Li & Hengzhou Xu, 2020. "Effect of local government decision‐making competition on carbon emissions: Evidence from China's three urban agglomerations," Business Strategy and the Environment, Wiley Blackwell, vol. 29(6), pages 2418-2431, September.
    2. Li, Xiaoyan, 2020. "Design of energy-conservation and emission-reduction plans of China’s industry: Evidence from three typical industries," Energy, Elsevier, vol. 209(C).
    3. Jin, Taeyoung & Kim, Jinsoo, 2019. "A new approach for assessing the macroeconomic growth energy rebound effect," Applied Energy, Elsevier, vol. 239(C), pages 192-200.
    4. Maliyamu Abudureheman & Qingzhe Jiang & Xiucheng Dong & Cong Dong, 2022. "CO 2 Emissions in China: Does the Energy Rebound Matter?," Energies, MDPI, vol. 15(12), pages 1-25, June.
    5. Xu, Guangyue & Schwarz, Peter & Yang, Hualiu, 2020. "Adjusting energy consumption structure to achieve China's CO2 emissions peak," Renewable and Sustainable Energy Reviews, Elsevier, vol. 122(C).
    6. Jafari, Mahboubeh & Stern, David I. & Bruns, Stephan B., 2022. "How large is the economy-wide rebound effect in middle income countries? Evidence from Iran," Ecological Economics, Elsevier, vol. 193(C).
    7. Xu, Mengmeng & Lin, Boqiang, 2022. "Energy efficiency gains from distortion mitigation: A perspective on the metallurgical industry," Resources Policy, Elsevier, vol. 77(C).
    8. Safarzadeh, Soroush & Rasti-Barzoki, Morteza & Hejazi, Seyed Reza & Piran, Md Jalil, 2020. "A game theoretic approach for the duopoly pricing of energy-efficient appliances regarding innovation protection and social welfare," Energy, Elsevier, vol. 200(C).
    9. Lin, Boqiang & Kuang, Yunming, 2020. "Natural gas subsidies in the industrial sector in China: National and regional perspectives," Applied Energy, Elsevier, vol. 260(C).
    10. Yan, Zheming & Ouyang, Xiaoling & Du, Kerui, 2019. "Economy-wide estimates of energy rebound effect: Evidence from China's provinces," Energy Economics, Elsevier, vol. 83(C), pages 389-401.
    11. Huang, Chin-wei & Ho, Foo Nin & Chiu, Yung-ho, 2014. "Measurement of tourist hotels׳ productive efficiency, occupancy, and catering service effectiveness using a modified two-stage DEA model in Taiwan," Omega, Elsevier, vol. 48(C), pages 49-59.
    12. Colmenares, Gloria & Löschel, Andreas & Madlener, Reinhard, 2019. "The rebound effect and its representation in energy and climate models," CAWM Discussion Papers 106, University of Münster, Münster Center for Economic Policy (MEP).
    13. Ru Sha & Tao Ge & Jinye Li, 2022. "How Energy Price Distortions Affect China’s Economic Growth and Carbon Emissions," Sustainability, MDPI, vol. 14(12), pages 1-27, June.
    14. Ai, Hongshan & Wu, Xiaofei & Li, Ke, 2020. "Differentiated effects of diversified technological sources on China's electricity consumption: Evidence from the perspective of rebound effect," Energy Policy, Elsevier, vol. 137(C).
    15. Cao, Hongjian & Wang, Bizhe & Li, Ke, 2021. "Regulatory policy and misallocation: A new perspective based on the productivity effect of cleaner production standards in China's energy firms," Energy Policy, Elsevier, vol. 152(C).
    16. An, Qingxian & Chen, Haoxun & Xiong, Beibei & Wu, Jie & Liang, Liang, 2017. "Target intermediate products setting in a two-stage system with fairness concern," Omega, Elsevier, vol. 73(C), pages 49-59.
    17. Kong, Li & Mu, Xianzhong & Hu, Guangwen & Tu, Chuang, 2023. "Will energy efficiency improvements reduce energy consumption? Perspective of rebound effect and evidence from beijing," Energy, Elsevier, vol. 263(PA).
    18. Peng, Hua-Rong & Zhang, Yue-Jun & Liu, Jing-Yue, 2023. "The energy rebound effect of digital development: Evidence from 285 cities in China," Energy, Elsevier, vol. 270(C).
    19. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    20. Sha, Ru & Li, Jinye & Ge, Tao, 2021. "How do price distortions of fossil energy sources affect China's green economic efficiency?," Energy, Elsevier, vol. 232(C).

    More about this item

    Keywords

    Industry sectors; Energy-conservation; Emission-reduction; Energy rebound effect; Implementation path;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:86:y:2020:i:c:s0140988319304256. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.