IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v175y2019icp1009-1020.html
   My bibliography  Save this article

Comparative study on power efficiency of China's provincial steel industry and its influencing factors

Author

Listed:
  • Wu, Ya
  • Su, JingRong
  • Li, Ke
  • Sun, Chuanwang

Abstract

In China, power consumption in the steel industry accounts for about 9% of the whole society's power consumption. There is a big gap between the power efficiency of China's steel industry and the world's advanced level, and the power efficiency varies greatly in all regions of China. By using the three-stage data envelope analysis model, this study analyzes the influence of external factors (including environmental regulation, industrial structure, and trade openness) on the power efficiency of the steel industry in 28 provinces of China. Overall, the power efficiency of the steel industry in the eastern, central, and western China present the high, middle, and low power efficiency, respectively. The results reveal that improving trade openness and optimizing industrial structure are conducive to improving the power efficiency, while improving the intensity of environmental regulation can cause the excessive substitution of power sources for other energy resources so as to decrease the power efficiency. Moreover, power efficiency in the eastern and western China are more affected by the external factors than it in the central China. The research conclusions are favorable to introduce different measures for various regions so as to reduce the gap in power efficiency of the steel industry.

Suggested Citation

  • Wu, Ya & Su, JingRong & Li, Ke & Sun, Chuanwang, 2019. "Comparative study on power efficiency of China's provincial steel industry and its influencing factors," Energy, Elsevier, vol. 175(C), pages 1009-1020.
  • Handle: RePEc:eee:energy:v:175:y:2019:i:c:p:1009-1020
    DOI: 10.1016/j.energy.2019.03.144
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054421930564X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2019.03.144?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. Lin, Boqiang & Wu, Ya & Zhang, Li, 2011. "Estimates of the potential for energy conservation in the Chinese steel industry," Energy Policy, Elsevier, vol. 39(6), pages 3680-3689, June.
    2. Karen Fisher-Vanden, Yong Hu, Gary Jefferson, Michael Rock and Michael Toman, 2016. "Factors influencing energy intensity in four Chinese industries," The Energy Journal, International Association for Energy Economics, vol. 0(China Spe).
    3. Sun, Fengrui & Yao, Yuedong & Chen, Mingqiang & Li, Xiangfang & Zhao, Lin & Meng, Ye & Sun, Zheng & Zhang, Tao & Feng, Dong, 2017. "Performance analysis of superheated steam injection for heavy oil recovery and modeling of wellbore heat efficiency," Energy, Elsevier, vol. 125(C), pages 795-804.
    4. Li, Ke & Lin, Boqiang, 2015. "The improvement gap in energy intensity: Analysis of China's thirty provincial regions using the improved DEA (data envelopment analysis) model," Energy, Elsevier, vol. 84(C), pages 589-599.
    5. Gale A. Boyd, 2008. "Estimating Plant Level Energy Efficiency with a Stochastic Frontier," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 23-44.
    6. Xu, Bin & Lin, Boqiang, 2017. "Assessing CO2 emissions in China's iron and steel industry: A nonparametric additive regression approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 325-337.
    7. Zhang, Qi & Zhao, Xiaoyu & Lu, Hongyou & Ni, Tuanjie & Li, Yu, 2017. "Waste energy recovery and energy efficiency improvement in China’s iron and steel industry," Applied Energy, Elsevier, vol. 191(C), pages 502-520.
    8. An, Runying & Yu, Biying & Li, Ru & Wei, Yi-Ming, 2018. "Potential of energy savings and CO2 emission reduction in China’s iron and steel industry," Applied Energy, Elsevier, vol. 226(C), pages 862-880.
    9. Yang, Wei & Shi, Jinfeng & Qiao, Han & Shao, Yanmin & Wang, Shouyang, 2017. "Regional technical efficiency of Chinese Iron and steel industry based on bootstrap network data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 14-24.
    10. Karimu, Amin & Brännlund, Runar & Lundgren, Tommy & Söderholm, Patrik, 2017. "Energy intensity and convergence in Swedish industry: A combined econometric and decomposition analysis," Energy Economics, Elsevier, vol. 62(C), pages 347-356.
    11. Sun, Fengrui & Yao, Yuedong & Li, Guozhen & Li, Xiangfang, 2018. "Geothermal energy extraction in CO2 rich basin using abandoned horizontal wells," Energy, Elsevier, vol. 158(C), pages 760-773.
    12. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    13. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    14. 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.
    15. Xu, Bin & Lin, Boqiang, 2016. "A quantile regression analysis of China's provincial CO2 emissions: Where does the difference lie?," Energy Policy, Elsevier, vol. 98(C), pages 328-342.
    16. Zhou, Kaile & Yang, Shanlin, 2016. "Emission reduction of China׳s steel industry: Progress and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 319-327.
    17. Hasanbeigi, Ali & Morrow, William & Sathaye, Jayant & Masanet, Eric & Xu, Tengfang, 2013. "A bottom-up model to estimate the energy efficiency improvement and CO2 emission reduction potentials in the Chinese iron and steel industry," Energy, Elsevier, vol. 50(C), pages 315-325.
    18. 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.
    19. Worrell, Ernst & Price, Lynn & Martin, Nathan & Farla, Jacco & Schaeffer, Roberto, 1997. "Energy intensity in the iron and steel industry: a comparison of physical and economic indicators," Energy Policy, Elsevier, vol. 25(7-9), pages 727-744.
    20. Wang, Xiaolei & Lin, Boqiang, 2016. "How to reduce CO2 emissions in China׳s iron and steel industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1496-1505.
    21. Lin, Boqiang & Wang, Xiaolei, 2014. "Exploring energy efficiency in China׳s iron and steel industry: A stochastic frontier approach," Energy Policy, Elsevier, vol. 72(C), pages 87-96.
    22. Brunke, Jean-Christian & Blesl, Markus, 2014. "A plant-specific bottom-up approach for assessing the cost-effective energy conservation potential and its ability to compensate rising energy-related costs in the German iron and steel industry," Energy Policy, Elsevier, vol. 67(C), pages 431-446.
    23. Xu, Bin & Lin, Boqiang, 2016. "Regional differences in the CO2 emissions of China's iron and steel industry: Regional heterogeneity," Energy Policy, Elsevier, vol. 88(C), pages 422-434.
    24. Sun, Fengrui & Yao, Yuedong & Li, Xiangfang, 2018. "The heat and mass transfer characteristics of superheated steam coupled with non-condensing gases in horizontal wells with multi-point injection technique," Energy, Elsevier, vol. 143(C), pages 995-1005.
    25. Wu, Xuecheng & Zhao, Liang & Zhang, Yongxin & Zhao, Lingjie & Zheng, Chenghang & Gao, Xiang & Cen, Kefa, 2016. "Cost and potential of energy conservation and collaborative pollutant reduction in the iron and steel industry in China," Applied Energy, Elsevier, vol. 184(C), pages 171-183.
    26. Xu, Bin & Lin, Boqiang, 2016. "Assessing CO2 emissions in China’s iron and steel industry: A dynamic vector autoregression model," Applied Energy, Elsevier, vol. 161(C), pages 375-386.
    27. Wei, Yi-Ming & Liao, Hua & Fan, Ying, 2007. "An empirical analysis of energy efficiency in China's iron and steel sector," Energy, Elsevier, vol. 32(12), pages 2262-2270.
    28. Zhang, Shaohui & Worrell, Ernst & Crijns-Graus, Wina & Wagner, Fabian & Cofala, Janusz, 2014. "Co-benefits of energy efficiency improvement and air pollution abatement in the Chinese iron and steel industry," Energy, Elsevier, vol. 78(C), pages 333-345.
    29. Sheinbaum, Claudia & Ozawa, Leticia & Castillo, Daniel, 2010. "Using logarithmic mean Divisia index to analyze changes in energy use and carbon dioxide emissions in Mexico's iron and steel industry," Energy Economics, Elsevier, vol. 32(6), pages 1337-1344, November.
    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. Sun, Huaping & Edziah, Bless Kofi & Sun, Chuanwang & Kporsu, Anthony Kwaku, 2019. "Institutional quality, green innovation and energy efficiency," Energy Policy, Elsevier, vol. 135(C).
    2. Michaela Staňková, 2020. "Efficiency Comparison and Efficiency Development of the Metallurgical Industry in the EU: Parametric and Non-parametric Approaches," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 68(4), pages 765-774.
    3. Elshkaki, Ayman, 2019. "Material-energy-water-carbon nexus in China’s electricity generation system up to 2050," Energy, Elsevier, vol. 189(C).
    4. Alvarez, Gonzalo E., 2020. "Operation of pumped storage hydropower plants through optimization for power systems," Energy, Elsevier, vol. 202(C).
    5. Xue, Liming & Zhang, Wenjie & Zheng, Zhixue & Liu, Zhe & Meng, Shuo & Li, Huaqing & Du, Yulin, 2021. "Measurement and influential factors of the efficiency of coal resources of China’s provinces: Based on Bootstrap-DEA and Tobit," Energy, Elsevier, vol. 221(C).
    6. Liu, Haomin & Zhang, Zaixu & Zhang, Tao & Wang, Liyang, 2020. "Revisiting China’s provincial energy efficiency and its influencing factors," Energy, Elsevier, vol. 208(C).
    7. Zhang, Caiqing & Chen, Panyu, 2022. "Applying the three-stage SBM-DEA model to evaluate energy efficiency and impact factors in RCEP countries," Energy, Elsevier, vol. 241(C).
    8. Yang, Jun & Zou, Ran & Cheng, Jixin & Geng, Zhifei & Li, Qi, 2023. "Environmental technical efficiency and its dynamic evolution in China's industry: A resource endowment perspective," Resources Policy, Elsevier, vol. 82(C).
    9. Yongzhong Jiang & Xueli Chen & Vivian Valdmanis & Tomas Baležentis, 2019. "Evaluating Economic and Environmental Performance of the Chinese Industry Sector," Sustainability, MDPI, vol. 11(23), pages 1-17, November.

    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. Xu, Bin & Lin, Boqiang, 2017. "Assessing CO2 emissions in China's iron and steel industry: A nonparametric additive regression approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 325-337.
    2. Song, Yi & Huang, Jian-Bai & Feng, Chao, 2018. "Decomposition of energy-related CO2 emissions in China's iron and steel industry: A comprehensive decomposition framework," Resources Policy, Elsevier, vol. 59(C), pages 103-116.
    3. An, Runying & Yu, Biying & Li, Ru & Wei, Yi-Ming, 2018. "Potential of energy savings and CO2 emission reduction in China’s iron and steel industry," Applied Energy, Elsevier, vol. 226(C), pages 862-880.
    4. Sheinbaum-Pardo, Claudia, 2016. "Decomposition analysis from demand services to material production: The case of CO2 emissions from steel produced for automobiles in Mexico," Applied Energy, Elsevier, vol. 174(C), pages 245-255.
    5. Wang, Xiaoyang & Yu, Biying & An, Runying & Sun, Feihu & Xu, Shuo, 2022. "An integrated analysis of China’s iron and steel industry towards carbon neutrality," Applied Energy, Elsevier, vol. 322(C).
    6. Wu, Rui & Geng, Yong & Cui, Xiaowei & Gao, Ziyan & Liu, Zhiqing, 2019. "Reasons for recent stagnancy of carbon emissions in China's industrial sectors," Energy, Elsevier, vol. 172(C), pages 457-466.
    7. Wang, Can & Zheng, Xinzhu & Cai, Wenjia & Gao, Xue & Berrill, Peter, 2017. "Unexpected water impacts of energy-saving measures in the iron and steel sector: Tradeoffs or synergies?," Applied Energy, Elsevier, vol. 205(C), pages 1119-1127.
    8. Chao-Qun Ma & Jiang-Long Liu & Yi-Shuai Ren & Yong Jiang, 2019. "The Impact of Economic Growth, FDI and Energy Intensity on China’s Manufacturing Industry’s CO 2 Emissions: An Empirical Study Based on the Fixed-Effect Panel Quantile Regression Model," Energies, MDPI, vol. 12(24), pages 1-16, December.
    9. Zhou, Kaile & Yang, Shanlin, 2016. "Emission reduction of China׳s steel industry: Progress and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 319-327.
    10. Feng, Chao & Huang, Jian-Bai & Wang, Miao, 2019. "The sustainability of China’s metal industries: features, challenges and future focuses," Resources Policy, Elsevier, vol. 60(C), pages 215-224.
    11. Xu, Mengmeng & Lin, Boqiang, 2022. "Energy efficiency gains from distortion mitigation: A perspective on the metallurgical industry," Resources Policy, Elsevier, vol. 77(C).
    12. Yongrok Choi & Yanni Yu & Hyoung Seok Lee, 2018. "A Study on the Sustainable Performance of the Steel Industry in Korea Based on SBM-DEA," Sustainability, MDPI, vol. 10(1), pages 1-15, January.
    13. Surakiat PARICHATNON & Kamonthip MAICHUM & Ke-Chung PENG, 2018. "Measuring technical efficiency of Thai rubber production using the three-stage data envelopment analysis," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 64(5), pages 227-240.
    14. Zhao, Haoran & Guo, Sen & Zhao, Huiru, 2019. "Provincial energy efficiency of China quantified by three-stage data envelopment analysis," Energy, Elsevier, vol. 166(C), pages 96-107.
    15. Hu, Rui & Zhang, Qun, 2015. "Study of a low-carbon production strategy in the metallurgical industry in China," Energy, Elsevier, vol. 90(P2), pages 1456-1467.
    16. Zeng, Shihong & Jiang, Chunxia & Ma, Chen & Su, Bin, 2018. "Investment efficiency of the new energy industry in China," Energy Economics, Elsevier, vol. 70(C), pages 536-544.
    17. Akihiro Otsuka, 2020. "How do population agglomeration and interregional networks improve energy efficiency?," Asia-Pacific Journal of Regional Science, Springer, vol. 4(1), pages 1-25, February.
    18. Zhang, Qi & Xu, Jin & Wang, Yujie & Hasanbeigi, Ali & Zhang, Wei & Lu, Hongyou & Arens, Marlene, 2018. "Comprehensive assessment of energy conservation and CO2 emissions mitigation in China’s iron and steel industry based on dynamic material flows," Applied Energy, Elsevier, vol. 209(C), pages 251-265.
    19. Yang, Wei & Shi, Jinfeng & Qiao, Han & Shao, Yanmin & Wang, Shouyang, 2017. "Regional technical efficiency of Chinese Iron and steel industry based on bootstrap network data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 14-24.
    20. Wu, Rongxin & Lin, Boqiang, 2021. "Does industrial agglomeration improve effective energy service: An empirical study of China’s iron and steel industry," Applied Energy, Elsevier, vol. 295(C).

    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:energy:v:175:y:2019:i:c:p:1009-1020. 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.journals.elsevier.com/energy .

    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.