IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i4p948-d141372.html
   My bibliography  Save this article

Energy-Saving Potential of China’s Steel Industry According to Its Development Plan

Author

Listed:
  • Kun He

    (School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China)

  • Li Wang

    (School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
    Beijing Engineering Research Center for Energy Saving & Environmental Protection, Beijing 100083, China)

  • Hongliang Zhu

    (Hanbao Steel Energy Center, Handan 056015, China)

  • Yulong Ding

    (Birmingham Centre for Energy Storage, School of Chemical Engineering, University of Birmingham, Birmingham B15 2TT, UK)

Abstract

The energy consumption of China’s steel industry accounted for 53% of the global steel industry energy consumption in 2014. This paper aims to analyze the energy saving potential of China’s steel industry, according to its development plan of the next decade, and find the key of energy conservation. A multivariate energy intensity (MEI) model is developed for energy saving potential analysis based on the research on China’s energy statistics indexes and methods, which is able to capture the impacts of production routes, technology progress, industrial concentration, energy structure, and electricity (proportion and generation efficiency). Different scenarios have been set to describe future policy measures in relation to the development of the iron and steel industry. Results show that an increasing scrap ratio (SR) has the greatest energy saving effect of 16.8% when compared with 2014, and the maximum energy saving potential reaches 23.7% after counting other factors. When considering coal consumption of power generation, the energy saving effect of increasing SR drops to 7.9%, due to the increase on the proportion of electricity in total energy consumption, and the maximum energy saving potential is 15.5%, and they can increase to 10.1% and 17.5%, respectively, with improving China’s power generation technology level.

Suggested Citation

  • Kun He & Li Wang & Hongliang Zhu & Yulong Ding, 2018. "Energy-Saving Potential of China’s Steel Industry According to Its Development Plan," Energies, MDPI, vol. 11(4), pages 1-16, April.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:948-:d:141372
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/4/948/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/11/4/948/
    Download Restriction: no
    ---><---

    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. Stefan Nabernegg & Birgit Bednar-Friedl & Fabian Wagner & Thomas Schinko & Janusz Cofala & Yadira Mori Clement, 2017. "The Deployment of Low Carbon Technologies in Energy Intensive Industries: A Macroeconomic Analysis for Europe, China and India," Energies, MDPI, vol. 10(3), pages 1-26, March.
    3. Fujimori, Shinichiro & Masui, Toshihiko & Matsuoka, Yuzuru, 2014. "Development of a global computable general equilibrium model coupled with detailed energy end-use technology," Applied Energy, Elsevier, vol. 128(C), pages 296-306.
    4. Ye Duan & Nan Li & Hailin Mu & Shusen Gui, 2017. "Research on CO 2 Emission Reduction Mechanism of China’s Iron and Steel Industry under Various Emission Reduction Policies," Energies, MDPI, vol. 10(12), pages 1-24, December.
    5. Proença, Sara & St. Aubyn, Miguel, 2013. "Hybrid modeling to support energy-climate policy: Effects of feed-in tariffs to promote renewable energy in Portugal," Energy Economics, Elsevier, vol. 38(C), pages 176-185.
    6. Murphy, Rose & Jaccard, Mark, 2011. "Energy efficiency and the cost of GHG abatement: A comparison of bottom-up and hybrid models for the US," Energy Policy, Elsevier, vol. 39(11), pages 7146-7155.
    7. Dai, Hancheng & Mischke, Peggy & Xie, Xuxuan & Xie, Yang & Masui, Toshihiko, 2016. "Closing the gap? Top-down versus bottom-up projections of China’s regional energy use and CO2 emissions," Applied Energy, Elsevier, vol. 162(C), pages 1355-1373.
    8. 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.
    9. He, Feng & Zhang, Qingzhi & Lei, Jiasu & Fu, Weihui & Xu, Xiaoning, 2013. "Energy efficiency and productivity change of China’s iron and steel industry: Accounting for undesirable outputs," Energy Policy, Elsevier, vol. 54(C), pages 204-213.
    10. 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.
    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. Xiongfeng Pan & Mengna Li & Chenxi Pu & Haitao Xu, 2021. "Study on the industrial structure optimization under constraint of energy intensity," Energy & Environment, , vol. 32(1), pages 134-151, February.
    2. Gu, Wei & Wei, Lirong & Zhang, Wenqing & Yan, Xiangbin, 2019. "Evolutionary game analysis of cooperation between natural resource- and energy-intensive companies in reverse logistics operations," International Journal of Production Economics, Elsevier, vol. 218(C), pages 159-169.

    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, 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.
    2. 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.
    3. Dai, Hancheng & Mischke, Peggy & Xie, Xuxuan & Xie, Yang & Masui, Toshihiko, 2016. "Closing the gap? Top-down versus bottom-up projections of China’s regional energy use and CO2 emissions," Applied Energy, Elsevier, vol. 162(C), pages 1355-1373.
    4. Xuan, Yanni & Yue, Qiang, 2017. "Scenario analysis on resource and environmental benefits of imported steel scrap for China’s steel industry," Resources, Conservation & Recycling, Elsevier, vol. 120(C), pages 186-198.
    5. 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.
    6. Ma, Ding & Chen, Wenying & Yin, Xiang & Wang, Lining, 2016. "Quantifying the co-benefits of decarbonisation in China’s steel sector: An integrated assessment approach," Applied Energy, Elsevier, vol. 162(C), pages 1225-1237.
    7. Lin, Boqiang & Wang, Xiaolei, 2014. "Promoting energy conservation in China's iron & steel sector," Energy, Elsevier, vol. 73(C), pages 465-474.
    8. 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.
    9. Zeng, Yujiao & Xiao, Xin & Li, Jie & Sun, Li & Floudas, Christodoulos A. & Li, Hechang, 2018. "A novel multi-period mixed-integer linear optimization model for optimal distribution of byproduct gases, steam and power in an iron and steel plant," Energy, Elsevier, vol. 143(C), pages 881-899.
    10. 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.
    11. 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.
    12. Hu, Xueyue & Wang, Chunying & Elshkaki, Ayman, 2024. "Material-energy Nexus: A systematic literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    13. 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.
    14. Yue, Hui & Worrell, Ernst & Crijns-Graus, Wina, 2021. "Impacts of regional industrial electricity savings on the development of future coal capacity per electricity grid and related air pollution emissions – A case study for China," Applied Energy, Elsevier, vol. 282(PB).
    15. Zhang, Shaohui & Worrell, Ernst & Crijns-Graus, Wina & Krol, Maarten & de Bruine, Marco & Geng, Guangpo & Wagner, Fabian & Cofala, Janusz, 2016. "Modeling energy efficiency to improve air quality and health effects of China’s cement industry," Applied Energy, Elsevier, vol. 184(C), pages 574-593.
    16. 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.
    17. Lee, Hwarang & Kang, Sung Won & Koo, Yoonmo, 2020. "A hybrid energy system model to evaluate the impact of climate policy on the manufacturing sector: Adoption of energy-efficient technologies and rebound effects," Energy, Elsevier, vol. 212(C).
    18. Pusnik, M. & Al-Mansour, F. & Sucic, B. & Cesen, M., 2017. "Trends and prospects of energy efficiency development in Slovenian industry," Energy, Elsevier, vol. 136(C), pages 52-62.
    19. Wang, Peng & Li, Wen & Kara, Sami, 2017. "Cradle-to-cradle modeling of the future steel flow in China," Resources, Conservation & Recycling, Elsevier, vol. 117(PA), pages 45-57.
    20. Gang Du & Chuanwang Sun, 2015. "Determinants of Electricity Demand in Nonmetallic Mineral Products Industry: Evidence from a Comparative Study of Japan and China," Sustainability, MDPI, vol. 7(6), pages 1-25, June.

    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:gam:jeners:v:11:y:2018:i:4:p:948-:d:141372. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.