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Greenhouse gas contribution and emission reduction potential prediction of China's aluminum industry

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Listed:
  • Wang, Junya
  • Zhao, Qinfang
  • Ning, Ping
  • Wen, Shikun

Abstract

The aluminum industry, with its traditionally high energy consumption, high emissions and high pollution, is facing increasing pressure to reduce greenhouse gas (GHG) emissions in China. This study analyzes the trajectory and characteristics of GHG emissions during the lifecycle of China's aluminum industry (CAI) from 2011 to 2020, and identifies key driving factors affecting the changes in GHG emissions from CAI. The results indicate that the GHG emissions of CAI mainly come from indirect emissions generated by electricity production (over 69 %). Electrolytic aluminum is the largest sub process of GHG emissions in CAI. In addition, the total energy consumption effect is the main driving factor for the increase in GHG emissions from CAI. On this basis, emission reduction measures are proposed, the economic benefits and applicability of various emission reduction measures are analyzed, and the grey prediction model GM (1,1) is used to predict the GHG emission reduction potential of CAI in 2030. According to analysis, the GHG emission reduction efficiency of CAI is expected to reach 86 % by 2030, and can produce an annual economic benefit of 2.93 × 109RMB. This study will provide a theoretical basis for GHG emission reduction in CAI and even the global aluminum industry (GAI).

Suggested Citation

  • Wang, Junya & Zhao, Qinfang & Ning, Ping & Wen, Shikun, 2024. "Greenhouse gas contribution and emission reduction potential prediction of China's aluminum industry," Energy, Elsevier, vol. 290(C).
  • Handle: RePEc:eee:energy:v:290:y:2024:i:c:s0360544223035776
    DOI: 10.1016/j.energy.2023.130183
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    as
    1. Ding, Yang & Li, Feng, 2017. "Examining the effects of urbanization and industrialization on carbon dioxide emission: Evidence from China's provincial regions," Energy, Elsevier, vol. 125(C), pages 533-542.
    2. Joeri Rogelj & Piers M. Forster & Elmar Kriegler & Christopher J. Smith & Roland Séférian, 2019. "Estimating and tracking the remaining carbon budget for stringent climate targets," Nature, Nature, vol. 571(7765), pages 335-342, July.
    3. Wang, Zheng-Xin & Li, Qin & Pei, Ling-Ling, 2018. "A seasonal GM(1,1) model for forecasting the electricity consumption of the primary economic sectors," Energy, Elsevier, vol. 154(C), pages 522-534.
    4. Zhang, Yuwei & Zhang, Yingjie & Zhu, Hengxi & Zhou, Pengxiang & Liu, Shuai & Lei, Xiaoli & Li, Yanhong & Li, Bin & Ning, Ping, 2022. "Life cycle assessment of pollutants and emission reduction strategies based on the energy structure of the nonferrous metal industry in China," Energy, Elsevier, vol. 261(PA).
    5. Chaoyang Zhang & Zhengxu Wang & Kai Ding & Felix T.S. Chan & Weixi Ji, 2020. "An energy-aware cyber physical system for energy Big data analysis and recessive production anomalies detection in discrete manufacturing workshops," International Journal of Production Research, Taylor & Francis Journals, vol. 58(23), pages 7059-7077, December.
    6. Li, Shupeng & Niu, Liping & Yue, Qiang & Zhang, Tingan, 2022. "Trajectory, driving forces, and mitigation potential of energy-related greenhouse gas (GHG) emissions in China's primary aluminum industry," Energy, Elsevier, vol. 239(PB).
    7. Schwarz, Hans-Günter & Briem, Sebastian & Zapp, Petra, 2001. "Future carbon dioxide emissions in the global material flow of primary aluminium," Energy, Elsevier, vol. 26(8), pages 775-795.
    8. Biel, K. & Glock, C. H., 2016. "Systematic literature review of decision support models for energy-efficient production planning," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 83071, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    9. Yuan, Chaoqing & Liu, Sifeng & Fang, Zhigeng, 2016. "Comparison of China's primary energy consumption forecasting by using ARIMA (the autoregressive integrated moving average) model and GM(1,1) model," Energy, Elsevier, vol. 100(C), pages 384-390.
    10. Du, J.D. & Han, W.J. & Peng, Y.H. & Gu, C.C., 2010. "Potential for reducing GHG emissions and energy consumption from implementing the aluminum intensive vehicle fleet in China," Energy, Elsevier, vol. 35(12), pages 4671-4678.
    11. Lu, Renzhi & Li, Yi-Chang & Li, Yuting & Jiang, Junhui & Ding, Yuemin, 2020. "Multi-agent deep reinforcement learning based demand response for discrete manufacturing systems energy management," Applied Energy, Elsevier, vol. 276(C).
    12. Joeri Rogelj & Michel den Elzen & Niklas Höhne & Taryn Fransen & Hanna Fekete & Harald Winkler & Roberto Schaeffer & Fu Sha & Keywan Riahi & Malte Meinshausen, 2016. "Paris Agreement climate proposals need a boost to keep warming well below 2 °C," Nature, Nature, vol. 534(7609), pages 631-639, June.
    13. Liu, Zhe & Geng, Yong & Adams, Michelle & Dong, Liang & Sun, Lina & Zhao, Jingjing & Dong, Huijuan & Wu, Jiao & Tian, Xu, 2016. "Uncovering driving forces on greenhouse gas emissions in China’ aluminum industry from the perspective of life cycle analysis," Applied Energy, Elsevier, vol. 166(C), pages 253-263.
    14. Wu, Dong & Geng, Yong & Pan, Hengyu, 2021. "Whether natural gas consumption bring double dividends of economic growth and carbon dioxide emissions reduction in China?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
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