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Optimizing the aluminum supply chain network subject to the uncertainty of carbon emissions trading market

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  • Guo, Ying
  • Zhou, Wenji
  • Ren, Hongtao
  • Yu, Yadong
  • Xu, Lei
  • Fuss, Maryegli

Abstract

Aluminum production is characterized by high electricity consumption; hence its decarbonization hinges on upstream low-carbon electricity generation. As a result, the supply chain of aluminum product manufacturing can be strongly affected by the uncertainty of carbon emissions price via electricity generation. This paper investigates these impacts on the strategic design and the tactic operations of the aluminum supply chain by constructing a stochastic mixed-integer linear programming (SMILP) model, in which carbon price uncertainty and demand uncertainty are both accounted for. The supply chain case in the study covers a full process from upstream power generation to end-use consumption. A variety of stochastic carbon price scenarios are designed and assessed. Sensitivity analysis with respect to demand fluctuation is also performed. The results show that carbon price uncertainty significantly affects the configuration of the whole system. The main driving forces are the supplier selection and configuration alteration triggered by the carbon price variation, whereas other metrics such as carbon emissions costs and the responses to demand fluctuations display complicated patterns of change. This study provides a useful analytical framework that can be applied to the planning problem for other industries facing the same challenge.

Suggested Citation

  • Guo, Ying & Zhou, Wenji & Ren, Hongtao & Yu, Yadong & Xu, Lei & Fuss, Maryegli, 2023. "Optimizing the aluminum supply chain network subject to the uncertainty of carbon emissions trading market," Resources Policy, Elsevier, vol. 80(C).
  • Handle: RePEc:eee:jrpoli:v:80:y:2023:i:c:s0301420722006900
    DOI: 10.1016/j.resourpol.2022.103247
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    1. Ahmad Rezaee & Farzad Dehghanian & Behnam Fahimnia & Benita Beamon, 2017. "Green supply chain network design with stochastic demand and carbon price," Annals of Operations Research, Springer, vol. 250(2), pages 463-485, March.
    2. Orji, Ifeyinwa Juliet & Liu, Shaoxuan, 2020. "A dynamic perspective on the key drivers of innovation-led lean approaches to achieve sustainability in manufacturing supply chain," International Journal of Production Economics, Elsevier, vol. 219(C), pages 480-496.
    3. Moretti, Luca & Milani, Mario & Lozza, Giovanni Gustavo & Manzolini, Giampaolo, 2021. "A detailed MILP formulation for the optimal design of advanced biofuel supply chains," Renewable Energy, Elsevier, vol. 171(C), pages 159-175.
    4. Coelho, António & Iria, José & Soares, Filipe, 2021. "Network-secure bidding optimization of aggregators of multi-energy systems in electricity, gas, and carbon markets," Applied Energy, Elsevier, vol. 301(C).
    5. Ma, Yiqun & Wang, Junhao, 2021. "Time-varying spillovers and dependencies between iron ore, scrap steel, carbon emission, seaborne transportation, and China's steel stock prices," Resources Policy, Elsevier, vol. 74(C).
    6. Kannan, Devika & Diabat, Ali & Alrefaei, Mahmoud & Govindan, Kannan & Yong, Geng, 2012. "A carbon footprint based reverse logistics network design model," Resources, Conservation & Recycling, Elsevier, vol. 67(C), pages 75-79.
    7. Ke Wang & Linan Che & Chunbo Ma & Yi-Ming Wei, 2017. "The Shadow Price of CO2 Emissions in China's Iron and Steel Industry," CEEP-BIT Working Papers 105, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    8. Zhou, Wenji & Jiang, Di & Chen, Dingjiang & Griffy-Brown, Charla & Jin, Yong & Zhu, Bing, 2016. "Capturing CO2 from cement plants: A priority for reducing CO2 emissions in China," Energy, Elsevier, vol. 106(C), pages 464-474.
    9. Amin Chaabane & Amar Ramudhin & Mourad Kharoune & Marc Paquet, 2011. "Trade-off model for carbon market sensitive green supply chain network design," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 10(4), pages 416-441.
    10. Hongtao Ren & Wenji Zhou & Ying Guo & Lizhen Huang & Yongping Liu & Yadong Yu & Liyun Hong & Tieju Ma, 2020. "A GIS-based green supply chain model for assessing the effects of carbon price uncertainty on plastic recycling," International Journal of Production Research, Taylor & Francis Journals, vol. 58(6), pages 1705-1723, March.
    11. Adekoya, Oluwasegun B. & Oliyide, Johnson A. & Noman, Ambreen, 2021. "The volatility connectedness of the EU carbon market with commodity and financial markets in time- and frequency-domain: The role of the U.S. economic policy uncertainty," Resources Policy, Elsevier, vol. 74(C).
    12. Chen, Wei-Qiang & Graedel, T.E., 2012. "Dynamic analysis of aluminum stocks and flows in the United States: 1900–2009," Ecological Economics, Elsevier, vol. 81(C), pages 92-102.
    13. Hammami, Ramzi & Nouira, Imen & Frein, Yannick, 2015. "Carbon emissions in a multi-echelon production-inventory model with lead time constraints," International Journal of Production Economics, Elsevier, vol. 164(C), pages 292-307.
    14. Chen, Weiqiang & Shi, Lei & Qian, Yi, 2010. "Substance flow analysis of aluminium in mainland China for 2001, 2004 and 2007: Exploring its initial sources, eventual sinks and the pathways linking them," Resources, Conservation & Recycling, Elsevier, vol. 54(9), pages 557-570.
    15. Yin, Jiuli & Zhu, Yan & Fan, Xinghua, 2021. "Correlation analysis of China’s carbon market and coal market based on multi-scale entropy," Resources Policy, Elsevier, vol. 72(C).
    16. Bartolini, Andrea & Mazzoni, Stefano & Comodi, Gabriele & Romagnoli, Alessandro, 2021. "Impact of carbon pricing on distributed energy systems planning," Applied Energy, Elsevier, vol. 301(C).
    17. Zakeri, Atefe & Dehghanian, Farzad & Fahimnia, Behnam & Sarkis, Joseph, 2015. "Carbon pricing versus emissions trading: A supply chain planning perspective," International Journal of Production Economics, Elsevier, vol. 164(C), pages 197-205.
    18. Ahdab, Yvana D. & Schücking, Georg & Rehman, Danyal & Lienhard, John H., 2021. "Cost effectiveness of conventionally and solar powered monovalent selective electrodialysis for seawater desalination in greenhouses," Applied Energy, Elsevier, vol. 301(C).
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