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A Comprehensive Life Cycle Carbon Footprint Assessment Model for Electric Power Material Warehouses

Author

Listed:
  • Yongjun Luo

    (Jiangsu Anfang Power Technology Co., Ltd., Taizhou 225300, China
    These authors contributed equally to this work.)

  • Xinyi Tang

    (School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
    These authors contributed equally to this work.)

  • Lei Geng

    (State Grid Jiangsu Electric Power Co., Ltd., Nanjing 210018, China)

  • Xiang Yao

    (Yangzhou Power Supply Branch, State Grid Jiangsu Electric Power Co., Ltd., Yangzhou 225002, China)

  • Feihong Li

    (China-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Xudong Li

    (School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Qingrui Wang

    (School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
    State Key Laboratory of Coal Combustion, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

Electric power material warehouses are critical to optimizing power grid supply chains and reducing carbon emissions, aiding the power sector’s decarbonization and climate goals. Nevertheless, to our knowledge, there are no comprehensive assessments of the life cycle carbon emissions associated with storage warehouses, so the emission reduction potential of the ever-increasing number of automated technologies is still unknown. This study presents an extensive life cycle carbon footprint assessment model tailored for electric power material warehouses, and it encompasses both traditional and automated frameworks. Utilizing a process-based life cycle assessment (LCA) methodology, carbon emissions across five distinct stages are examined: storage buildings and facilities, loading and unloading, transportation, packaging, and information management systems. For this purpose, warehouses in Jiangsu Province, China, are employed as a case study. The results show that automating warehouses can achieve a reduction in total carbon emissions of 42.85% compared with traditional warehouses, with total life cycle emissions of 39,531.26 tCO 2 , and the transportation stage is identified as the predominant contributor. This research not only offers actionable recommendations for strategies, including renewable energy integration, intelligent control systems, and standardized packaging protocols, but also establishes a framework for future investigations of refining carbon accounting methodologies—particularly in underexplored domains such as packaging.

Suggested Citation

  • Yongjun Luo & Xinyi Tang & Lei Geng & Xiang Yao & Feihong Li & Xudong Li & Qingrui Wang, 2024. "A Comprehensive Life Cycle Carbon Footprint Assessment Model for Electric Power Material Warehouses," Energies, MDPI, vol. 17(24), pages 1-13, December.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:24:p:6352-:d:1545866
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    References listed on IDEAS

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    2. Bauer, Christian & Hofer, Johannes & Althaus, Hans-Jörg & Del Duce, Andrea & Simons, Andrew, 2015. "The environmental performance of current and future passenger vehicles: Life cycle assessment based on a novel scenario analysis framework," Applied Energy, Elsevier, vol. 157(C), pages 871-883.
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