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A mechanistic model to link technical specifications of vehicle end‐of‐life treatment with the potential of closed‐loop recycling of post‐consumer scrap alloys

Author

Listed:
  • Qingshi Tu
  • Edgar G. Hertwich

Abstract

Closed‐loop recycling of scrap from end‐of‐life (EoL) vehicles could reduce the demand for virgin material production and associated greenhouse gas (GHG) emissions. However, current modeling frameworks for closed‐loop recycling lack a mechanistic representation of the linkage between the changes in scrap quality (i.e., alloying element composition) and the EoL treatment practices, demonstrating a challenge to comprehensively assess the merits of closed‐loop recycling. The Vehicle Recycling LCA model (VehiReLCA) was developed to address this challenge by parameterizing the key factors involved in the EoL treatment steps, quantifying their influences on the alloying composition of resulting scrap ingots and ultimately, the associated closed‐loop utilization ratios and life cycle GHG emissions. A series of scenarios were investigated, representing a wide range of results that originated from different assumptions of scrap mixing, sorting efficiency, and remelting for six vehicle archetypes. Based on the prevailing assumption of constant closed‐loop utilization ratios in the literature, the life cycle GHG emissions for conventional (lightweight) internal combustion engine vehicle, plug‐in electric vehicle and battery electric vehicle were 3788 (4598), 4136 (4799), and 3327 (4166) kg CO2‐eq per vehicle, respectively. In comparison, explicitly correlating the alloy compositions with random sorting error and/or cross‐mixing of vehicle components often led to an order of magnitude decrease in scrap utilization ratios. Accordingly, the increase in GHG emissions, compared to those estimated using constant utilization ratios, varied from 15%–47% (for all archetypes when 2% random sorting error was considered) to 64%–71% (for lightweight archetypes when the most heterogeneity of EoL treatment steps was assumed). This revealed a significant range of uncertainty regarding the GHG reduction benefits of closed‐loop recycling that was not previously identified in the literature.

Suggested Citation

  • Qingshi Tu & Edgar G. Hertwich, 2022. "A mechanistic model to link technical specifications of vehicle end‐of‐life treatment with the potential of closed‐loop recycling of post‐consumer scrap alloys," Journal of Industrial Ecology, Yale University, vol. 26(3), pages 704-717, June.
    • Handle: RePEc:bla:inecol:v:26:y:2022:i:3:p:704-717
    DOI: 10.1111/jiec.13223
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    References listed on IDEAS

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    1. Trevor Zink & Roland Geyer & Richard Startz, 2018. "Toward Estimating Displaced Primary Production from Recycling: A Case Study of U.S. Aluminum," Journal of Industrial Ecology, Yale University, vol. 22(2), pages 314-326, April.
    2. Stefan Pauliuk & Niko Heeren, 2020. "ODYM—An open software framework for studying dynamic material systems: Principles, implementation, and data structures," Journal of Industrial Ecology, Yale University, vol. 24(3), pages 446-458, June.
    3. Ohno, Hajime & Matsubae, Kazuyo & Nakajima, Kenichi & Kondo, Yasushi & Nakamura, Shinichiro & Nagasaka, Tetsuya, 2015. "Toward the efficient recycling of alloying elements from end of life vehicle steel scrap," Resources, Conservation & Recycling, Elsevier, vol. 100(C), pages 11-20.
    4. Sanfélix, Javier & Messagie, Maarten & Omar, Noshin & Van Mierlo, Joeri & Hennige, Volker, 2015. "Environmental performance of advanced hybrid energy storage systems for electric vehicle applications," Applied Energy, Elsevier, vol. 137(C), pages 925-930.
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    1. Zhiguo Wang & Cici Xiao He, 2025. "Decision-making of dual-channel reverse supply chain for end-of-life vehicles considering consumer preferences," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(9), pages 22475-22499, September.

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