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Influence of Different Allocation Methods for Recycling and Dynamic Inventory on CO 2 Savings and Payback Times of Light-Weighted Vehicles Computed under Product- and Fleet-Based Analyses: A Case of Internal Combustion Engine Vehicles

Author

Listed:
  • Pasan Dunuwila

    (Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-0041, Japan)

  • Ko Hamada

    (Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-0041, Japan)

  • Kentaro Takeyama

    (Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-0041, Japan)

  • Daryna Panasiuk

    (Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-0041, Japan)

  • Takeo Hoshino

    (Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-0041, Japan)

  • Shinichiro Morimoto

    (National Institute of Advanced Industrial Science and Technology, Ibaraki 305-8569, Japan)

  • Kiyotaka Tahara

    (National Institute of Advanced Industrial Science and Technology, Ibaraki 305-8569, Japan)

  • Ichiro Daigo

    (Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-0041, Japan)

Abstract

Light weighting by material substitution is a key to reducing GHG emissions during vehicle operation. The GHG benefits are a salient factor in selecting lightweight materials for vehicles. Although the literature has performed lightweight material selections using GHG benefits under product- and fleet-based life-cycle inventory (LCI) analyses, recycling effects have therein been accounted for by arbitrarily selecting allocation methods for recycling, as the consensus on their selection is absent. Furthermore, studies have mistreated the temporal variations of the LCI parameters (the dynamic inventory (DI)), though that could be an important factor affecting the overall LCI results when allocation methods for recycling are in place. Therefore, to investigate their influence on greenhouse gas (GHG) benefit evaluations, an LCI case study was conducted, centered on aluminum- and magnesium-substituted internal combustion engine vehicles (ICEVs) at the product- and fleet- levels. “CO 2 savings” and the “CO 2 payback time”, as well as four allocation methods for recycling, were considered to represent the GHG benefits and address the recycling effects, respectively. The dynamic inventory was based on the world average electricity grid mix change. The results indicate that changing the conditions of the DI and the allocation methods for recycling could alter the better performing material under fleet-based analyses. Therefore, we ascertained that the choice of the allocation method for recycling and conducting fleet-scale dynamic LCI analyses in the presence of the DI is pivotal for material selections.

Suggested Citation

  • Pasan Dunuwila & Ko Hamada & Kentaro Takeyama & Daryna Panasiuk & Takeo Hoshino & Shinichiro Morimoto & Kiyotaka Tahara & Ichiro Daigo, 2021. "Influence of Different Allocation Methods for Recycling and Dynamic Inventory on CO 2 Savings and Payback Times of Light-Weighted Vehicles Computed under Product- and Fleet-Based Analyses: A Case of I," Sustainability, MDPI, vol. 13(24), pages 1-17, December.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:24:p:13935-:d:704278
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