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Author:

Du, Shiwei (Du, Shiwei.) | Gao, Feng (Gao, Feng.) | Nie, Zuoren (Nie, Zuoren.) (Scholars:聂祚仁) | Liu, Yu (Liu, Yu.) | Sun, Boxue (Sun, Boxue.) | Gong, Xianzheng (Gong, Xianzheng.)

Indexed by:

EI Scopus SCIE

Abstract:

Power lithium-ion batteries (LIBs) are an important component of carbon neutrality in the transportation sector. The rapid growth of the LIB recycling industry is driven by various factors, such as resource scarcity. As a process interacting upstream and downstream, LIB recycling must consider the impact of the application of modeling approaches on the allocation of environmental benefits and burdens, especially at a time when carbon emissions are highly correlated with profit. In this study, seven allocation methods were chosen and applied to the production and multiple recycling process of typical LIB on the same data basis. The application of different allocation methods produced very disparate allocation results, and the conclusions of previous studies comparing the environmental performance of battery types need to be revisited. The life-cycle assessment (LCA) results should be interpreted with caution due to the impact of the allocation methods. Furthermore, a multi-indicator qualitative analysis based on product and process characteristics compares the applicability of the allocation methods to different aspects of LIB recycling. Relevant product standards for batteries should consider the characteristics of different methods and recommend a specific allocation method for the LCA community to employ in time to ensure that relevant studies are representative and comparable.

Keyword:

allocation EVs lithium-ion battery recycling environmental impact life-cycle assessment

Author Community:

  • [ 1 ] [Du, Shiwei]Beijing Univ Technol, Fac Mat & Mfg, Natl Engn Lab Ind Big Data Applicat Technol, Beijing 100124, Peoples R China
  • [ 2 ] [Gao, Feng]Beijing Univ Technol, Fac Mat & Mfg, Natl Engn Lab Ind Big Data Applicat Technol, Beijing 100124, Peoples R China
  • [ 3 ] [Nie, Zuoren]Beijing Univ Technol, Fac Mat & Mfg, Natl Engn Lab Ind Big Data Applicat Technol, Beijing 100124, Peoples R China
  • [ 4 ] [Liu, Yu]Beijing Univ Technol, Fac Mat & Mfg, Natl Engn Lab Ind Big Data Applicat Technol, Beijing 100124, Peoples R China
  • [ 5 ] [Sun, Boxue]Beijing Univ Technol, Fac Mat & Mfg, Natl Engn Lab Ind Big Data Applicat Technol, Beijing 100124, Peoples R China
  • [ 6 ] [Gong, Xianzheng]Beijing Univ Technol, Fac Mat & Mfg, Natl Engn Lab Ind Big Data Applicat Technol, Beijing 100124, Peoples R China

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Source :

ENVIRONMENTAL SCIENCE & TECHNOLOGY

ISSN: 0013-936X

Year: 2022

Issue: 24

Volume: 56

Page: 17977-17987

1 1 . 4

JCR@2022

1 1 . 4 0 0

JCR@2022

ESI Discipline: ENVIRONMENT/ECOLOGY;

ESI HC Threshold:47

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count: 19

SCOPUS Cited Count: 23

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 9

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