Digital product passport data to improve the material flow and stock monitoring and projections at EU-level: the case of EV-batteries

Macro-monitoring of material flows and stocks enables policy-makers to evaluate progress towards meeting its resource use-related commitments. Additionally, it allows to revise the products’ circularity requirements laid down in the regulations based on realistic scenarios on a societal scale. Current monitoring practices often rely on non-specific and not regularly updated data. This study examines whether the current practices satisfy the need to create realistic policies, by the case of electric vehicle batteries. A prospective material system analysis is conducted to evaluate the uncertainties in the existing data for macro-monitoring the availability of recycled lithium by 2030. The information is crucial for revising the recycled content requirements in regulation (EU) no. 2023/1542 concerning batteries and waste batteries. The analysis concludes that considerable uncertainty is associated with projecting recycled lithium availability, due to the variability in battery composition and lifespan. The study emphasizes the need to mitigate the uncertainties associated with the expected material outflows from the urban mine, in order to establish realistic recycled lithium content requirements. The recently introduced regulation also mandates battery producers to disclose sustainability-related information via a digital product passport (DPP). This paper proposes an approach for leveraging DPP-information to enhance the material flow and stock monitoring and projections, thereby facilitating well-informed policy-making, to create executable eco-design guidelines.

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Publication Details

Journal
Procedia CIRP
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procir.2024.12.057
Citations
1
Primary Topic
Extraction and Separation Processes
Type
article
Field-Weighted Citation Impact
0.71

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article

Digital product passport data to improve the material flow and stock monitoring and projections at EU-level: the case of EV-batteries

K.M.B. Jansen, J. Lennartz, Elmer Rietveld
1 citations
Procedia CIRP
Extraction and Separation Processes
0.71
article

Digital product passport data to improve the material flow and stock monitoring and projections at EU-level: the case of EV-batteries

K.M.B. Jansen, J. Lennartz, Elmer Rietveld
article en
1 citations

Abstract

Macro-monitoring of material flows and stocks enables policy-makers to evaluate progress towards meeting its resource use-related commitments. Additionally, it allows to revise the products’ circularity requirements laid down in the regulations based on realistic scenarios on a societal scale. Current monitoring practices often rely on non-specific and not regularly updated data. This study examines whether the current practices satisfy the need to create realistic policies, by the case of electric vehicle batteries. A prospective material system analysis is conducted to evaluate the uncertainties in the existing data for macro-monitoring the availability of recycled lithium by 2030. The information is crucial for revising the recycled content requirements in regulation (EU) no. 2023/1542 concerning batteries and waste batteries. The analysis concludes that considerable uncertainty is associated with projecting recycled lithium availability, due to the variability in battery composition and lifespan. The study emphasizes the need to mitigate the uncertainties associated with the expected material outflows from the urban mine, in order to establish realistic recycled lithium content requirements. The recently introduced regulation also mandates battery producers to disclose sustainability-related information via a digital product passport (DPP). This paper proposes an approach for leveraging DPP-information to enhance the material flow and stock monitoring and projections, thereby facilitating well-informed policy-making, to create executable eco-design guidelines.

Procedia CIRPVol. 135
Utrecht University (NL)
European Commission
Openalex Percentile: Top 29%
Extraction and Separation Processes
0.71
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