Regulations and Policies on the Management of the End of the Life of Lithium-Ion Batteries in Electrical Vehicles
Bibliographic record
Abstract
Electrical vehicle (EV) batteries, particularly lithium-ion batteries, pose significant environmental challenges due to their hazardous components, the effects of initial building-material fabrication, and the difficulties of recycling and disposal. Policies and legislative strategies adopted by different governments to solve these issues are investigated in this manuscript, specifically based on circularity and resource use. Important steps are end-of-life management, safe disposal and transportation, avoidance of hazardous gas emissions, circularity, resource use, fire prevention, and expanded producer accountability. As of February 2024, New Jersey is the first and only state in the United States that has adopted a thorough legislative framework for EV battery management, therefore establishing a standard for other states. California passed major laws encouraging Zero-Emission Vehicle (ZEV) battery manufacture and recycling. Other states are likewise trying to show initiative by implementing and changing laws. Globally, the European Union is leading, while Canada, Australia, China, and others have created strong rules of regulation. This paper looks at and contrasts the environmental problems of lithium-ion electric vehicles with the legislative actions made by different nations and states to solve these problems. By means of a thorough examination of these policies, this paper seeks to present a whole picture of the current scene and the best techniques for lifetime management of EV batteries that can be embraced by different governments. In this manuscript, a comparison is made between two leading legislations, specifically that of the state of New Jersey and the European Union. To achieve the most beneficial outcome, it is the responsibility of stakeholders to promote rules; emphasize battery recycling, secure disposal, and extended producer accountability; promote innovation in sustainable battery technology; and try to build a pragmatic approach to battery management to mitigate environmental impacts based on a hybrid version of the legislations from the state of New Jersey and the European Union.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".