Greenhouse gas and pollutant distribution from the supply chain of lithium-ion batteries for the German and European EV market
Bibliographic record
Abstract
This study examines the geographic distribution of greenhouse gas (GHG) and pollutant emissions in the lithium-ion battery (LIB) supply chain for the global electric vehicle (EV) market. Electrification of vehicles and the shift toward decarbonized energy sources are concentrating a greater share of emissions in the production phase. Using life cycle assessment (LCA) data and country-specific emission tables, emissions from mining, refining, cell manufacturing, and battery assembly were allocated to production regions for the reference year 2019. Results show that China dominates battery cell production (44%) and accounts for 54% of CO2eq emissions. In contrast, regions like Canada and Europe exhibit lower emission intensity. These findings underscore the role of regional energy mixes and production efficiencies in LIB supply chain emissions. Future strategies should focus on decarbonizing supply chains, diversifying production locations, and adopting cleaner energy sources globally.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".