Sustainable Production of Rare Earth Elements from Mine Waste and Geoethics
Bibliographic record
Abstract
The vulnerability of the rare earth element (REE) supply in a global context of increasing demands entails important economic and political issues, and has encouraged several countries to develop their own REE production projects. This study comparatively evaluated the production of REEs from primary and secondary resources in terms of their sustainability and contribution to the achievement of the Geoethics concept as responsibility towards oneself, colleagues, society, and the Earth system. Twelve categories of potential environmental and social impacts were selected: human health toxicity, global warming or climate change, terrestrial and aquatic eutrophication, acidification potential, particulate matter, resource depletion, water consumption, fresh water ecotoxicity, ionizing radiation, fossil fuel consumption, and ozone depletion. The results showed that the environmental impact of REE production from secondary sources is much lower relative to primary sources. A comparison of conventional and non-conventional REE resources showed that significant impact categories were related to particulate matter formation, abiotic resource depletion, and fossil fuel depletion, which could result from avoiding the tailings disposal before reuse. Based on these findings, governments and stakeholders should be encouraged to increase the recycling of secondary REE sources with Geoethics in mind, in order to balance the high demand of REEs while minimizing the overexploitation of non-renewable resources.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".