Renewable energy in the mining industry: Status, opportunities and challenges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Currently, the mining sector is confronted with declining ore grades, volatile energy prices, and environmental pollution from massive carbon emissions. Due to the advantages of RE in terms of emission reduction and cost, some mining companies are actively exploring integrating RE in production to alleviate these challenges. At the same time, the integration of RE in mining sites also faces many obstacles. This paper highlights the importance of incorporating RE into mining projects through a comprehensive review of existing research and analyzes the opportunities and challenges from multiple perspectives. Finally, the conclusions summarize the gaps in existing work and provide appropriate recommendations. The paper aims to inform and provide implications for the transition to RE practices in the mining industry. • This paper highlights the importance of integrating renewable energy (RE) into mining projects by a comprehensive review. • The feasibility and application potential of integrating RE in the mining industry are analyzed from multiple perspectives. • The current techno-economic analysis and MCDM for the deployment of RE projects in the mining industry are reviewed. • The advantages and opportunities of RE in mining are summarized in four areas: economic, environmental, social and policy. • The barriers are analyzed from five perspectives: technology, expertise, financing, legislation and related interests.
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.
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 it