Towards an integrated approach for zero coal mine waste storage: solutions based on materials circularity and sustainable resource governance
Bibliographic record
Abstract
Around 25 million tons of coal mine waste rock (CMWR) are stored in many places in Morocco due to coal mining activities. As a result, air and water quality of the neighborhood is polluted and large lands are occupied. This study aimed to investigate the use of an integrated and circular approach based on coal recovery and waste rock recycling. More than 30 drill core samples were taken from the big coal dump reaching a depth of 60 m and analyzed to evaluate the chemical composition variability. Froth flotation was used to recover coal particles using diesel as a collector and Methyl Isobutyl Carbinol as a frother, 100 g/t each. The tailings of coal flotation process (CFT) were used to manufacture fired bricks at a pilot scale. The results of this study highlighted the possibility to valorize the whole waste material toward an objective of zero waste in the future. On a basis of 100t feed, (i) 10-15t can be recovered as high-quality anthracite coal with a calorific value over 7500 kcal/kg using flotation processing at a recovery yield over 80%, (ii) 45-60t can be reused as shales for bricks production with a compressive strength over 16MPa, (iii) 20-30t can be reused as aggregates for concrete production with a compressive strength over 20MPa. The remaining material can be reused as sand. The recovered anthracite can be reused to manufacture coal briquettes or used at it is in the thermal power plant next to the dump site.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".