NEUTRALIZATION OF ACID MINE DRAINAGE IN ANOXIC LIMESTONE DRAINS: A LABORATORY STUDY
Bibliographic record
Abstract
Oxidation of sulphidic mining waste can generate acidic leachate (called acid mine drainage AMD) that has the potential to seriously affect the nearby ecosystems. AMD is characterised by high acidity (pH often below 4) and high concentrations of sulphates and heavy metals. To reduce environmental impacts of AMD, neutralisation of the effluent using limestone drains is an option proposed in the literature and used around the world. This study focuses on the influence of the limestone mineralogy (calcite and dolomite) and the particles size of the material on the neutralising capacity of the system treatment. The tests were performed in two different anoxic conditions: in batch reactors, and in columns having a hydraulic retention time of 15 hours. The results showed that the neutralisation capacity of calcite is more important than that of dolomite, and that smaller particle size gives better alkalinity production (for a same calcite). The impact of particle size and mineralogy is different depending on AMD composition. The use of calcite and small particle size is more appropriate for low pH and high acidity AMD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".