Effect of wetting and drying processes on ultramafic and mafic tailing minerals amended with topsoil
Bibliographic record
Abstract
Environmental context Mine tailings are a mixture of fine materials obtained after crushing, processing and extracting the valuable minerals from ore. Ultramafic and mafic mine tailings have the potential to mineralise carbon, offering a solution to offset greenhouse gas emissions from the mining sector. The study revealed that the effects of wetting and drying ultramafic and mafic mine tailings under atmospheric conditions have the potential for carbon sequestration and acid mine drainage. Rationale As the result of their carbon mineralisation potential, there is an increasing interest in using ultramafic and mafic (U+M) mine tailings as a feedstock for carbon (C) sequestration. However, little is known about the relative chemical stability of U+M minerals, and it is unclear whether acid mine drainage may be generated during weathering. Methodology This study determined the relative stability of the constituent minerals of several U+M tailings from mines in British Columbia, Canada, and Australia using selective chemical extractions and an 18-week laboratory experiment of cycles of wetting and drying to simulate conditions that may be experienced under field conditions. Tailings were mixed with topsoil to investigate the potential use as a soil amendment. Results Initially, the tailing sample’s pH was 8.4–9.7 and decreased to 7.7–9.1 over the 18 weeks. Soil additions lowered the initial pH and converged with the tailing’s pH over 18 weeks. Sequentially weathered minerals determined by X-ray diffraction were consistent with the empirical Goldich weathering sequence. Metal concentrations from inductively coupled plasma–mass spectrometry supported X-ray diffraction results, confirming the stability of the U+M tailings using different methods and the need for future studies on potential metal contamination. Discussion Minor concentrations of sulfur seemed to have resulted in larger fluctuations in pH when low amounts of carbonates were present. However, reactive oxides and basic cations in the U+M tailings maintained pH above 7. Therefore, C sequestration was likely supported, although there was a slight reduction in total C content for almost all samples. This study suggests future research is required under field conditions to confirm C sequestration and to investigate the use of U+M tailings for restoration applications.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".