Bench- and field-scale trials of in-situ biological treatment of cadmium and zinc in flooded mine workings, Northern Canada
Bibliographic record
Abstract
Passive and semi-passive treatment of underground mine waters provides a low cost, low maintenance alternative to active treatment; however, such non-traditional approaches often require pilot testwork to ensure regulator and stakeholder acceptance. Here we describe two examples of laboratory- and field-based studies of in-situ treatment of mine workings water. To support closure planning of an unnamed mine in British Columbia, 200 L mesocosms comprising synthetic mine water (SMW), waste rock, and cemented tailings that will backfill the mine at closure were prepared. These were amended with glycerol or ethanol, resulting in sulphate-reducing conditions under which constituents of concern (COCs) such as antimony (average initial concentration of 1.9 mg/L), cadmium (0.088 mg/L), selenium (0.039 mg/L), and zinc (5.0 mg/L) exhibited marked peak removal (>99%, >99%, 99%, and 95%, respectively relative to control trial). Sustained treatment below the discharge standards was achieved by the end of the 26-week experiment. Glycerol-amended trials exhibited the greatest treatment, likely related to the higher abundance and diversity of sulphide-producing and selenium-reducing bacteria observed in these trials. At the historical Silver King mine (Yukon), in-situ treatment has been ongoing since October 2014 and provides a field-scale exemplar for this treatment approach in a remote, cold climate setting. Molasses injection to the flooded underground mine workings resulted in rapid removal (>90%) of COCs cadmium and zinc. Multiple injection events in the first year of operation created sustained sulphate-reducing conditions with an attendant shift in the microbial community structure towards the naturally occurring sulphide-producing bacteria key to the treatment process. Following such initial ‘commissioning’, biennial methanol injections have maintained metal concentrations in the adit discharge below effluent quality standards since 2016. Such laboratory- and field-based demonstrations provide important information regarding the inclusion of in-situ treatment in the toolbox of long-term treatment options for mine closure.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".