Environmental geochemistry of tailings, sediments and surface waters collected from 14 historical gold mining districts in Nova Scotia
Bibliographic record
Abstract
From 1861 to the mid-1940s, stamp milling at orogenic lode gold mines in Nova Scotia generated more than 3,000,000 tonnes of tailings. Most of the mined gold was recovered using mercury (Hg) amalgamation, and an estimated 10 - 25% of the Hg used was lost to the tailings and to the atmosphere. Arsenic (As) also occurs naturally in the ore, and is present at high concentrations in the mine wastes. Tailings from these operations were generally slurried into local rivers, swamps, lakes and the ocean. Recent land-use changes (e.g. residential development, recreational activities, shellfish harvesting) in some historical mining districts are increasing the likelihood of human exposure to these tailings. This Open File Report presents the results of a multi-disciplinary investigation of the dispersion, speciation and fate of metal(loid)s in terrestrial and shallow marine environments surrounding 14 abandoned gold mines in Nova Scotia. From 2003 to 2006, samples of tailings, sediment, and water were collected at 14 former gold mines. Field studies reveal that most mine sites contain large volumes of unconfined tailings, and in several districts these have been transported significant distances (>2 km) offsite by streams and rivers. Chemical analyses of 482 tailings and sediment samples show high concentrations of As (10 mg/kg to 31 wt.%; median 2550 mg/kg) and Hg (<5 ug/kg to 350 mg/kg; median 1640 ug/kg). Arsenic is hosted in arsenopyrite and a variety of secondary phases including scorodite (FeAsO4·2H2O), amorphous Fe arsenate, and As bound to Fe oxyhydroxides. Mercury is present in elemental form, amalgam (AuxHgx), and in secondary phases. Results from this study led to the formation of a Provincial-Federal Historic Gold Mines Advisory Committee in 2005, which has evaluated the ecological and human health risks associated with gold mines throughout Nova Scotia and developed recommendations for management of these tailings sites. This Open File Report provides the most comprehensive summary available of the history, distribution, and geochemistry of tailings at gold mines throughout Nova Scotia. The geographic coordinates provided for each district can be used to quickly explore the tailings deposits via most web-based mapping services. The results can be used to help minimize the environmental impacts associated with past, present, and future gold extraction and to inform land-use decisions.
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How this classification was reachedexpand
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) | 0.003 | 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 teacher head, 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".