Spatial distribution of selenium and other potentially toxic elements surrounding mountaintop coal mines in the Elk Valley, British Columbia, Canada
Bibliographic record
Abstract
Despite the extensive use of mountaintop coal mining in the Elk Valley, British Columbia, Canada's largest metallurgical coal-producing region, little is known about the transport and deposition of fugitive dust emissions within its mountain landscape. This study aimed to assess the extent and spatial distribution of selenium and other potentially toxic elements (PTEs) near the town of Sparwood originating from fugitive dust emitted from two mountaintop coal mines. To achieve these objectives concentrations of 47 elements within moss tissues of Hylocomium splendens , Pleurozium schreberi , and Ptilium crista-castrensis were analyzed from 19 locations between May 29 to June 1, 2022. Contamination factors were then calculated to identify areas of contamination, along with generalized additive models to assess the relationship between selenium and the mines. Finally, Pearson correlation coefficients were calculated between selenium and other PTEs to determine which exhibited similar behaviour. This study found that selenium concentrations are a function of proximity to mountaintop mines, and the region's topographic features and prevailing wind patterns play a role in the transport and deposition of fugitive dust. Contamination is highest immediately surrounding mines and decreases at increasing distances, with the region's steep mountain ridges shielding the deposition of some fugitive dust when acting as a geographic barrier between adjacent valleys. Furthermore, silver, germanium, nickel, uranium, vanadium, and zirconium were identified as other PTEs of concern. The implications of this study are significant as it demonstrated the extent and spatial distribution of contaminants originating from fugitive dust emissions surrounding mountaintop mines and some of the controls to its distribution in mountain regions. As Canada and other mining jurisdictions look to expand critical mineral development, it will be important for proper risk assessment and mitigation in mountain regions to limit community and environmental exposure to contaminants within fugitive dust.
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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 | 0.001 | 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) | 0.001 | 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 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".