Spatio-temporal variations in dissolved trace elements in peat bog porewaters impacted by dust inputs from open-pit mining activities in the Athabasca Bituminous Sands (ABS) region
Bibliographic record
Abstract
Considerable volumes of dust are generated from open-pit bitumen mining operations in northern Alberta, Canada. The reactive mineral phases of these dust particles can potentially dissolve in acidic (pH < 4) bog waters. Their dissolution could release trace elements (TEs), which could eventually alter these bog ecosystems. The impact of dust dissolution on the abundance of TEs in the dissolved (<0.45 μm) fraction of porewaters from excavated pits (30-40 cm deep) in the ombrogenic zone of five peatlands was evaluated. Porewaters were collected from four bogs situated within 70 km of mines and upgraders in the Athabasca Bituminous Sands (ABS) region, Alberta, Canada, and from a reference bog situated 264 km away. Over two consecutive years, the dissolved concentrations of some conservative (Al, Th, Y) and mobile lithophile elements (Fe, Li, Mn, Sr), as well as the metals enriched in bitumen (V, Ni, Mo), all increased with proximity to the mining area, in the ABS region. These trends reflect the observed increase in dust deposition with proximity to the mining area from independent studies of snow, lichens, and Sphagnum moss. Contrarily, the impact of dust dissolution on the concentration of potentially toxic TEs (As, Cd, Pb, Sb, and Tl) was negligible. Thus, the elements which are more abundant in the porewaters near industry are either ecologically benign (e.g. Li and Sr) or essential micronutrients (e.g. Fe, Mn, Ni, and Mo). Manganese was the only element which was enriched by more than 10x at all sites near the mining area, compared to its concentration at the reference site. The enrichments of all other elements were <10x, indicating that anthropogenic dust emissions from mining areas have had only a modest effect on the TEs abundance in peat porewaters.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".