Paleolimnological evaluation of metal(loid) enrichment from oil sands and gold mining operations in northwestern Canada
Bibliographic record
Abstract
Abundant reserves of metals and oil have spurred large-scale mining developments across northwestern Canada during the past 80 years. Historically, the associated emissions footprint of hazardous metal(loid)s has been difficult to identify, in part, because monitoring records are too short and sparse to have characterized their natural concentrations before mining began. Stratigraphic analysis of lake sediment cores has been employed where concerns of pollution exist to determine pre-disturbance metal(loid) concentrations and quantify the degree of enrichment since mining began. Here, we synthesize the current state of knowledge via systematic re-analysis of temporal variation in sediment metal(loid) concentrations from 51 lakes across four key regions spanning 670 km from bitumen mining in the Alberta Oil Sands Region (AOSR) to gold mining (Giant and Con mines) at Yellowknife in central Northwest Territories. Our compilation includes upland and floodplain lakes at varying distances from the mines to evaluate dispersal of pollution-indicator metal(loid)s from bitumen (vanadium and nickel) and gold mining (arsenic and antimony) via atmospheric and fluvial pathways. Results demonstrate 'severe' enrichment of vanadium and nickel at near-field sites (≤20 km) within the AOSR and 'severe' (near-field; ≤ 40 km) to 'considerable' (far-field; 40-80 km) enrichment of arsenic and antimony due to gold mining at Yellowknife via atmospheric pathways, but no evidence of enrichment of vanadium or nickel via atmospheric or fluvial pathways at the Peace-Athabasca Delta and Slave River Delta. Findings can be used by decision makers to evaluate risks associated with contaminant dispersal by the large-scale mining activities. In addition, we reflect upon methodological approaches to be considered when evaluating paleolimnological data for evidence of anthropogenic contributions to metal(loid) deposition and advocate for proactive inclusion of paleolimnology in the early design stage of environmental contaminant monitoring programs.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".