Atmospheric Deposition of Mercury and Methylmercury to Landscapes and Waterbodies of the Athabasca Oil Sands Region
Bibliographic record
Abstract
Atmospheric deposition of metals originating from a variety of sources, including bitumen upgrading facilities and blowing dusts from landscape disturbances, is of concern in the Athabasca oil sands region of northern Alberta, Canada. Mercury (Hg) is of particular interest as methylmercury (MeHg), a neurotoxin which bioaccumulates through foodwebs, can reach levels in fish and wildlife that may pose health risks to human consumers. We used spring-time sampling of the accumulated snowpack at sites located varying distances from the major developments to estimate winter 2012 Hg loadings to a ∼20 000 km(2) area of the Athabasca oil sands region. Total Hg (THg; all forms of Hg in a sample) loads were predominantly particulate-bound (79 ± 12%) and increased with proximity to major developments, reaching up to 1000 ng m(-2). MeHg loads increased in a similar fashion, reaching up to 19 ng m(-2) and suggesting that oil sands developments are a direct source of MeHg to local landscapes and water bodies. Deposition maps, created by interpolation of measured Hg loads using geostatistical software, demonstrated that deposition resembled a bullseye pattern on the landscape, with areas of maximum THg and MeHg loadings located primarily between the Muskeg and Steepbank rivers. Snowpack concentrations of THg and MeHg were significantly correlated (r = 0.45-0.88, p < 0.01) with numerous parameters, including total suspended solids (TSS), metals known to be emitted in high quantities from the upgraders (vanadium, nickel, and zinc), and crustal elements (aluminum, iron, and lanthanum), which were also elevated in this region. Our results suggest that at snowmelt, a complex mixture of chemicals enters aquatic ecosystems that could impact biological communities of the oil sands region.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".