Oil sands development contributes polycyclic aromatic compounds to the Athabasca River and its tributaries
Bibliographic record
Abstract
For over a decade, the contribution of oil sands mining and processing to the pollution of the Athabasca River has been controversial. We show that the oil sands development is a greater source of contamination than previously realized. In 2008, within 50 km of oil sands upgrading facilities, the loading to the snowpack of airborne particulates was 11,400 T over 4 months and included 391 kg of polycyclic aromatic compounds (PAC), equivalent to 600 T of bitumen, while 168 kg of dissolved PAC was also deposited. Dissolved PAC concentrations in tributaries to the Athabasca increased from 0.009 microg/L upstream of oil sands development to 0.023 microg/L in winter and to 0.202 microg/L in summer downstream. In the Athabasca, dissolved PAC concentrations were mostly <0.025 microg/L in winter and 0.030 microg/L in summer, except near oil sands upgrading facilities and tailings ponds in winter (0.031-0.083 microg/L) and downstream of new development in summer (0.063-0.135 microg/L). In the Athabasca and its tributaries, development within the past 2 years was related to elevated dissolved PAC concentrations that were likely toxic to fish embryos. In melted snow, dissolved PAC concentrations were up to 4.8 microg/L, thus, spring snowmelt and washout during rain events are important unknowns. These results indicate that major changes are needed to the way that environmental impacts of oil sands development are monitored and managed.
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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 | 0.001 |
| 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".