In-situ bitumen extraction associated with increased petrogenic polycyclic aromatic compounds in lake sediments from the Cold Lake heavy oil fields (Alberta, Canada)
Bibliographic record
Abstract
Most future growth in the Alberta bituminous sands will be based on thermal in-situ recovery technologies. To date, however, most attention on the environmental effects of bitumen recovery has focused on surface mining in the Athabasca region. Recent uncontrolled bitumen flow-to-surface incidents (FTS; appearance at the surface of bitumen emulsions from deep subsurface recovery zones) reported at the Cold Lake heavy oil fields highlight the need to better understand the potential role of in-situ extraction as a source of contaminants to landscapes and surface waters. We analyzed sediment cores from a lake located ∼2 km away from a recent bitumen FTS incident to provide a long-term perspective on the delivery of metals, polycyclic aromatic compounds (PACs), and polychlorinated biphenyls (PCBs) to surface freshwaters, and to assess whether the onset of local in-situ bitumen extraction can be linked to contaminant increases in nearby lakes. An increase in alkyl PACs coincided with the onset and expansion of commercial in-situ bitumen extraction, and multiple lines of evidence indicate a petrogenic source for recent alkyl PAC enrichment. However, no coincident increase in vanadium (enriched in bitumen) occurred that would suggest the source of petrogenic PAC enrichment is direct input of bituminous particles. Our results show that, similar to surface mining in the Athabasca region, activities associated with in-situ extraction can increase the burden of petrogenic PACs in nearby lakes, but many questions still remain regarding the exact sources and pathways of PACs into the environment. Given that more than 80% of Alberta's bitumen reserves can only be accessed using in-situ technologies, we recommend that this be made a research priority.
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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 | 0.002 | 0.001 |
| 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".