Occurrence, characterization, and ecological risk analysis of petroleum hydrocarbons in water and sediments following large-scale field simulated oil spills at the experimental lakes area, Northwestern Ontario, Canada
Bibliographic record
Abstract
This study assessed the impact of on-site field-simulated oil spills at the International Institute for Sustainable Development-Experimental Lakes Area (IISD-ELA) on a freshwater boreal lake. Low total petroleum hydrocarbons (TPH) values were obtained in water and sediments from the locations without direct oil loading across the 6-year monitoring program. Biogenic n -alkanes and pyrogenic polycyclic aromatic hydrocarbons (PAHs) were predominant pre- and post-spill. No petroleum biomarkers were detected in the water, but trace levels appeared in a few sediments. Most TPH and PAH levels were within acceptable limits set by the Canadian Council of Ministers of the Environment (CCME) and Ontario regulations, though some PAHs exceeded guidelines. However, the frequency of exceedances did not change significantly before and after the spill. These results suggest that the spilled oil was contained effectively during the experiment period, and the environment recovered to near-background levels afterward with appropriate precautions and remediation operations. • Six years of field surveys were conducted before and after simulated oil spill projects. • Biogenic and pyrogenic inputs are primary for n-alkanes and PAHs, respectively. • All TPH and most PAH values are lower than the national and provincial guidelines. • The frequency of PAH guideline exceedances remains largely unchanged throughout the 6 years. • The area used for simulated oil spills was unaffected by project operations.
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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 | 0.000 | 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) | 0.000 | 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 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".