Monitoring Perfluorinated Surfactants in Biota and Surface Water Samples Following an Accidental Release of Fire-Fighting Foam into Etobicoke Creek
Bibliographic record
Abstract
Perfluorinated surfactants have emerged as priority environmental contaminants due to recent reports of their detection in environmental and biological matrices as well as concerns regarding their persistence and toxicity. In June 2000, 22000 L of fire retardant foam containing perfluorinated surfactants was accidentally released at L. B. Pearson International Airport, Toronto, ON, and subsequently entered into Etobicoke Creek, a tributary to Lake Ontario. A suite of analytical tools that include liquid chromatography/tandem mass spectrometry (LC/MS/MS) and 19F NMR were employed to characterize fish (common shiner, Notropus cornutus) and surface water samples collected following the discharge of the perfluorinated material. Total perfluoroalkanesulfonate (4, 6, and 8 carbons) concentrations in fish liver samples ranged from 2.00 to 72.9 microg/g, and total perfluorocarboxylate (5-14 carbons) concentrations ranged from 0.07 to 1.02 microg/g. In addition to fish samples, total perfluoroalkanesulfonate (6 and 8 carbons) concentrations were detected in creek water samples by LC/MS/MS over a 153 day sampling period with concentrations ranging from <0.017 to 2260 microg/L; perfluorooctanoate concentrations (<0.009-11.3 microg/L) were lower than those observed for the perfluoroalkane-sulfonates. By 19F NMR, the total perfluorinated surfactant concentrations in surface water samples ranged from < 10 to 17000 microg/L. A bioaccumulation factor range of 6300-125000 was calculated for perfluorooctanesulfonate, based on concentrations in fish liver and surface water. The residence time of perfluorooctanesulfonate in Etobicoke Creek as well as the high bioaccumulation in fish liver suggests that perfluorinated surfactants will persist and bioaccumulate following release into the aquatic environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".