Zwitterionic, cationic, and anionic PFAS in freshwater sediments from AFFF-impacted and non-impacted sites of Eastern Canada
Bibliographic record
Abstract
Zwitterionic, cationic, and anionic per- and polyfluoroalkyl substances (PFAS) were investigated in freshwater sediments of Canada, including sites impacted by aqueous film-forming foams (AFFFs). The first step of the project involved optimizing the extraction method with equilibrated sediment-water-AFFF samples. The analytical method had acceptable linearity, accuracy, and precision in the sediment matrix, and was further validated with NIST SRM 1936. In the second step of the project, the method was applied to determine over 70 target PFAS in field-collected sediments (n = 102). At federal contaminated sites of Ontario, Newfoundland, and Québec (ditches and creeks at international airports with fire training or fire equipment testing areas), summed PFAS averaged 30 ng/g (maximum of 160 ng/g) with molecular patterns dominated by perfluorooctane sulfonate (maximum PFOS: 84 ng/g). Based on maximum observed concentrations >10 ng/g, other key PFAS at these AFFF-impacted sites included negative ion mode perfluorohexane sulfonate, perfluorohexane sulfonamide, fluorotelomer sulfonates (6:2 FTS and 8:2 FTS) and 5:3 fluorotelomer acid, and positive ion mode N-dimethylammoniopropyl perfluorohexane sulfonamide and 5:1:2 fluorotelomer betaine. In contrast, environmental sediment samples collected at a larger spatial scale (province-wide survey) were characterized by low ΣPFAS (generally <1 ng/g), with PFOS/PFOA below chronic toxicity thresholds for aquatic life. • Methods were tested for a wide breadth of PFAS using sediment-water-AFFF experiments. • The method had improved recoveries and LODs for screening ESI+ PFAS in sediments. • ΣPFAS reached 160 ppb at federal contaminated sites, with PFOS often dominating. • ESI+ PFHxSAm, 5:1:2 FTB, & 6:2 FTAB ranked within the top 15 most abundant PFAS. • PFAS levels were extremely low at other sites (<1 ppb), except near airports.
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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 | 0.002 | 0.002 |
| 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".