PFAS contamination in tap water: Target and suspect screening of zwitterionic, cationic, and anionic species across Canada and beyond
Bibliographic record
Abstract
This study investigated the occurrence of perfluoroalkyl and polyfluoroalkyl substances (PFAS), including anionic, cationic, and zwitterionic compounds, in drinking water. Between 2021-2023, an expanded list of 76 target PFAS was screened in tap water samples mainly from Canada, but also including tap water samples from the Eastern United States, Mexico, South America (Argentina), the Caribbean (Dominican Republic, Cuba), Africa (Algeria, Cameroon, Central African Republic, Morocco, Rwanda, Tunisia), Europe (France, Greece, Italy, Spain, and the United Kingdom) and Asia (Japan, Vietnam, Iran, and Türkiye). An additional ∼ 200 suspect-target PFAS were screened using high-resolution Orbitrap mass spectrometry. The results revealed widespread contamination of PFAS in tap water. The most frequent were perfluorobutane sulfonate (PFBS), perfluorooctane sulfonate (PFOS), and perfluorobutanoic acid (PFBA) with detection rates of ≥ 79 %. Several PFAS not currently included in EPA methods for drinking water revealed region-specific trends. For instance, emerging zwitterionic 6:2 fluorotelomer sulfonamidopropyl betaine (6:2 FTAB) was found at the highest levels in cities of France, British Columbia (Canada), and the UK. The occurrence of FTAB likely reflects shifts from PFOS-based aqueous film-forming foams (AFFF) in the past decades, and possibly other uses. Short-chain perfluoroalkyl sulfonamides (FBSA, FHxSA) were also globally recurrent. Bistriflimide, a counterion often used in the composition of ionic liquids and in the production of lithium-ion batteries, was detected in 46 % of the samples. The highest levels of total PFAS in drinking water were linked to contamination from fluorochemical industries (surface water), AFFF use (groundwater), and landfills (groundwater). This database of 275 PFAS x 153 samples provides valuable insights toward refining the lists of relevant PFAS to be monitored in drinking water.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".