Cross-cutting studies of per- and polyfluorinated alkyl substances (PFAS) in Arctic wildlife and humans
Bibliographic record
Abstract
This cross-cutting review focuses on the presence and impacts of per- and polyfluoroalkyl substances (PFAS) in the Arctic. Several PFAS undergo long-range transport via atmospheric (volatile polyfluorinated compounds) and oceanic pathways (perfluorinated alkyl acids, PFAAs), causing widespread contamination of the Arctic. Beyond targeting a few well-known PFAS, applying sum parameters, suspect and non-targeted screening are promising approaches to elucidate predominant sources, transport, and pathways of PFAS in the Arctic environment, wildlife, and humans, and establish their time-trends. Across wildlife species, concentrations were dominated by perfluorooctane sulfonic acid (PFOS), followed by perfluorononanoic acid (PFNA); highest concentrations were present in mammalian livers and bird eggs. Time trends were similar for East Greenland ringed seals ( Pusa hispida ) and polar bears ( Ursus maritimus ). In polar bears, PFOS concentrations increased from the 1980s to 2006, with a secondary peak in 2014–2021, while PFNA increased regularly in the Canadian and Greenlandic ringed seals and polar bear livers. Human time trends vary regionally (though lacking for the Russian Arctic), and to the extent local Arctic human populations rely on traditional wildlife diets, such as marine mammals. Arctic human cohort studies implied that several PFAAs are immunotoxic, carcinogenic or contribute to carcinogenicity, and affect the reproductive, endocrine and cardiometabolic systems. Physiological, endocrine, and reproductive effects linked to PFAS exposure were largely similar among humans, polar bears, and Arctic seabirds. For most polar bear subpopulations across the Arctic, modeled serum concentrations exceeded PFOS levels in human populations, several of which already exceeded the established immunotoxic thresholds for the most severe risk category. Data is typically limited to the western Arctic region and populations. Monitoring of legacy and novel PFAS across the entire Arctic region, combined with proactive community engagement and international restrictions on PFAS production remain critical to mitigate PFAS exposure and its health impacts in the Arctic. Differential pathways of transport, accumulation and effects of PFAS in the Arctic environment, biota and humans • Long-range transport, reactions and novel PFAS affect profiles and levels in Arctic. • Time-trends of PFAS across Arctic diverge among environment, wildlife and humans. • Greatest PFAS concentrations present in liver of mammals and seabird eggs. • PFAS persist, accumulate, and pose threats to Arctic biodiversity and humans. • PFAS effects in humans and wildlife seem similar, but polar bears at greater risk.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".