Environmental Occurrence and Biotic Concentrations of Ultrashort-Chain Perfluoroalkyl Acids: Overlooked Global Organofluorine Contaminants
Bibliographic record
Abstract
Per- and polyfluoroalkyl substances (PFASs) are a large group of anthropogenic fluorinated chemicals. Ultrashort-chain perfluoroalkyl acids (PFAAs) have recently gained attention due to their prevalence in the environment and increasing environmental concerns. In this review, we established a literature database from 1990 to 2024, encompassing environmental and biological concentrations (>3,500 concentration records) of five historically overlooked ultrashort-chain PFAAs (perfluoroalkyl carboxylic and sulfonic acids with less than 4 carbons): trifluoroacetic acid (TFA), perfluoropropanoic acid (PFPrA), trifluoromethanesulfonic acid (TFMS), perfluoroethanesulfonate (PFEtS), and perfluoropropanesulfonate (PFPrS). Our data mining and analysis reveal that (1) ultrashort-chain PFAAs are globally distributed in various environments including water bodies, solid matrices, and air, with concentrations usually higher than those of longer-chain compounds; (2) TFA, the most extensively studied ultrashort-chain PFAA, shows a consistent upward trend in concentrations in surface water, rainwater, and air over the past three decades; and (3) ultrashort-chain PFAAs are present in various organisms, including plants, wildlife, and human blood, serum, and urine, with concentrations sometimes similar to those of longer-chain compounds. The current state of knowledge regarding the sources and fate of TFA and other ultrashort-chain PFAAs is also reviewed. Amid the global urgency to regulate PFASs, particularly as countries worldwide have intensified such efforts, this critical review will inform scientific research and regulatory policies.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.017 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".