What is the effect of phasing out long-chain per- and polyfluoroalkyl substances on the concentrations of perfluoroalkyl acids and their precursors in the environment? A systematic review
Bibliographic record
Abstract
Abstract Background There is a concern that continued emissions of man-made per- and polyfluoroalkyl substances (PFASs) may cause environmental and human health effects. Now widespread in human populations and in the environment, several PFASs are also present in remote regions of the world, but the environmental transport and fate of PFASs are not well understood. Phasing out the manufacture of some types of PFASs started in 2000 and further regulatory and voluntary actions have followed. The objective of this review is to understand the effects of these actions on global scale PFAS concentrations. Methods Searches for primary research studies reporting on temporal variations of PFAS concentrations were performed in bibliographic databases, on the internet, through stakeholder contacts and in review bibliographies. No time, document type, language or geographical constraints were applied in the searches. Relevant subjects included human and environmental samples. Two authors screened all retrieved articles. Dual screening of 10% of the articles was performed at title/abstract and full-text levels by all authors. Kappa tests were used to test consistency. Relevant articles were critically appraised by four reviewers, with double checking of 20% of the articles by a second reviewer. Meta-analysis of included temporal trends was considered but judged to not be appropriate. The trends were therefore discussed in a narrative synthesis. Results Available evidence suggests that human concentrations of perfluorooctane sulfonate (PFOS), perfluorodecane sulfonate (PFDS), and perfluorooctanoic acid (PFOA) generally are declining, while previously increasing concentrations of perfluorohexane sulfonate (PFHxS) have begun to level off. Rapid declines for PFOS-precursors (e.g. perfluorooctane sulfonamide, FOSA) have also been consistently observed in human studies. In contrast, limited data indicate that human concentrations of PFOS and PFOA are increasing in China where the production of these substances has increased. Human concentrations of longer-chained perfluoroalkyl carboxylic acids (PFCAs) with 9–14 carbon atoms are generally increasing or show insignificant trends with too low power to detect a trend. For abiotic and biological environmental samples there are no clear patterns of declining trends. Most substances show mixed results, and a majority of the trends are insignificant with low power to detect a trend. Conclusions For electrochemically derived PFASs, including PFOS and PFOA, most human studies in North America and Europe show consistent statistically significant declines. This contrasts with findings in wildlife and in abiotic environmental samples, suggesting that declining PFOS, PFOS-precursor and PFOA concentrations in humans likely resulted from removal of certain PFASs from commercial products including paper and board used in food packaging. Increasing concentrations of long-chain PFCAs in most matrices, and in most regions, is likely due to increased use of alternative PFASs. Continued temporal trend monitoring in the environment with well-designed studies with high statistical power are necessary to evaluate the effectiveness of past and continuing regulatory mitigation measures. For humans, more temporal trend studies are needed in regions where manufacturing is most intense, as the one human study available in China is much different than in North America or Europe.
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 | 0.018 | 0.072 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".