PFAS in water environments: recent progress and challenges in monitoring, toxicity, treatment technologies, and post-treatment toxicity
Bibliographic record
Abstract
There is growing awareness of the environmental presence of per- and polyfluoroalkyl substances (PFAS) and their harmful effects on animals and humans. Recent studies have revealed changes in human embryonic stem cells and maternal biomarkers, underscoring the severity and unpredictable outcomes associated with long-term exposure to PFAS. Monitoring efforts continually identify additional PFAS compounds worldwide, but a standardized and unified approach is still lacking. Traditional treatment methods such as adsorption and membrane filtration have been effective in removing 80–95% of PFAS from wastewater. However, complete removal of short-chain PFAS remains limited to a few recently developed techniques. The inability of advanced treatment methods to eliminate emerging short-chain and ultrashort-chain PFAS suggests the need for more integrated approaches that target all PFAS classes. Additionally, a few studies have discussed the potential toxicity outcomes of these treatments at both laboratory and full-scale levels. While advanced oxidative processes (AOPs) are rapidly gaining attention for degrading 90–100% of PFAS in sewage, it remains challenging to fully break down PFAS into non-toxic, mineralized products such as CO2 and H2O due to the strong C-F bonds and the potential toxicity of by-products in post-treated wastewater. Standardized and reliable bioassays for assessing PFAS toxicity are still under development, and current predictive models linking molecular structure to human health effects are at an early stage. This review examines the emerging health and ecological risks associated with both legacy and novel PFAS, alongside recent advances and limitations in individual and combined treatment technologies for water and wastewater. Emphasis is placed on the potential toxicity of degradation products, highlighting the need for more integrated and comprehensive toxicity assessments to guide safer PFAS remediation strategies.
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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 | 0.003 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".