Setting guideline values for PFAS in drinking water: decision-making process in Israel
Bibliographic record
Abstract
SUMMARY Regulatory authorities in the field of environmental health often grapple with decision-making in the face of scientific uncertainty and rapidly emerging data. The identification of per- and polyfluoroalkyl substances (PFAS) contamination in drinking water sources in Israel, and the need for rapid decision-making on PFAS drinking water standards, is one such example. The Water Authority, which is responsible for management of the water sector in Israel, first discovered PFAS contamination in groundwater in 2019. The Ministry of Health (MOH), which is responsible for drinking water quality, began measuring PFAS compounds in 2020. As of the end of 2024, the MOH has measured nine PFAS compounds in over 375 drinking water wells, 14.7% of which have at least one detected PFAS compound. This manuscript reviews four considerations taken into account in the decision on guideline values for PFAS: toxicological threshold, consideration of current worldwide regulatory standards, practical achievability, and analytical capacity. Based on these considerations, the MOH adopted Health Canada’s 2018 maximum acceptable concentrations in drinking water for perfluorooctanoate (PFOA) and perfluorooctane sulfonic acid (PFOS) as an interim guideline value. Subsequently, the MOH decided to adopt the EU Drinking Water Directive standards on PFAS, which include 20 PFAS compounds, and which will enter into force in 2026. To date, drinking water supply has been discontinued from four wells, and another 10 drinking water wells will be discontinued or will require treatment once the stricter standard enters force. Quarterly or annual monitoring for tens of wells is required, depending on measured PFAS concentrations. In addition to ongoing monitoring of PFAS in drinking water wells, the MOH is conducting a human biomonitoring (HBM) study to measure PFAS in blood in an adult population and is involved in work developing HBM guideline values, as part of the Partnership for Chemical Risk Assessment (PARC).
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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 | 0.093 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".