Widespread Occurrence of Non-Extractable Fluorine in Artificial Turfs from Stockholm, Sweden
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Per- and polyfluoroalkyl substances (PFAS) are frequently used in the production of rubber and plastic, but little is known about the identity, concentration, or prevalence of PFAS in these products. In this study, a representative sample of plastic- and rubber-containing artificial turf (AT) fields from Stockholm, Sweden, was subjected to total fluorine (TF), extractable organic fluorine (EOF), and target PFAS analysis. TF was observed in all 51 AT samples (ranges of 16-313, 12-310, and 24-661 μg of F/g in backing, filling, and blades, respectively), while EOF and target PFAS occurred in <42% of all samples (<200 and <1 ng of F/g, respectively). A subset of samples extracted with water confirmed the absence of fluoride. Moreover, application of the total oxidizable precursor assay revealed negligible perfluoroalkyl acid (PFAA) formation across all three sample types, indicating that the fluorinated substances in AT are not low-molecular weight PFAA precursors. Collectively, these results point toward polymeric organofluorine (e.g., fluoroelastomer, polytetrafluoroethylene, and polyvinylidene fluoride), consistent with patent literature. The combination of poor extractability and recalcitrance toward advanced oxidation suggests that the fluorine in AT does not pose an imminent risk to users. However, concerns surrounding the production and end of life of AT, as well as the contribution of filling and blades to environmental microplastic contamination, remain.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 it