Degradation of Fluorotelomer-Based Polymers Contributes to the Global Occurrence of Fluorotelomer Alcohol and Perfluoroalkyl Carboxylates: A Combined Dynamic Substance Flow and Environmental Fate Modeling Analysis
Bibliographic record
Abstract
Using coupled dynamic substance flow and environmental fate models, CiP-CAFE and BETR-Global, we investigated whether the degradation of side-chain fluorotelomer-based polymers (FTPs), mostly in waste stocks (i.e., landfills and dumps), serves as a long-term source of fluorotelomer alcohols (FTOHs) and perfluoroalkyl carboxylates (PFCAs) to the global environment. The modeling results indicate that, in the wake of the worldwide transition from long-chain to short-chain products, in-use stocks of C8 FTPs will peak and decline afterward, while the in-use stocks of C6 FTPs, and the waste stocks of both FTPs will generally grow. FTP degradation in waste stocks is making an increasing contribution to FTOH generation, the bulk of which readily migrates from waste stocks and degrades into PFCAs in the environment; the remaining part of the generated FTOHs degrade in waste stocks, which makes those stocks reservoirs that slowly release PFCAs into the environment over the long run because of the low leaching rate and extreme persistence of PFCAs. Short-chain FTPs have higher relative release rates of PFCAs from waste stocks than long-chain ones. Estimates of in-use and waste stocks of FTPs were more sensitive to the selected lifespan of finished products, while those of the emissions of FTOHs and PFCAs were more sensitive to the degradation half-life of FTPs in waste stocks. Our preliminary calculations highlight the need for environmentally sound management of obsolete FTP-containing products into the foreseeable future.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".