Transformation of Polyfluoroalkyl Precursors in AFFF-Contaminated Concrete
Bibliographic record
Abstract
The contamination of concrete by per- and polyfluoroalkyl substances (PFAS) derived from aqueous film-forming foams (AFFFs) at impacted sites is a newly recognized issue, but the behavior and transformation of PFAS within concrete and in its vicinity remain largely unexplored. In this study, we discovered amide-based precursors from an electrochemical fluorination (ECF) AFFF, specifically, N -(3-(dimethylamino)propyl)-perfluoroalkylamides (PFAAAm or AmPr-FAAd), can transform into perfluoroalkyl carboxylates (PFCAs) when AFFF solutions or individual PFAS were exposed to concrete. This transformation was attributed to alkaline hydrolysis driven by leaching of Ca(OH) 2 from concrete, which raises the solution pH. In the same experiments, the generation of perfluoroalkyl sulfonamides (FASAs) was also observed, but their precursors remained unidentified. Meanwhile, during the validation of PFAS extraction methods from AFFF-contaminated concrete powder, PFCAs and FASAs were similarly generated during the pre-equilibration step, further confirming the occurrence of hydrolysis. Further investigations using four sulfonamide-based precursors suggested that their rapid decrease in aqueous concentration was likely due to low solubility and sorption to container walls and concrete powder, rather than chemical transformation, which suggests the relatively high stability of these perfluoroalkyl sulfonamide precursors. The exact precursors to FASAs remain unresolved, highlighting the need for research into PFAS behavior in concrete.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".