Ion-Exchange Treatment of Perfluorinated Carboxylic Acids in Water: Comparison of Polystyrenic and Polyacrylic Resin Structures and Impact of Sulfate on Their Performance
Bibliographic record
Abstract
The removal of three perfluorinated carboxylic acids (PFCAs)-PFHpA, PFOA, and PFNA-in ultrapure and river water was evaluated using two anion-exchange resins-previously unreported macroporous polystyrenic A-500P and a more widely studied macroporous polyacrylic A-860. Both resins had similar properties, allowing direct comparison of PFCA removal performance between the two resin structures/matrices. This study also presents a new gas chromatography-mass spectrometry (GC/MS) method developed for PFCA analysis in water. In ultrapure water, A-500P exhibited higher removal capacity and faster removal compared to A-860, suggesting greater effectiveness of the polystyrenic structure compared to the polyacrylic structure. In the Grand River water, the target PFCAs were well removed by A-500P but not A-860. However, both resins achieved similarly high overall reductions of dissolved organic carbon (∼75%), suggesting, later confirmed in ultrapure water experiments, that inorganic anions (sulfate particularly) were the dominant competitors for the A-860 resin. The uncharged styrenic and acrylic beads (base materials) of the two tested resins were unable to remove PFOA, implying that the dominant removal mechanism involves charge interactions between the negatively charged PFCA and the positively charged anion-exchange functional groups.
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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 | 0.000 |
| 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) | 0.001 | 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".