Perfluorinated Acid Isomer Profiling in Water and Quantitative Assessment of Manufacturing Source
Bibliographic record
Abstract
A method for isomer profiling of perfluorinated compounds (PFCs) in water was developed and applied to quantitatively assess the contributions from electrochemical (ECF) and telomer manufacturing processes around source regions of North America, Asia, and Europe. With the exception of 3 sites in Japan, over 80% of total perfluorooctanoate (PFOA, C(7)F(15)COO(-)) was from ECF, with the balance attributable to strictly linear (presumably telomer) manufacturing source(s). Comparing PFOA isomer profiles in samples from China, with PFOA obtained from a local Chinese manufacturer, indicated <3% difference in overall branched isomer content; thus, exclusive contribution from local ECF production cannot be ruled out. In Tokyo Bay, ECF, linear-telomer, and isopropyl-telomer sources contributed to 33%, 53%, and 14% of total PFOA, respectively. Perfluorooctane sulfonate (PFOS, C(8)F(17)SO(3)(-)) isomer profiles were enriched in branched content (i.e., >50% branched) in the Mississippi River but in all other locations were similar or only slightly enriched in branched content relative to historical ECF PFOS. Isomer profiles of other PFCs are also reported. Overall, these data suggest that, with the exception of Tokyo Bay, ECF manufacturing has contributed to the bulk of contamination around these source regions, but other sources are significant, and remote sites should be monitored.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".