A Rapid Derivatization for Quantitation of Perfluorinated Carboxylic Acids from Aqueous Matrices by Gas Chromatography–Mass Spectrometry
Bibliographic record
Abstract
Ultrashort-chain perfluorinated carboxylic acids (PFCAs) are receiving more attention due to their ever-increasing presence in the environment. Methods have been established for the analysis of short- and long-chain PFCAs, while robust quantitation of ultrashort-chain species is scarce. Here, we develop a novel derivatization method using diphenyl diazomethane for quantitation of C2–C14 PFCAs in aqueous matrices. The method is highlighted by rapid completion of derivatization (<1 min) and retention and separation of ultrashort-chain (C2/C3) PFCA derivatives using H 2 carrier gas ( R > 1.5). A weak anion exchange solid-phase extraction procedure for analyte recovery from representative aqueous samples was developed and validated by spike and recovery from ultrapure water, synthetic ocean water, and simulated denuder extracts used for collecting gaseous PFCAs. Recoveries for PFCAs ranged from 83 to 130% for the majority of analytes and matrices. The instrument detection limits (IDLs) range from 8 to 220 fg per injection, and method detection limits (MDLs) range from 0.06 to 14.6 pg/mL for 500 mL aqueous samples, which are within an order of magnitude to conventional LC–MS/MS methods. The method was applied to the analysis of real samples of tap water, rainwater, ocean water, and annular denuder extracts. The overall method provides a cost-effective alternative to conventional LC–MS/MS methods, overcoming the typical GC–MS drawbacks of high detection limits and long sample preparation times while being able to simultaneously analyze the complete spectrum of environmentally relevant PFCAs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".