A Method to Measure Total Gaseous Fluorine
Bibliographic record
Abstract
Total fluorine (TF) analysis is a powerful tool for the characterization of organofluorine contaminants in the environment. Organofluorine compounds are known primarily with respect to the notorious poly- and perfluoroalkyl substances (PFAS) and as potent greenhouse gases that can impact the climate. The use of targeted methods for every organofluorine compound in the environment is not feasible. While methods are available for TF analysis of condensed phase samples, no technique exists for gas phase TF measurements (TF g ). Herein we demonstrate an in situ instrumental method for TF g via platinum catalyzed thermolysis at 1000 °C in the presence of propane. TF g is fully converted into HF and subsequently quantified by an ion selective electrode or ion chromatography for F – . The method was validated using nine organofluorine compounds with differing functional groups. We characterized TF g and compared it to common speciated measurements in the headspace of four commercial fluorosurfactants and outdoor air. Most TF g (65.0–99.8% or 1.5–10.2 ppmv F) in the fluorosurfactant headspace was unknown. In outdoor air, >50% of TF g (7.2–24.2 ppmv F) was unknown. These high quantities of unknown organofluorine indicate a measurement gap in the gas phase, which could have important implications for atmospheric sources and the burdens of PFAS and fluorinated greenhouse gases.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".