Rapid and Convenient Potentiometric Method for Determining Fluorosulfate, a Byproduct of the Fumigant and Greenhouse Gas Sulfuryl Fluoride
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide A fluorosulfate ion (FSO 3 – ) is a hydrolysis product of sulfuryl fluoride (SO 2 F 2 ), which is widely used to fumigate buildings, soil, construction materials, and postharvest commodities, and is a potent greenhouse gas. It is a potential marker for biological exposure to SO 2 F 2 and for monitoring the progress of reactions used to scrub SO 2 F 2 from fumigation vent gases. Here, we report a simple and inexpensive potentiometric method for determining FSO 3 – using a commercial nitrate-selective electrode and discuss its application. The method is suitable for solutions between 0.0025 mM and 660 mM FSO 3 – at initial pH between 5 and 9. Halide interference depends on its molar ratio to FSO 3 – and follows the sequence, F – < Cl – < Br – ≪ I – . Halide interference can be eliminated by adding silver sulfate. Interference by bicarbonate can be eliminated by H 2 SO 4 pretreatment, and interference by phosphate or pyrophosphate by MgSO 4 addition. Sulfate does not interfere, as it does in ion chromatography. Satisfactory method detection limits for FSO 3 – in spiked aqueous extracts of 11 fruits were obtained. The method accurately quantified the yield of FSO 3 – relative to that of F – in base hydrolysis of SO 2 F 2 . This study demonstrates that the developed method is highly selective, convenient, and sensitive and thus can be of great value in practice.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 0.002 |
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".