A gas chromatograph for quantification of peroxycarboxylic nitric anhydrides calibrated by thermal dissociation cavity ring-down spectroscopy
Bibliographic record
Abstract
Abstract. The peroxycarboxylic nitric anhydrides (PANs, molecular formula: RC(O)O2NO2) can readily be observed by gas chromatography (PAN-GC) coupled to electron capture detection. Calibration of a PAN-GC remains a challenge, because the response factors differ for each of the PANs, and because their synthesis in sufficiently high purity is non-trivial, in particular for PANs containing unsaturated side chains. In this manuscript, a PAN-GC and its calibration using diffusion standards, whose output was quantified by blue diode laser thermal dissociation cavity ring-down spectroscopy (TD-CRDS), are described. The PAN-GC peak areas correlated linearly with total peroxy nitrate (ΣPN) mixing ratios measured by TD-CRDS (r > 0.96). Accurate determination of response factors required the concentrations of PAN impurities in the synthetic standards to be subtracted from ΣPN. The PAN-GC and its TD-CRDS calibration method were deployed during ambient air measurement campaigns in Abbotsford, BC, from 20 July to 5 August 2012, and during the Fort McMurray Oil Sands Strategic Investigation of Local Sources (FOSSILS) campaign at the AMS13 ground site in Fort McKay, AB, from 10 August to 5 September 2013. The PAN-GC limits of detection for PAN, PPN, and MPAN during FOSSILS were 1, 2, and 3 pptv, respectively. For the Abbotsford data set, the PAN-GC mixing ratios were compared, and agreed with those determined in parallel by thermal dissociation chemical ionization mass spectrometry (TD-CIMS). Advantages and disadvantages of the PAN measurement techniques used in this work and the utility of TD-CRDS as a PAN-GC calibration method are discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".