Development of an analytical technique and stability evaluation of 143 C3–C12 volatile organic compounds in Summa® canisters by gas chromatography–mass spectrometry
Bibliographic record
Abstract
A technique using Summa canisters with cryogenic preconcentration and gas chromatographic-mass spectrometric (GC-MS) detection was developed to determine 143 C3-C12 volatile organic compounds (VOCs) including alkanes, alkenes, aromatics and halohydrocarbons in ambient and indoor air. The method detection limits and practical quantification limits were sensitive at 0.02 and 0.10 ppbv, respectively, and the method precision and accuracy were also satisfactory. The stability of C3-C12 VOC standards at ppbv levels under elevated pressure in canisters was assessed over various time intervals (from 1 week to 4 months after preparation) and most of the compounds were found to be acceptably stable with a mean recovery of 85.6 +/- 9.9% during the course of a 4-month study. However, a small fraction (approximately 6%) of the compounds, including two halohydrocarbons (bromotrichloromethane and benzyl chloride) and six alkenes (2-methylbuta-1,3-diene (isoprene), cis-4-methylpent-2-ene, cis-3-methylpent-2-ene, hept-1-ene, oct-1-ene and styrene) displayed relatively low recoveries in the range 34.6-67.9%. The loss of these compounds is most probably caused by their physical adherence to the active sites of the canister surface, chemical decomposition and/or reactions with other species. The results indicated that one must be cautious in attempting to measure these compounds owing to their instability in canisters. Overall, this analytical technique, which has been used for the determination of the VOCs under study in the toxic air pollutant monitoring network administered by the HKSAR Government, was amenable to the measurement of airborne VOCs collected both outside and inside a semi-confined car park in the present study.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".