The carbon kinetic isotope effects of ozone‐alkene reactions in the gas‐phase and the impact of ozone reactions on the stable carbon isotope ratios of alkenes in the atmosphere
Bibliographic record
Abstract
The kinetic isotope effects (KIEs) for several ozone‐alkene reactions in the gas phase were studied in a 30 L PTFE reaction chamber. The time dependence of the stable carbon isotope ratios and the concentrations were determined using a gas chromatography combustion isotope ratio mass spectrometry (GCC‐IRMS) system. The following average KIE values were obtained: 18.9 ± 2.8 (ethene), 9.5 ± 2.5 (propene), 8.7 ± 1 (1‐butene), 8.1 ± 0.4 (E‐2‐butene), 7.9 ± 0.4 (1,3‐butadiene), 6.7 ± 0.9 (1‐pentene), 7.3 ± 0.2 (Z‐2‐pentene), 6.7 ± 0.7 (cyclopentene), 6.1 ± 1 (isoprene), 5.0 ± 0.7 (1‐hexene), 5.6 ± 0.5 (cyclohexene), and 4.3 ± 0.7 (1‐heptene). These data are the first of their kind to be reported in the literature. The ozone‐alkene KIE values show a systematic inverse dependence from alkene carbon number. Based on the observed KIEs, the contribution of ozone‐alkene reactions to the isotopic fractionation of alkenes in the atmosphere can be estimated. On average this contribution is generally small compared to the impact of reaction with OH radicals. However, when OH‐concentrations are very low, e.g. during nighttime and at high latitudes in winter, the contribution of the ozone reaction dominates and under these conditions the ozone‐alkene reaction will have a clearly visible impact on the stable carbon isotope ratio of atmospheric alkenes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".