The stable carbon isotope fractionation for reactions of selected hydrocarbons with OH‐radicals and its relevance for atmospheric chemistry
Bibliographic record
Abstract
Measurements of the kinetic isotope effect (KIE) for the reactions of light n‐alkanes as well as for several unsaturated hydrocarbons, including alkenes, dienes, benzene, and ethyne with OH‐radicals are presented. All measured KIEs are positive; that is, molecules containing only C‐12 react faster than the C‐13 labeled molecules. However, the KIEs for n‐alkanes are quite small; between one and four permil. They can be explained mainly by the mass dependence of the collision frequency between the n‐alkanes and OH‐radicals. KIEs for the reaction of alkenes with OH‐radicals are considerably higher. They can be explained by a fractionation of 24.5±1.1‰ for the addition of an OH‐radical to a double bond. Inverse dependence on number of carbon atoms and mass dependence of the collision frequencies explain our observations. For benzene the KIE is slightly higher; for ethyne it is somewhat lower than expected from this simple model. For the reaction of many light nonmethane hydrocarbons (NMHC), especially of unsaturated hydrocarbons, with OH‐radicals the KIEs are sufficiently large to have significant impact on the isotopic composition of atmospheric NMHC. A small series of stable carbon isotope ratio measurements of atmospheric NMHC were made in the greater Toronto area. Traffic related NMHC emissions were also studied for their stable carbon isotope ratios. From these data it is possible to quantitatively determine the extent of photochemical processing due to OH‐radical reactions that the individual NMHC has experienced. Thus such measurements allow quantitative evaluation of the extent of chemical processing the different NMHC have gone through. This also includes the possibility to differentiate between the impact of local sources and regional or large scale transport. It is shown that in combination with concentration measurements isotope ratio measurements are extremely valuable to study the complex interaction between chemical removal mechanisms, mixing, and dilution processes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".