pH Dependence of the OH Reactivity of Organic Acids in the Aqueous Phase
Bibliographic record
Abstract
Photochemical processing taking place in atmospheric aqueous phases serves as both a source and a sink of organic compounds. In aqueous environments, acid–base chemistry and, by extension, aqueous-phase pH, are an important yet often neglected factors to consider when investigating the kinetics of organic compounds. We have investigated the aqueous-phase OH-oxidation of pinic acid, cis- pinonic acid, limononic acid, and formic acid (FA) as a function of pH. We have also extended our studies to other organic acids (OAs) present in the water-soluble fraction of secondary organic aerosol (SOA) arising from the ozonolysis of α-pinene. Although all the OAs exhibited larger OH reactivities at pH 10, the pH dependence was dramatically different between FA, the smallest OA, and those that contained more than eight carbons. A kinetic box model was also employed to characterize our photoreactor and to provide confidence to our results. Our finding shows that the atmospheric lifetimes of small OAs (e.g., FA) are highly sensitive to cloud water pH. However, those of larger OAs and many other OAs in α-pinene SOA are affected to a much less extent. These results are of great importance for the simplification of cloud water chemistry models.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".