Organic acids as cloud condensation nuclei: Laboratory studies of highly soluble and insoluble species
Bibliographic record
Abstract
Abstract. The ability of sub-micron-sized organic acid particles to act as cloud condensation nuclei (CCN) has been examined at room temperature using a newly constructed continuous-flow, thermal-gradient diffusion chamber (TGDC). The organic acids studied were: oxalic, malonic, glutaric, oleic and stearic. The CCN properties of the highly soluble acids – oxalic, malonic and glutaric – match very closely Kohler theory predictions which assume full dissolution of the dry particle and a surface tension of the growing droplet equal to that of water. In particular, for supersaturations between 0.3 and 0.6, agreement between the dry particle diameter which gives 50% activation and that calculated from Kohler theory is to within 3 nm on average. In the course of the experiments, considerable instability of glutaric acid particles was observed as a function of time and there is evidence that they fragment to some degree to smaller particles. Stearic acid and oleic acid, which are both highly insoluble in water, did not activate at supersaturations of 0.6% with dry diameters up to 140 nm. Finally, to validate the performance of the TGDC, we present results for the activation of ammonium sulfate particles that demonstrate good agreement with Kohler theory if solution non-ideality is considered. Our findings support earlier studies in the literature that showed highly soluble organics to be CCN active but insoluble species to be largely inactive.
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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 | 0.000 | 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 | 0.000 |
| 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".