Relative humidity-dependent viscosities of isoprene-derived secondary organic material and atmospheric implications for isoprene-dominant forests
Bibliographic record
Abstract
Abstract. Oxidation of isoprene is an important source of secondary organic material (SOM) in atmospheric particles, especially in areas such as the Amazon Basin. Information on the viscosities, diffusion rates, and mixing times within isoprene-derived SOM is needed for accurate predictions of air quality, visibility, and climate. Currently, however, this information is not available. Using a bead-mobility technique and a poke-flow technique combined with fluid simulations, the relative humidity (RH)-dependent viscosities of SOM produced from isoprene photo-oxidation were quantified for 20–60 μm particles at 295 ± 1 K. From 84.5 to 0% RH, the viscosities for isoprene-derived SOM varied from ~ 2 × 10−1 to ~ 3 × 105 Pa s, implying that isoprene-derived SOM ranges from a liquid to a semisolid over this RH range. These viscosities correspond to diffusion coefficients of ~ 2 × 10−8 to ~ 2 × 10−14 cm2 s−1 for large organic molecules that follow the Stokes–Einstein relation. Based on the diffusion coefficients, the mixing time of large organic molecules within 200 nm isoprene-derived SOM particles ranges from approximately 0.1 h to less than 1 s. To illustrate the atmospheric implications of this study's results, the Amazon Basin is used as a case study for an isoprene-dominant forest. Considering the RH and temperature range observed in the Amazon Basin and with some assumptions about the dominant chemical compositions of SOM particles in the region, it is likely that SOM particles in this area are liquid and reach equilibrium with large gas-phase organic molecules on short time scales, less than or equal to approximately 0.1 h.
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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".