Phase Behavior of Internal Mixtures of Hydrocarbon-like Primary Organic Aerosol and Secondary Aerosol Based on Their Differences in Oxygen-to-Carbon Ratios
Bibliographic record
Abstract
The phase behavior, the number and type of phases, in atmospheric particles containing mixtures of hydrocarbon-like organic aerosol (HOA) and secondary organic aerosol (SOA) is important for predicting their impacts on air pollution, human health, and climate. Using a solvatochromic dye and fluorescence microscopy, we determined the phase behavior of 11 HOA proxies (O/C = 0-0.29) each mixed with 7 different SOA materials generated in environmental chambers (O/C 0.4-1.08), where O/C represents the average oxygen-to-carbon atomic ratio. Out of the 77 different HOA + SOA mixtures studied, we observed two phases in 88% of the cases. The phase behavior was independent of relative humidity over the range between 90% and <5%. A clear trend was observed between the number of phases and the difference between the average O/C ratios of the HOA and SOA components (ΔO/C). Using a threshold ΔO/C of 0.265, we were able to predict the phase behavior of 92% of the HOA + SOA mixtures studied here, with one-phase particles predicted for ΔO/C < 0.265 and two-phase particles predicted for ΔO/C ≥ 0.265. The threshold ΔO/C value provides a relatively simple and computationally inexpensive framework for predicting the number of phases in internal SOA and HOA mixtures in atmospheric 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 | 0.000 |
| 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) | 0.000 | 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".