Phase Behavior of Hydrocarbon-like Primary Organic Aerosol and Secondary Organic Aerosol Proxies Based on Their Elemental Oxygen-to-Carbon Ratio
Bibliographic record
Abstract
A large fraction of atmospheric aerosols can be characterized as primary organic aerosol (POA) and secondary organic aerosol (SOA). Knowledge of the phase behavior, that is, the number and type of phases within internal POA + SOA mixtures, is crucial to predict their effect on climate and air quality. For example, if POA and SOA form a single phase, POA will enhance the formation of SOA by providing organic mass to absorb SOA precursors. Using microscopy, we studied the phase behavior of mixtures of SOA proxies and hydrocarbon-like POA proxies at relative humidity (RH) values of 90%, 45%, and below 5%. Internal mixtures of POA and SOA almost always formed two phases if the elemental oxygen-to-carbon ratio (O/C) of the POA was less than 0.11, which encompasses a large fraction of atmospheric hydrocarbon-like POA from fossil fuel combustion. SOA proxies mixed with POA proxies having 0.11 ≤ O/C ≤ 0.29 mostly resulted in particles with one liquid phase. However, two liquid phases were also observed, depending on the type of SOA and POA surrogates, and an increase in phase-separated particles was observed when increasing the RH in this O/C range. The results have implications for predicting atmospheric SOA formation and policy strategies to reduce SOA in urban environments.
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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 | 0.000 |
| 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".