Secondary organic aerosol formation from biomass burning intermediates: phenol and methoxyphenols
Bibliographic record
Abstract
Abstract. The formation of secondary organic aerosol from oxidation of phenol, guaiacol (2-methoxyphenol), and syringol (2,6-dimethoxyphenol), major components of biomass burning, is described. Photooxidation experiments were conducted in the Caltech laboratory chambers under low-NOx (< 10 ppb) conditions using H2O2 as the OH source. Secondary organic aerosol (SOA) yields (ratio of mass of SOA formed to mass of primary organic reacted) greater than 25% are observed. Aerosol growth is rapid and linear with the primary organic conversion, consistent with the formation of essentially non-volatile products. Gas- and aerosol-phase oxidation products from the guaiacol system provide insight into the chemical mechanisms responsible for SOA formation. Syringol SOA yields are lower than those of phenol and guaiacol, likely due to novel methoxy group chemistry that leads to early fragmentation in the gas-phase photooxidation. Atomic oxygen to carbon (O : C) ratios calculated from high-resolution-time-of-flight Aerodyne Aerosol Mass Spectrometer (HR-ToF-AMS) measurements of the SOA in all three systems are ~ 0.9, which represent among the highest such ratios achieved in laboratory chamber experiments and are similar to that of aged atmospheric organic aerosol. The global contribution of SOA from intermediate volatility and semivolatile organic compounds has been shown to be substantial (Pye and Seinfeld, 2010). An approach to representing SOA formation from biomass burning emissions in atmospheric models could involve one or more surrogate species for which aerosol formation under well-controlled conditions has been quantified. The present work provides data for such an approach.
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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".