Box model studies of the secondary organic aerosol formation under different HC/NO<sub>x</sub>conditions using the subset of the Master Chemical Mechanism for<i>α</i>‐pinene oxidation
Bibliographic record
Abstract
A subset of a near‐explicit Master Chemical Mechanism (v3.1) describingα‐pinene oxidation (976 reactions and 331 compounds) coupled with a gas/particle absorptive partitioning model is used as a benchmark for the study of secondary organic aerosol (SOA) formation within a box model under atmospheric relevant conditions of averaged HC/NOxratios between 0.18 and 8.43 (ppbvC/ppbv). Results from the detailed mechanism forα‐pinene oxidation show that total SOA mass increases as the HC/NOxratio increases within the studied range. The mass of peroxynitrates and the nitrates in the aerosol phase increases with increasing HC/NOxratio, despite decreases in the total (gas plus aerosol) mass of these species, because of increases in mass of organic peroxides and acids in these conditions. The fractional composition of aerosol mass indicates organic peroxides and acids dominate at high HC/NOxratios and peroxynitrates and nitrates dominate at low HC/NOxratios. In addition, 28 out of 149 condensable products are identified as important compounds for SOA formation. Of the organic nitrates, only two contribute consistently to organic aerosol mass. Organic peroxide and acid mass in the aerosol phase is distributed over a larger number of species. The 28 species identified here are suitable targets for future laboratory and field analysis of organic aerosols and are recommended for use in future mechanism reduction work.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".