Kinetics, Mechanism, and Secondary Organic Aerosol Yield of Aqueous Phase Photo-oxidation of α-Pinene Oxidation Products
Bibliographic record
Abstract
Formation of secondary organic aerosol (SOA) involves atmospheric oxidation of volatile organic compounds (VOCs), the majority of which are emitted from biogenic sources. Oxidation can occur not only in the gas-phase but also in atmospheric aqueous phases such as cloudwater and aerosol liquid water. This study explores for the first time the aqueous-phase OH oxidation chemistry of oxidation products of α-pinene, a major biogenic VOC species emitted to the atmosphere. The kinetics, reaction mechanisms, and formation of SOA compounds in the aqueous phase of two model compounds, cis-pinonic acid (PIN) and tricarballylic acid (TCA), were investigated in the laboratory; TCA was used as a surrogate for 3-methyl-1,2,3-butanetricarboxylic acid (MBTCA), a known α-pinene oxidation product. Aerosol time-of-flight chemical ionization mass spectrometry (Aerosol-ToF-CIMS) was used to follow the kinetics and reaction mechanisms at the molecular level. Room-temperature second-order rate constants of PIN and TCA were determined to be 3.3 (± 0.5) × 10(9) and 3.1 (± 0.2) × 10(8) M(-1) s(-1), respectively, from which were estimated their condensed-phase atmospheric lifetimes. Aerosol-ToF-CIMS detected a large number of products leading to detailed reaction mechanisms for PIN and MBTCA. By monitoring the particle size distribution after drying, the amount of SOA material remaining in the particle phase was determined. An aqueous SOA yield of 40 to 60% was determined for PIN OH oxidation. Although recent laboratory studies have focused primarily on aqueous-phase processing of isoprene-related compounds, we demonstrate that aqueous formation of SOA materials also occurs from monoterpene oxidation products, thus representing an additional source of biogenically driven aerosol formation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".