Photooxidation and ozonolysis of α-pinene and limonene mixtures: Mechanisms of secondary organic aerosol formation and cross-dimerization
Bibliographic record
Abstract
Elucidating the interplay between different volatile organic compounds (VOCs) is crucial for understanding the formation mechanisms of secondary organic aerosols (SOA). This study systematically investigated the interactions between the bicyclic monoterpene α-pinene and the monocyclic monoterpene limonene under NO 2 photooxidation and dark ozonolysis conditions. The results show that under the NO 2 photooxidation conditions, the increase of [limonene] 0 enhances particle mass concentrations, number concentrations, and particle size; the increase of [α-pinene] 0 results in the increase of particle mass and number concentrations without the increase of particle size. Under the dark ozonolysis conditions, particle mass and number concentrations increase with the increase of [α-pinene] 0 and [limonene] 0 ; the effect of increasing [α-pinene] 0 on SOA mass concentration is significantly smaller than that of increasing [limonene] 0 , which may be attributed to the shift to a smaller particle size with the increase of [α-pinene] 0 . As the [limonene] 0 /[mixed VOCs] 0 ratio increases from 0 % to 100 %, the SOA yield increases from 54.6 % to 65.2 % under the NO 2 photooxidation conditions and from 19.8 % to 26.2 % under the O 3 conditions. Using threshold photoionization mass spectrometry based on a vacuum ultraviolet free electron laser, a series of new products were detected at molecular weights of 364, 366, 380, 386, 411, 413, and 414, which could be assigned to the cross-dimers, such as organic peroxides, ester dimers, and organic nitrates. Our study underscores the critical role of monocylic monoterpene limonene in the SOA formation and advances our understanding of the SOA formation in the atmosphere.
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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 | 0.001 |
| 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".