Formation of aqueous-phase α-hydroxyhydroperoxides (α-HHP): potential atmospheric impacts
Bibliographic record
Abstract
Abstract. The focus of this work is on quantifying the degree of the aqueous-phase formation of α-hydroxyhydroperoxides (α-HHPs) via reversible nucleophilic addition of H2O2 to aldehydes. Formation of this class of highly oxygenated organic hydroperoxides represents a poorly characterized aqueous-phase processing pathway that may lead to enhanced SOA formation and aerosol toxicity. Specifically, the equilibrium constants of α-HHP formation have been determined using proton nuclear-magnetic-resonance (1H NMR) spectroscopy and proton-transfer-reaction mass spectrometry (PTR-MS). Significant α-HHP formation was observed from formaldehyde, acetaldehyde, propionaldehyde, glycolaldehyde, glyoxylic acid, and methylglyoxal, but not from methacrolein and ketones. Low temperatures enhanced the formation of α-HHPs but slowed their formation rates. High inorganic salt concentrations shifted the equilibria toward the hydrated form of the aldehydes and slightly suppressed α-HHP formation. Using the experimental equilibrium constants, we predict the equilibrium concentration of α-HHPs to be in the μM level in cloud water, but it may also be present in the mM level in aerosol liquid water (ALW), where the concentrations of H2O2 and aldehydes can be high. Formation of α-HHPs in ALW may significantly affect the effective Henry's law constants of H2O2 and aldehydes but may not affect their gas-phase levels. The photochemistry and reactivity of this class of atmospheric species have not been studied.
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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 | 0.001 |
| 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".