Aqueous-Phase OH Oxidation of Glyoxal: Application of a Novel Analytical Approach Employing Aerosol Mass Spectrometry and Complementary Off-Line Techniques
Bibliographic record
Abstract
Aqueous-phase chemistry of glyoxal may play an important role in the formation of highly oxidized secondary organic aerosol (SOA) in the atmosphere. In this work, we use a novel design of photochemical reactor that allows for simultaneous photo-oxidation and atomization of a bulk solution to study the aqueous-phase OH oxidation of glyoxal. By employing both online aerosol mass spectrometry (AMS) and offline ion chromatography (IC) measurements, glyoxal and some major products including formic acid, glyoxylic acid, and oxalic acid in the reacting solution were simultaneously quantified. This is the first attempt to use AMS in kinetics studies of this type. The results illustrate the formation of highly oxidized products that likely coexist with traditional SOA materials, thus, potentially improving model predictions of organic aerosol mass loading and degree of oxidation. Formic acid is the major volatile species identified, but the atmospheric relevance of its formation chemistry needs to be further investigated. While successfully quantifying low molecular weight organic oxygenates and tentatively identifying a reaction product formed directly from glyoxal and hydrogen peroxide, comparison of the results to the offline total organic carbon (TOC) analysis clearly shows that the AMS is not able to quantitatively monitor all dissolved organics in the bulk solution. This is likely due to their high volatility or low stability in the evaporated solution droplets. This experimental approach simulates atmospheric aqueous phase processing by conducting oxidation in the bulk phase, followed by evaporation of water and volatile organics to form SOA.
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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) | 0.000 | 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 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".