Gas-Phase Nitrate Radical Production Using Irradiated Ceric Ammonium Nitrate: Insights into Secondary Organic Aerosol Formation from Biogenic and Biomass Burning Precursors
Bibliographic record
Abstract
The importance of nitrate radicals (NO 3 ) as an atmospheric oxidant is well-established. For decades, laboratory studies of multiphase NO 3 chemistry have used the same methods – either NO 2 + O 3 reactions or N 2 O 5 thermal decomposition – to generate NO 3 as it occurs in the atmosphere. These methods, however, come with limitations, especially for N 2 O 5, which must be produced and stored under cold and dry conditions until its use. Recently, we developed a new photolytic source of gas-phase NO 3 by irradiating aqueous solutions of ceric ammonium nitrate and nitric acid. In this study, we adapted the method to maintain stable NO 3 concentrations for over 24 h. We applied the method in laboratory oxidation flow reactor (OFR) experiments to measure the yield and chemical composition of oxygenated volatile organic compounds (OVOCs) and secondary organic aerosol (SOA) formed from NO 3 oxidation of volatile organic compounds (VOCs) emitted by biogenic sources (isoprene, β-pinene, limonene, and β-caryophyllene) and biomass burning sources (phenol, guaiacol, and syringol). SOA yields and elemental ratios were typically within a factor of 2 and 10%, respectively, of those obtained in studies using conventional NO 3 sources. Maximum SOA yields obtained in our studies ranged from 0.02 (isoprene/NO 3 ) to 0.96 (β-caryophyllene/NO 3 ). The highest SOA oxygen-to-carbon ratios (O/C) ranged from 0.48 (β-caryophyllene/NO 3 ) to 1.61 (syringol/NO 3 ). Additionally, we characterized novel condensed-phase oxidation products from syringol/NO 3 reactions. Overall, the use of irradiated aqueous cerium nitrate as a source of gas-phase NO 3 may enable more widespread studies of NO 3 -initiated oxidative aging, which has been less explored compared to that of hydroxyl radical chemistry.
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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".