Measurements of the sum of HO <sub>2</sub> NO <sub>2</sub> and CH <sub>3</sub> O <sub>2</sub> NO <sub>2</sub> in the remote troposphere
Bibliographic record
Abstract
Abstract. The chemistry of peroxynitric acid (HO2NO2) and methyl peroxynitrate (CH3O2NO2)is predicted to be particularly important in the upper troposphere where temperatures are frequently low enough that these compounds do not rapidly decompose. At temperatures below 240K, we calculate that about 20% of NOy in the mid- and high-latitude upper troposphere is HO2NO2. Under these conditions, the reaction of OH with HO2NO2 is estimated to account for as much as one third of the permanent loss of hydrogen radicals. During the Tropospheric Ozone Production about the Spring Equinox (TOPSE) campaign, we used thermal dissociation laser-induced fluorescence (TD-LIF) to measure the sum of peroxynitrates (PNs HO2NO2+CH3O2NO2+PAN+PPN+...) aboard the NCAR C-130 research aircraft. We infer the sum of HO2NO2 and CH3O2NO2 as the difference between PN measurements and gas chromatographic measurements of the two major peroxy acyl nitrates, peroxy acetyl nitrate (PAN) and peroxy propionyl nitrate (PPN). Comparison with NOy and other nitrogen oxide measurements confirms the importance of HO2NO2 and CH3O2NO2 to the reactive nitrogen budget and shows that current thinking about the chemistry of these species is approximately correct. During the spring high latitude conditions sampled during the TOPSE experiment, the model predictions of the contribution of (HO2NO2+CH3O2NO2) to NOy are highly temperature dependent: on average 30% of NOy at 230K, 15% of NOy at 240K, and 5% of NOy above 250K. The temperature dependence of the inferred concentrations corroborates the contribution of overtone photolysis to the photochemistry of peroxynitric acid. A model that includes IR photolysis (J=1x10-5s-1) agreed with the observed sum of HO2NO2+CH3O2NO2 to better than 35% below 240K where the concentration of these species is largest.
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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 | 0.000 |
| 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".