Observations of Acyl Peroxy Nitrates During the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ)
Bibliographic record
Abstract
Abstract We report on measurements of acyl peroxy nitrates (APNs) obtained from two ground sites and the NSF/National Center for Atmospheric Research C‐130 aircraft during the 2014 Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ). The relative abundance of the APNs observed at the Boulder Atmospheric Observatory (BAO) indicates that anthropogenic emissions of volatile organic compounds (VOCs) are the dominant drivers of photochemistry during days with the most elevated peroxyacetyl nitrate (PAN). Reduced major axis regression between propionyl peroxynitrate (PPN) and PAN observed at BAO and from the C‐130 produced a slope of 0.21 (R2 = 0.92). Periods of lower PPN/PAN ratios (~0.10) were associated with cleaner background air characterized by lower ammonia and formic acid abundances. The abundance of methacryloyl peroxynitrate relative to PAN only exceeded 0.05 at BAO when PAN mixing ratios were <300 parts per trillion by volume, implying low influence of isoprene oxidation during periods with substantial local PAN production. We show an example of a day (19 July) where high O3 was not accompanied by enhanced local PAN production. The contribution of biogenic VOCs to local O3 production on the other days in July with elevated O3 (22, 23, 28, and 29 July 2014) was small; evidence is provided in the high abundance of PPN to PAN (slopes between 0.18 and 0.26). The PAN chemistry observed from surface and aircraft platforms during FRAPPÉ implies that anthropogenic VOCs played a dominant role in PAN production during periods with the most O3 and that the relative importance of biogenic hydrocarbon chemistry decreased with increasing O3 production during FRAPPÉ.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".