Peroxyacetyl nitrate photochemistry and interactions with the Arctic surface
Bibliographic record
Abstract
Peroxyacetyl nitrate (PAN) is a NOx reservoir compound that has the ability to transport NOx to remote environments, allowing for NOx photochemistry and/or deposition of nitrogen to these clean locations. Measurements of PAN have been made at Alert, Nunavut, and Summit, Greenland, aimed at understanding the impact of PAN chemistry on atmospheric nitrogen in the Arctic. These measurements show concentrations of PAN that are only slowly varying, even during ozone depletion events at polar sunrise, when free radical photochemistry is relatively active. We used a zero‐dimensional photochemical model incorporating known gas‐phase chemistry to simulate the observed behavior of PAN at Alert, Nunavut, and Summit, Greenland. The model simulations suggest a substantial net production rate for PAN over sunlit surfaces, which is inconsistent with the measured gas‐phase concentrations. These observations thus indicate a fundamental problem with our understanding of PAN chemistry in low‐temperature, snow‐covered environments. We explore the possibility that we are missing an important sink for atmospheric PAN above snow‐covered surfaces. If the loss is caused by snowpack deposition, the data result in calculated deposition velocities ranging from 0.05 to 1 cm s−1, which would represent a significant fraction of the unidentified total nitrate input to the snowpack and glacial ice at Summit, Greenland.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".