Laboratory Investigation of Renoxification from the Photolysis of Inorganic Particulate Nitrate
Bibliographic record
Abstract
Abstract Nitrogen oxides (NOx) play a key role in regulating the oxidizing capacity of the atmosphere through controlling the abundance of O3, OH, and other important gas and particle species. Some recent studies have suggested that particulate nitrate, which is conventionally considered as the ultimate oxidation product of NOx, can undergo “renoxification” via photolysis, recycling NOx and HONO back to the gas phase. However, there are large discrepancies in estimates of the importance of this channel, with reported renoxification rate constants spanning three orders of magnitude. In addition, previous laboratory studies derived the rate constant using bulk particle samples collected on substrates instead of suspended particles. In this work, we study renoxification of suspended submicron particulate sodium and ammonium nitrate through controlled laboratory photolysis experiments using an environmental chamber. We find that, under atmospherically relevant wavelengths and relative humidities, particulate inorganic nitrate releases NOx and HONO less than 10 times as rapidly as gaseous nitric acid, putting our measurements on the low end of recently reported renoxification rate constants. To the extent that our laboratory conditions are representative of the real atmosphere, renoxification from the photolysis of inorganic particulate nitrate appears to play a limited role in contributing to the NOx and OH budgets in remote environments. These results are based on simplified model systems; future studies should investigate renoxification of more complex aerosol mixtures that represent a broader spectrum of aerosol properties to better constrain the photolysis of ambient aerosols.
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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 | 0.001 |
| 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".