Impact of Nitrate and Iron Ions on Uptake Coefficients and Condensed Phase Products From the Reaction of Gaseous NO<sub>2</sub> With HULIS Proxies
Bibliographic record
Abstract
Abstract Humic‐like substances (HULIS) are a ubiquitous reactive component of atmospheric aerosol. They participate in the formation of secondary organic aerosols via chemical reactions with atmospheric oxidants. Here, we assess the influence of transition metal ions (namely ferric iron, Fe(III)), and nitrate ions () on the heterogeneous reaction of gaseous NO2 with an aqueous film containing gallic acid (GA) or tannic acid (TA) as proxies for HULIS. Using a vertical wetted wall flow tube technique, the uptake coefficients of gaseous NO2 on GA and TA increased nonlinearly with increasing [Fe(III)], in dark and under light irradiation. However, the combined effect of both ions, Fe(III) and , led to a substantial decrease in NO2 uptake in the dark and under simulated near‐UV sunlight irradiation (300 < λ < 400 nm). The lifetime of GA in dilute aqueous phase, which corresponds to cloud water, due to reaction with NO2 would be 6 hr during both nighttime and daytime. However, the lifetime of GA in aerosol particles which contain both ions, that is, Fe(III) and , would increase to 27 hr during nighttime and 11 days and 6 hr due to light‐induced reaction with NO2. Also, we observed, using Fourier transform ion cyclotron resonance mass spectrometry, the formation of nitrocatechols compounds (e.g., methyl‐nitrocatechol), which contribute to brown carbon. Compounds with reduced functional groups such as amines were also observed in the presence of iron and nitrate ions in the dark and under irradiation, indicating that Fe(III) and , can influence the kinetics and product distribution in deliquescent aerosol particles.
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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".