Rapid Nighttime Darkening of Biomass Burning Brown Carbon by Nitrate Radicals Is Suppressed by Prior Daytime Photochemical Aging
Bibliographic record
Abstract
Brown carbon (BrC) carbonaceous aerosol affects climate through its ability to absorb light. Here, we investigate in an environmental chamber the changes to the optical properties of water-soluble biomass burning organic aerosol (BBOA) particles that arise via exposure to gas-phase NO 3 radicals, as occurs at night in the atmosphere. Low mixing ratios (1–2 ppt) of NO 3 lead to absorption enhancement by a factor of 2 at 375 nm via extremely rapid processing, on the time scale of 15 min, with the aging occurring faster and more extensively at a lower relative humidity (10 ± 3%) than at higher values (50 ± 10%). Prior daytime aging processes of the BBOA material lead to suppressed absorption enhancement at 375 nm by subsequent NO 3 oxidation. In particular, samples with 2 h of aqueous OH radical oxidation or 3 h of ultraviolet (UV) light exposure displayed a decrease of 52 and 32% of absorption at 375 nm, respectively, relative to no prior aging, indicating competitive mechanisms and common reactive entities within the BBOA. Even longer prior aqueous OH exposure largely removed the NO 3 absorption enhancement. Lastly, UV exposure after NO 3 aging led to absorption photoenhancement from 375 to 625 nm but at a slower rate than without prior NO 3 exposure. These results point to strong diurnal effects in the optical aging of BBOA particles, with the darkening that will rapidly occur via nighttime NO 3 exposure strongly modulated by prior photochemical processing in the preceding daytime.
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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".