Singlet Oxygen Seasonality in Aqueous PM<sub>10</sub> is Driven by Biomass Burning and Anthropogenic Secondary Organic Aerosol
Bibliographic record
Abstract
The first excited state of molecular oxygen is singlet-state oxygen ( 1 O 2 ), formed by indirect photochemistry of chromophoric organic matter. To determine whether 1 O 2 can be a competitive atmospheric oxidant, we must first quantify its production in organic aerosols (OA). Here, we report the spatiotemporal distribution of 1 O 2 over a 1-year dataset of PM 10 extracts at two locations in Switzerland, representing a rural and suburban site. Using a chemical probe technique, we measured 1 O 2 steady-state concentrations with a seasonality over an order of magnitude peaking in wintertime at 4.59 ± 0.01 × 10 –13 M and with a quantum yield of up to 2%. Next, we identified biomass burning and anthropogenic secondary OA (SOA) as the drivers for 1 O 2 formation in the PM 10 aqueous extracts using source apportionment data. Importantly, the quantity, the amount of brown carbon present in PM 10, and the quality, the chemical composition of the brown carbon present, influence the concentration of 1 O 2 sensitized in each extract. Anthropogenic SOA in the extracts were 4 times more efficient in sensitizing 1 O 2 than primary biomass burning aerosols. Last, we developed an empirical fit to estimate 1 O 2 concentrations based on PM 10 components, unlocking the ability to estimate 1 O 2 from existing source apportionment data. Overall, 1 O 2 is likely a competitive photo-oxidant in PM 10 since 1 O 2 is sensitized by ubiquitous biomass burning OA and anthropogenic SOA.
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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".