How quality and quantity of brown carbon influence singlet oxygen production in aqueous organic aerosols
Bibliographic record
Abstract
Singlet oxygen (1O2) is a reactive oxygen species that has recently gained attention as a competitive oxidant in the atmosphere. This excited state of molecular oxygen is formed by indirect photochemistry in the presence of chromophoric dissolved organic matter (DOM) as sensitizers, molecular oxygen and sunlight. The produced highly reactive intermediate 1O2 is then capable of oxidizing and degrading many organic atmospheric components, thereby affecting their lifetime in the atmosphere. Despite this influence on atmospheric fate, the spatiotemporal distribution of 1O2 in particular matter (PM) is currently unknown. We hypothesized that brown carbon in biomass burning organic aerosols emitted during winter in Switzerland would lead to higher 1O2 steady-state concentrations in PM compared to summer. Therefore, to advance atmospheric 1O2 research, we investigated the 1O2 sensitizing ability of organic aerosols sampled on 24-hour PM10 filters. Specifically, these filters were collected throughout 2013 in Frauenfeld and San Vittore in Switzerland, characterized as urban background and rural traffic measurement stations, respectively. We extracted the water-soluble organic components and quantified 1O2 steady state concentrations as well as 1O2 quantum yield. The quantum yield enhances the data intercomparison as this value shows the normalization of 1O2 production as a function of the rate of absorbance of the organic aerosols. In our ongoing efforts of expanding the spatiotemporal scale of our measurements, our results from Frauenfeld so far show a range between 0.38 – 6.05 · 10-13 M for 1O2 steady state concentrations and quantum yields up to 2.1± 0.5%. In preliminary experiments, samples from the rural site San Vittore show similar values, with potentially higher values during periods of significant biomass burning contributions. The values underline 1O2’spotential importance for atmospheric processing, e.g. comparing to Manfrin et al. (ES&T, 2019)1 who reported 1O2 steady state concentrations of 3 ± 1 · 10-14 M from secondary organic aerosols extracts. More importantly, the filter extracts analyzed thus far show a strong seasonal trend, with increased 1O2 values and higher variability in winter as compared to summer. This result corroborates the hypothesis that there is more chromophoric DOM present in winter, due to a higher fraction of brown carbon emitted e.g. in biomass burning for residential heating. To extend this analysis, we are currently correlating the results for 1O2 with molecular markers based on mass spectrometry data available from previous filter analysis provided by Daellenbach et al., (ACP, 2017)2. Finding these correlations will enable the prediction of 1O2 sensitizing abilities of organic material present in the aerosols both qualitatively and quantitatively. In all, our work will help constrain the seasonal relevance of 1O2 photochemistry in the atmosphere. References 1. Manfrin, A. et al. Reactive Oxygen Species Production from Secondary Organic Aerosols: The Importance of Singlet Oxygen. Environmental Science & Technology 53, 8553–8562 (2019). 2. Daellenbach, K. R. et al. Long-term chemical analysis and organic aerosol source apportionment at nine sites in central Europe: source identification and uncertainty assessment. Atmospheric Chemistry and Physics 17, 13265–13282 (2017).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 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".