Which atmospheric processing of biomass burning organic aerosol produces the most singlet oxygen: photochemical aging or dilution?
Bibliographic record
Abstract
Atmospheric organic aerosols containing chromophores undergo excitation upon absorbing visible and UV light. These chromophores are integral components of brown carbon (BrC), predominantly originating from incomplete combustion sources such as forest fires, biomass burning, and cooking. When exposed to light BrC can act as photo-sensitizers, generating reactive oxygen species (ROS), including singlet oxygen (1O2). 1O2 is a competitive ROS species within atmospheric aerosols and can be produced in diverse environmental matrices, including cloud water, fog water, rainwater, and particulate matter extracts. However, the relative sources and sinks of 1O2 depend on the chromophores present in the biomass burning organic aerosols (BBOA), and the chemical composition of these chromophores evolves during atmospheric processing with unknown implications for 1O2 production. This study aims to quantify the impact of atmospheric aging, including dilution and photochemical processing, on the ability of BBOA to sensitize 1O2.To assess this goal, we combusted different biomass samples, i.e. straw, cow dung, beechwood, and plastic in the PSI smog chamber. On quartz filters we collected the primary organic aerosols generated after the burning of each sample from a holding tank. Next, we aged the BBOA via two different pathways: UV aging and dilution. First, BBOA was collected after photooxidation treatment using a Potential Aerosol Mass (PAM) chamber. Second, the BBOA was passed through a heated diffusion dryer to simulate dilution of the plume. Our method involves extracting filters with acetonitrile to obtain the non-soluble fraction of BBOA, in which we expect to find the most effective sensitizers for 1O2. In these solvent extracts, we added furfuryl alcohol as a 1O2 probe and exposed the extracts to UVA light in a photochemical reactor. We measured the pseudo-first order kinetics of 1O2 to calculate singlet oxygen quantum yield and steady-state concentration.The results show an increase in quantum yield when the photooxidation process occurs, i.e. of about 3% for beechwood samples. This outcome suggests that aged chromophores through indirect photochemistry are more effective sensitizers. Remarkably, we observed a decrease in quantum yield of BBOA due to dilution, of about 1% and 3% for straw and beechwood respectively. This result might imply that the most effective chromophores are volatile and partitioning to the gas phase during dilution, with important implications for evolving BBOA plumes. When changing the burning fuel, this trend always appeared showing a possible change in the quantity and quality of the chromophores present. Moreover, 1O2 quantum yield and steady-state concentrations differ within the type of fuel, such as beechwood showing higher values compared to straw, highlighting the importance of analyzing different biomass burning organic materials. Our experimental results offer insights into how different atmospheric processing can impact the production of 1O2, useful for the development of a global model that encompasses both chromophores and 1O2 production.
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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".