Dynamic Wood Smoke Aerosol Toxicity during Oxidative Atmospheric Aging
Bibliographic record
Abstract
Wildfires are a major source of biomass burning aerosol to the atmosphere, with their incidence and intensity expected to increase in a warmer future climate. However, the toxicity evolution of biomass burning organic aerosol (BBOA) during atmospheric aging remains poorly understood. In this study, we report a unique set of chemical and toxicological metrics of BBOA from pine wood smoldering during multiphase aging by gas-phase hydroxyl radicals (OH). Both the fresh and OH-aged BBOA show activity relevant to adverse health outcomes. The results from two acellular assays (DTT and DCFH) show significant oxidative potential (OP) and reactive oxygen species (ROS) formation in OH-aged BBOA. Also, radical concentrations in the aerosol assessed by electron paramagnetic resonance (EPR) spectroscopy increased by 50% following heterogeneous aging. This enhancement was accompanied by a transition from predominantly carbon-centered radicals (85%) in the fresh aerosol to predominantly oxygen-centered radicals (76%) following aging. Both the fresh and aged biomass burning aerosols trigger prominent antioxidant defense during the in vitro exposure, indicating the induction of oxidative stress by BBOA in the atmosphere. By connecting chemical composition and toxicity using an integrated approach, we show that short-term aging initiated by OH radicals can produce biomass burning particles with a higher particle-bound ROS generation capacity, which are therefore a more relevant exposure hazard for residents in large population centers close to wildfire regions than previously studied fresh biomass burning emissions.
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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".