Atmospheric Evolution of Emissions from a Boreal Forest Fire: The Formation of Highly-Functionalized Oxygen-, Nitrogen-, and Sulfur-Containing Compounds
Bibliographic record
Abstract
Abstract. Forest fires are major contributors of reactive gas- and particle-phase organic compounds to the atmosphere. We used offline high resolution tandem mass spectrometry to perform a molecular-level speciation of evolving gas- and particle-phase compounds sampled via aircraft from a boreal forest fire in Saskatchewan, Canada. We observed diverse multifunctional compounds containing oxygen, nitrogen, and sulfur (CHONS), whose structure, formation, and impacts are understudied. The abundance of particle-phase CHONS species increased with plume age, from 19 % to 40 % of the relative abundance of observed functionalized OA over the first 4 hours of downwind transport. The relative contribution of particle-phase sulfide functional groups increased with age from 4 % to 40 % of observed OA abundance, and were present in up to 75 % of CHONS compounds. The increases in sulfides were accompanied by increases in ring-bound nitrogen, and both increased together with CHONS prevalence. A complex mixture of intermediate- and semi-volatile gas-phase organic sulfur species was emitted from the fire and depleted downwind, representing potential precursors to particle-phase CHONS compounds. These results demonstrate CHONS formation from nitrogen/oxygen-containing biomass burning emissions in the presence of reduced sulfur species, and highlight chemical pathways that may also be relevant in situations with elevated levels of nitrogen and sulfur emissions from residential biomass burning and fossil fuel use (e.g. coal), respectively.
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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 | 0.001 | 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".