Composition of Size-Resolved Aged Boreal Fire Aerosols: Brown Carbon, Biomass Burning Tracers, and Reduced Nitrogen
Bibliographic record
Abstract
Aerosols that were size-resolved into 13 fractions between 10 nm and 18 μm were collected from an aged boreal forest wildfire plume in July 2013. Samples were extracted into water and analyzed for molecular-size-resolved brown carbon (BrC), biomass burning (BB) markers, reduced nitrogen compounds, and elemental composition. Absorption of BrC was primarily in fine-mode aerosols and dominated by high-molecular-weight compounds (>500 Da). The molecular size distribution of BrC was conserved across aerosol sizes, with a decrease in the importance of large molecules in smaller aerosols. The aerosol-size-resolved composition of BrC absorption was different than those of the two BB markers, non-sea-salt potassium and levoglucosan, suggesting that they may not be suitable for identifying BB BrC in aged plumes. Strong correlations were observed between BrC and the reduced nitrogen compounds ammonium, dimethylamine, and diethylamine. In aerosols with high BrC and reduced nitrogen, there was a strong cationic excess. These observations could be caused by (i) uptake of ammonium and alkylamines to form stable salts with organic acids or (ii) reactive uptake to form imines or enamines that were hydrolyzed during the BrC extraction process.
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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 | 0.001 | 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) | 0.000 | 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".