Origin, variability and age of biomass burning plumes intercepted during BORTAS-B
Bibliographic record
Abstract
Abstract. We use the GEOS-Chem atmospheric chemistry transport model to interpret aircraft measurements of carbon monoxide (CO) in biomass burning outflow taken during the 2011 BORTAS-B campaign over eastern Canada. The model has some skill reproducing the observed variability (r = 0.45) but has a negative bias for observations below 100 ppb and a positive bias above 300 ppb. We find that observed CO variations are largely due to NW North American biomass burning, as expected, with smaller and less variable contributions from fossil fuel combustion from eastern Asia and NE North America. To help interpret observed variations of CO we develop an Eulerian effective age of emissions (A) metric, accounting for mixing and chemical decay, which we apply to pyrogenic emissions of CO. We find that during BORTAS-B the age of emissions intercepted over Halifax, Nova Scotia is typically 4–11 days, and on occasion as young as two days. We show that A is typically 1–5 days older than the associated photochemical ages inferred from colocated measurements of different hydrocarbons. We find that the median difference between the age measures (Δτ) in plumes (CH3CN > 150 ppt) peaks at 3–5 days corresponding to a chemical retardation of 50%. We find a strong relationship in plumes between A and Δτ (r2 = 0.60), which is not evident outwith these plumes (r2 = 0.23). We argue that these observed relationships, together with a robust observed relationship between CO and black carbon aerosol during BORTAS-B (r2 > 0.7), form the basis of indirect evidence that aerosols co-emitted with gases during pyrolysis markedly slowed down the plume photochemistry during BORTAS-B with respect to photochemistry at the same latitude and altitude in clear skies.
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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".