Measurements of CO, HCN, and C2H6 total columns in smoke plumes transported from the 2010 Russian boreal forest fires to the Canadian high arctic
Bibliographic record
Abstract
In August 2010, simultaneous enhancements of aerosol optical depth and total columns of carbon monoxide (CO), hydrogen cyanide (HCN), and ethane (C2H6) were observed at the Polar Environment Atmospheric Research Laboratory (PEARL, 80.05°N, −86.42°W, 0.61 km above sea level, Eureka, Nunavut, Canada). Moderate Resolution Imaging Spectroradiometer (MODIS) hot spots, Ozone Monitoring Instrument (OMI) aerosol index maps, and Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) back-trajectories were used to attribute these enhancements to an intense boreal fire event occurring in Russia. A ground-based Fourier Transform InfraRed (FTIR) spectrometer at PEARL provided vertically integrated measurements of trace gases transported in smoke plumes. We derived HCN and C2H6 equivalent emission ratios with respect to CO of 0.0054 ± 0.0022 and 0.0108 ± 0.0036, respectively, and converted them into equivalent emission factors of 0.66 ± 0.27 g kg−1 and 1.47 ± 0.50 g kg−1 (in grams of gas per kilogram of dry biomass burnt, with one-sigma uncertainties). These emission factors add new observations to the relatively sparse datasets available and can be used to improve the simulation of biomass burning fire emissions in chemical transport models. These emission factors for the boreal forest are in agreement with the mean values recently reported in a compilation study.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".