Emissions of air pollutants by Canadian wildfires from 2000 to 2004
Bibliographic record
Abstract
A wildfire emission model, based on the Canadian Forest Fire Behaviour Prediction System and the Canadian weather forecast Global Environmental Multiscale model, was applied to forest fires that occurred in Canada between 2000 and 2004. Emissions of 21 chemical species and injection heights were calculated hourly for a regular 0.4° grid, with injection heights corresponding to the maximum altitude reached by a convective plume over a fire every hour. Wildfire emissions were compared with anthropogenic fossil fuel combustion sources at provincial, territorial and national levels. The 2002 fire season in central Quebec accounted for ~30, 60 and 80% of the annual primary greenhouse gases, carbon monoxide and black carbon emissions respectively for that province. In 2003, fires represented 60 and 20% of greenhouse gas emissions in Manitoba and British Columbia respectively. During the 2004 fire season in north-western Canada, when area burned was above average, fires were responsible for almost all greenhouse gas emissions occurring in the sparsely populated Yukon Territory and Northwest Territories. On average, between 2000 and 2004, fires contributed 10, 30 and 40% of Canadian annual greenhouse gases, CO and black carbon emissions respectively. This methodology for calculating wildland fire emissions is also applicable to other regions of the world.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".