ACE-FTS observations of pyrogenic trace species in boreal biomass burning plumes during BORTAS
Bibliographic record
Abstract
Abstract. To further our understanding of the effects of biomass burning emissions on atmospheric composition, the Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites (BORTAS) campaign was conducted on 12 July to 3 August 2011 during the Boreal forest fire season in Canada. The simultaneous aerial, ground and satellite measurement campaign sought to record instances of Boreal biomass burning to measure the tropospheric volume mixing ratios (VMRs) of short- and long-lived trace molecular species from biomass burning emissions. The goal was to investigate the connection between the composition and the distribution of these pyrogenic outflows and their resulting perturbation to atmospheric chemistry, with particular focus on oxidant species to determine the overall impact on the oxidizing capacity of the free troposphere. Measurements of pyrogenic trace species in Boreal biomass burning plumes were made by the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) onboard the Canadian Space Agency (CSA) SCISAT-1 satellite during the BORTAS campaign. Even though most biomass burning smoke is typically confined to the boundary layer, emissions are often injected directly into the upper troposphere via fire-related convective processes, thus allowing space-borne instruments to measure these pyrogenic outflows. An extensive set of 15 molecules, CH3OH, CH4, C2H2, C2H6, C3H6O, CO, HCN, HCOOH, HNO3, H2CO, NO, NO2, OCS, O3 and PAN have been analyzed. Included in this analysis is the calculation of age-dependent sets of enhancement ratios for each of the species.
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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 | 0.001 | 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".