Airborne hydrogen cyanide measurements using a chemical ionisation mass spectrometer for the plume identification of biomass burning forest fires
Bibliographic record
Abstract
Abstract. A Chemical Ionisation Mass Spectrometer (CIMS) was developed for measuring hydrogen cyanide (HCN) from biomass burning events in Canada using I− reagent ions on board the FAAM BAe-146 research aircraft during the BORTAS campaign in 2011. The ionisation scheme enabled highly sensitive measurements at 1 Hz frequency through biomass burning plumes in the troposphere. A strong correlation between the HCN, carbon monoxide (CO) and acetonitrile (CH3CN) was observed, indicating the potential of HCN as a biomass burning (BB) marker. A plume was defined as being 6 standard deviations above background for the flights. This method was compared with a number of alternative plume defining techniques employing CO and CH3CN measurements. The 6 sigma technique produced the highest R2 values for correlations with CO. A Normalised Excess Mixing Ratio (NEMR) of 3.76 ± 0.022 pptv ppbv−1 was calculated which is within the range quoted in previous research (Hornbrook et al., 2011). The global tropospheric model STOCHEM-CRI incorporated both the observed ratio and extreme ratios derived from other studies to generate global emission totals of HCN via biomass burning. Using the ratio derived from this work the emission total for HCN from BB was 0.92 Tg (N) yr−1.
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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) | 0.001 | 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".