Exceptional Wildfire Enhancements of PAN, C<sub>2</sub>H<sub>4</sub>, CH<sub>3</sub>OH, and HCOOH Over the Canadian High Arctic During August 2017
Bibliographic record
Abstract
Abstract Extreme enhancements in the total columns of carbon monoxide (CO), peroxyacetyl nitrate (PAN), ethylene (C2H4), methanol (CH3OH), and formic acid (HCOOH) were observed over the Canadian high Arctic during the period of 17–22 August 2017 by a ground‐based Fourier transform infrared (FTIR) spectrometer at Eureka, Nunavut (80.05°N, 86.42°W), and by the Infrared Atmospheric Sounding Interferometer (IASI) satellite instruments. These enhancements have been attributed to wildfires in British Columbia (BC) and the Northwest Territories (NWT) of Canada, and represent the largest short‐term perturbations of PAN, C2H4, and HCOOH above ambient concentrations over the 14‐year (2006–2020) Eureka time‐series. Enhancement ratios, emission ratios, and emission factors relative to CO were calculated for all species for both FTIR and IASI observations. The C2H4 and HCOOH emission factors are significantly larger than previous studies, suggesting unusually high emissions from these fires. The wildfire plumes were also simulated using the GEOS‐Chem model. Initial GEOS‐Chem simulations displayed a severe under‐estimation relative to observations for these fire plumes resulting from the injection height scheme of the model. Sensitivity tests highlighted that injection heights of 12.5 km for BC (based on previous studies) and 10 km for the NWT fires yielded the strongest correlations with ground‐based measurements. Applying these injection heights to the model significantly improves the simulated plume transport and agreement with ground‐ and space‐based observations. GEOS‐Chem was also used to estimate the magnitude of secondary in‐plume production of CH3OH and HCOOH; it was found to be an important component (∼18%) of the enhanced HCOOH columns at Eureka.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".