Detection of HCOOH, CH<sub>3</sub>OH, CO, HCN, and C<sub>2</sub>H<sub>6</sub>in Wildfire Plumes Transported Over Toronto Using Ground‐Based FTIR Measurements From 2002–2018
Bibliographic record
Abstract
Abstract The Fourier transform infrared (FTIR) spectrometer at the University of Toronto Atmospheric Observatory has been operational since 2002, collecting solar absorption spectra from which atmospheric trace gas profiles and columns are retrieved. The time series of total columns of CH3OH and HCOOH over Toronto are presented here for the first time, along with those for CO, HCN, and C2H6. Transport of wildfire plumes over the site results in enhanced columns of biomass burning species. Here we report the detection of biomass burning enhancement events between 2002 and 2018. Several simultaneous enhancements of CO, HCN, and C2H6were observed, and the measured columns were used to derive emission ratios and emission factors for HCN and C2H6for fire events in 2012, 2015, and 2017. From these events, which included plumes from both boreal and temperate forest fires, emission ratios with respect to CO were derived using CO lifetimes of 30 and 61 days. HCN emission ratios range between 0.0037 ± 0.0003 and 0.0057 ± 0.0008, while C2H6emission ratios vary from 0.00122 ± 0.0015 to 0.019 ± 0.001. Enhanced columns of CH3OH and HCOOH were also observed during the 2015 and 2017 events, and emission ratios were derived but have greater uncertainties due to shorter lifetimes and other sources for these gases. The FLEXPART, HYSPLIT, and GEOS‐Chem models were used for source attribution and traveltime estimation. GEOS‐Chem was run in the tagged CO simulation mode and successfully captured the CO enhancements from fires for the 2015 and 2017 events.
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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".