Unprecedented Atmospheric Ammonia Concentrations Detected in the High Arctic From the 2017 Canadian Wildfires
Bibliographic record
Abstract
Abstract From 17–22 August 2017 simultaneous enhancements of ammonia (NH3), carbon monoxide (CO), hydrogen cyanide (HCN), and ethane (C2H6) were detected from ground‐based solar absorption Fourier transform infrared (FTIR) spectroscopic measurements at two high‐Arctic sites: Eureka (80.05°N, 86.42°W) Nunavut, Canada, and Thule (76.53°N, 68.74°W), Greenland. These enhancements were attributed to wildfires in British Columbia and the Northwest Territories of Canada using FLEXPART back‐trajectories and fire locations from Moderate Resolution Imaging Spectroradiometer (MODIS) and found to be the greatest observed enhancements in more than a decade of measurements at Eureka (2006–2017) and Thule (1999–2017). Observations of gas‐phase NH3 from these wildfires illustrate that boreal wildfires may be a considerable episodic source of NH3 in the summertime high Arctic. Comparisons of GEOS‐Chem model simulations using the Global Fire Assimilation System (GFASv1.2) biomass burning emissions to FTIR measurements and Infrared Atmospheric Sounding Interferometer (IASI) measurements showed that the transport of wildfire emissions to the Arctic was underestimated in GEOS‐Chem. However, GEOS‐Chem simulations showed that these wildfires contributed to surface layer NH3 and NH enhancements of 0.01–0.11 ppbv and 0.05–1.07 ppbv, respectively, over the Canadian Archipelago from 15–23 August 2017.
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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 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".