Ozone production from Canadian wildfires during June and July of 1995
Bibliographic record
Abstract
During the summer of 1995, especially between June and mid July, extensive wildfires occurred throughout Canada, primarily north of 55°N latitude. A previous report used aircraft and surface observations and tracer simulations to show these fires strongly influenced CO concentrations as far south as 35°N in the central and eastern United States [ Wotawa and Trainer , 2000 ]. This study extends those results by incorporating wildfire emissions estimates for CO, NO x , and nonmethane hydrocarbons into a three‐dimensional photochemical transport model specifically designed to simulate ozone photochemistry in the continental United States. The results of the model are compared to observations from four measurement platforms deployed during the time period of interest: National Oceanic and Atmospheric Administration WP‐3 aircraft observations collected during the 1995 Southern Oxidants Study (SOS‐95) field campaign; 12 eastern U.S. surface stations that measured ozone, CO, and NO y ; rural ozone measurements from the Aerometric Information Retrieval System network collected by the U.S. Environmental Protection Agency; and daily ozonesondes obtained near Nashville, Tennessee, during SOS‐95. Model performance, as determined by correlation and bias with observations from these four platforms, is significantly improved for both O 3 and CO when the Canadian fires are considered. Both observations and model results show enhanced O 3 from air transported from the Northwest Territory. The model results imply that during the period of strongest fire influence 10 to 30 ppbv enhancement of O 3 throughout a large region of the central and eastern United States was due to these fires. Modeled O 3 increases are sensitive to the NO x /CO emission ratio assumed for the fires, which is highly uncertain and variable. A molar NO x /CO ratio of 0.007 yields model comparisons that are most consistent for O 3 and ΔO 3 /ΔCO observations within aged fire plumes during SOS‐95, and is also consistent with previously observed NO x /CO ratios from boreal fires. For this NO x /CO emission ratio, and considering the entire eastern United States, most of the O 3 increase is associated with the NO x emitted directly by the fires and the photochemical O 3 formation that occurs before the plumes actually reach the United States. However, the in situ oxidation of CO from the Canadian fires with NO x emitted locally leads to significantly higher O 3 increases for high‐NO x ‐emitting regions that are limited by hydrocarbon availability. Thus O 3 in urban areas, or any other region modified by nearby NO x sources, is more sensitive to long‐range fires compared to less populated or polluted regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".