Changes in ozone and precursors during two aged wildfire smoke events in the Colorado Front Range in summer 2015
Bibliographic record
Abstract
Abstract. The relative importance of wildfire smoke for air quality over the western US is expected to increase as the climate warms and anthropogenic emissions decline. We report on in situ measurements of ozone (O3), a suite of volatile organic compounds (VOCs), and reactive oxidized nitrogen species collected during summer 2015 at the Boulder Atmospheric Observatory (BAO) in Erie, CO. Aged wildfire smoke impacted BAO during two distinct time periods during summer 2015: 6–10 July and 16–30 August. The smoke was transported from the Pacific Northwest and Canada across much of the continental US. Carbon monoxide and particulate matter increased during the smoke-impacted periods, along with peroxyacyl nitrates and several VOCs that have atmospheric lifetimes longer than the transport timescale of the smoke. During the August smoke-impacted period, nitrogen dioxide was also elevated during the morning and evening compared to the smoke-free periods. There were nine empirically defined high-O3 days during our study period at BAO, and two of these days were smoke impacted. We examined the relationship between O3 and temperature at BAO and found that for a given temperature, O3 mixing ratios were greater (∼ 10 ppbv) during the smoke-impacted periods. Enhancements in O3 during the August smoke-impacted period were also observed at two long-term monitoring sites in Colorado: Rocky Mountain National Park and the Arapahoe National Wildlife Refuge near Walden, CO. Our data provide a new case study of how aged wildfire smoke can influence atmospheric composition at an urban site, and how smoke can contribute to increased O3 abundances across an urban–rural gradient.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".