Long‐range transport of Siberian biomass burning emissions and impact on surface ozone in western North America
Bibliographic record
Abstract
During the summer of 2003, biomass fires burned a large area of Siberia, the largest in at least 10 years. We used the NRL Aerosol Analysis and Prediction System (NAAPS) model to forecast the transport of the smoke from these fires. Transport of these airmasses to North America was confirmed by aircraft and surface observations. The fires resulted in enhancements in summer background CO and O 3 of 23–37 and 5–9 ppbv, respectively, at 10 sites in Alaska, Canada and the Pacific Northwest. From the area burned, we estimate that the Siberian fires generated 68 Tg of CO and 0.82 Tg of NO x (as N). In addition, we show that the background O 3 enhancement contributed to an exceedance of the ozone air quality standard in the Pacific Northwest. These results show that regional air quality and health are linked to global processes, including climate, forest fires and long‐range transport of pollutants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".