The episodic nature of air pollution transport from Asia to North America
Bibliographic record
Abstract
We employ the Geophysical Fluid Dynamics Laboratory (GFDL) global chemistry transport model (GCTM) to address the episodic nature of trans‐Pacific pollution. The strongest Asian CO episodes over North America (NA), occurring most frequently between February and May, are often associated with disturbances that entrain pollution over eastern Asia and amplify over the western Pacific Ocean. Using 55 ppb of Asian CO as a criterion for major events, we find that during a typical year three to five Asian pollution events analogous to those observed by Jaffe et al. [1999] are expected in the boundary layer all along the U.S. West Coast between February and May. In contrast to CO, Asia currently has a small impact on the magnitude and variability of background ozone arriving over NA from the west. Direct and indirect Asian contributions to episodic O3 events over the western United States are generally in the 3–10 ppbv range. The two largest total O3 events (>60 ppbv), while having trajectories which pass over Asia, show negligible impact from Asian emissions. However, this may change. A future emission scenario in which Asian NOx emissions increase by a factor of 4 from those in 1990 produces late spring ozone episodes at the surface of California with Asian contributions reaching 40 ppb. Such episodic contributions are certain to exacerbate local NA pollution events, especially in elevated areas more frequently exposed to free tropospheric and more heavily Asian‐influenced air.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".