The Midlatitude North American Background Aerosol and Global Aerosol Variation
Bibliographic record
Abstract
Protocols for the particulate matter (PM) National Ambient Air Quality Standards (NAAQS), and the Regional Haze Rule (RHR) give two complementary definitions for "natural" background airborne particle concentrations in the United States. The definition for the NAAQS derives largely from reported annual averages, whereas the definition for the RHR takes into account the frequency of occurrence of a range of visibility conditions estimated using fine particle composition. These definitions are simple, static representations of background or "unmanageable" aerosol conditions in the United States. An accumulation of data from rural-remote sites representing global conditions indicates that the airborne particle concentrations are highly variable. Observational campaigns show weather-related variations, including incidents of regional or intercontinental transport of pollution that influence background aerosol levels over midlatitude North America. Defining a background in North America based on long-term observations relies mainly on the remote-rural IMPROVE network in the United States, with a few additional measurements from Canada. Examination of the frequency of occurrence of mass concentrations and particle components provides insight not only about annual median conditions but also the variability of apparent background conditions. The results of this analysis suggest that a more elaborate approach to defining an unmanageable background could improve the present approach taken for information input into the U.S. regulatory process. An approach interpreting the continental gradients in fine PM (PM2.5) concentrations and composition may be warranted.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".