Chemical characteristics of North American surface layer outflow: Insights from Chebogue Point, Nova Scotia
Bibliographic record
Abstract
We present a factor analysis‐based method for differentiating air masses on the basis of source influence and apply the method to a broad suite of trace gas and aerosol measurements collected at Chebogue Point, Nova Scotia, during the summer of 2004 to characterize the chemical composition of atmospheric outflow from eastern North America. CO, ozone, and aerosol mass were elevated by 30%, 56%, and more than 300% at Chebogue Point during U.S. outflow periods. Organic aerosol mass was highest during U.S. pollution events, but made up the largest fraction (70%) of the total aerosol during periods of primary and especially secondary biogenic influence, indicating the importance of both anthropogenic and biogenic organic aerosol. Anthropogenic and oxygenated volatile organic compounds account for the bulk of the gas‐phase organic carbon under most conditions; however, biogenic compounds are important in terms of chemical reactivity. Biogenic emissions thus have a significant impact on the chemistry of air masses downwind of the polluted northeastern United States. Using output from a global 3‐D model of atmospheric composition (GEOS‐Chem), we estimate that CO directly emitted from U.S. pollution sources makes up 28% of the total CO observed at Chebogue Point during U.S. outflow events and 19% at other times, although more work is needed to improve U.S. emission estimates for CO and other pollutants. We conclude that the effects of North American pollution on the chemistry of the western North Atlantic boundary layer are pervasive and not restricted to particular events.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".