Transatlantic transport of pollution and its effects on surface ozone in Europe and North America
Bibliographic record
Abstract
We examine the transatlantic transport of anthropogenic ozone and its impact on surface ozone in Europe and North America by using a 5‐year (1993–1997) simulation with the GEOS‐CHEM global three‐dimensional model of tropospheric chemistry. Long‐term time series of ozone and CO at Mace Head (Ireland) and Sable Island (Canada) are used to evaluate transatlantic transport in the model. North American anthropogenic emissions contribute on average 5 ppbv to surface ozone at Mace Head, and up to 10–20 ppbv during transatlantic transport events, which are forerunners of broader events in Europe. These events are associated with low‐level westerly flow driven by an intense Icelandic low between Iceland and the British Isles. North American influence on ozone at Mace Head is strongly correlated with the North Atlantic Oscillation (NAO), implying that the NAO index can be used to forecast transatlantic transport of North American pollution to Europe. European anthropogenic emissions contribute on average less than 2 ppbv to surface ozone at Sable Island but up to 5–10 ppbv during transatlantic transport events. These events are associated with low‐level easterly flow established by anomalous low pressure at 45°N over the North Atlantic. North American anthropogenic emissions enhance surface ozone in continental Europe by 2–4 ppbv on average in summer and by 5–10 ppbv during transatlantic transport events; transport in the boundary layer and subsidence from the free troposphere are both important mechanisms. We find in the model that 20% of the violations of the European Council ozone standard (55 ppbv, 8‐hour average) in the summer of 1997 over Europe would not have occurred in the absence of anthropogenic emissions from North America. North American influence on surface ozone in Europe is particularly strong at the thresholds used for the European standards (55–65 ppbv).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".