Particle formation and growth at five rural and urban sites
Bibliographic record
Abstract
Abstract. Ultrafine particle (UFP) number and size distributions were simultaneously measured at five urban and rural sites during the summer of 2007 in Ontario, Canada as part of the Border Air Quality and Meteorology Study (BAQS-Met 2007). Particle formation and growth events at these five sites were classified based on their strength and persistence as well as the variation in geometric mean diameter. Regional nucleation and growth events and local short-lived strong nucleation events were frequently observed at the near-border rural sites, upwind of industrial sources. Surprisingly, the particle number concentrations at one of these sites were higher than the concentrations at a downtown site in a major city, despite its high traffic density. Regional nucleation and growth events were favored during intense solar irradiance and in less polluted cooler drier air. The most distinctive regional particle nucleation and growth event during the campaign was observed simultaneously at all five sites, which were up to 350 km apart. Although the ultrafine particle concentrations and size distributions generally were spatially heterogeneous across the region, a more uniform spatial distribution of UFP across the five areas was observed during this regional nucleation event. Thus, nucleation events can cover large regions, contributing to the burden of UFP in cities and potentially to the associated health impacts on urban populations. Local short-lived nucleation events at the three near-border sites during this summer three-week campaign were associated with high SO2, which likely originated from US and Canadian industrial sources. Hence, particle formation in southwestern Ontario appears to often be related to anthropogenic gaseous emissions but biogenic emissions at times also contribute. Longer-term studies are needed to help resolve the relative contributions of anthropogenic and biogenic emissions to nucleation and growth in this region.
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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 | 0.000 | 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".