New-particle formation, growth and climate-relevant particle production in Egbert, Canada: analysis from one year of size-distribution observations
Bibliographic record
Abstract
Abstract. Aerosol particle nucleation, or new-particle formation, is the dominant contributor to particle number in the atmosphere. However, these particles must grow through condensation of low-volatility vapors without coagulating with the larger, pre-existing particles in order to reach climate-relevant sizes (diameters larger than 50–100 nm), where the particles may affect clouds and radiation. In this paper, we use one year of size-distribution measurements from Egbert, Ontario, Canada to calculate the frequency of regional-scale new-particle formation events, new-particle formation rates, growth rates and the fraction of new particles that survive to reach climate-relevant sizes. Regional-scale new-particle formation events occurred on 14–31% of the days (depending on the stringency of the classification criteria), with event frequency peaking in the spring and fall. New-particle formation rates and growth rates were similar to those measured at other mid-latitude continental sites. We calculate that roughly half of the climate-relevant particles (with diameters larger than 50–100 nm) at Egbert are formed through new-particle formation events. With the addition of meteorological and SO2 measurements, we find that new-particle formation often occurred under synoptic conditions associated with high surface pressure and large-scale subsidence that cause sunny conditions and clean-air flow from the north and west. However, new-particle formation also occurred when air flow came from the polluted regions to the south and southwest of Egbert. The nucleation rates tend to be faster during events under the polluted south/southwest flow conditions.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".