New-particle formation, growth and climate-relevant particle production in Egbert, Canada: analysis from 1 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, preexisting 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 1 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 occur 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 are similar to those measured at other midlatitude 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 at Egbert often occurs 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 occurs when air flows from the polluted regions to the south and southwest of Egbert. The new-particle-formation 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) | 0.001 | 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 | 0.001 | 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".