Concentrations, properties, and sources of ice nucleating particles in remote Canadian environments
Bibliographic record
Abstract
Ice nucleating particles (INPs) are particles that cause heterogeneous ice nucleation in the atmosphere. INPs affect the formation and properties of ice and mixed-phase clouds and therefore influence the radiative forcing of the Earth-atmosphere system. However, the climatic effect of INPs is poorly understood, in part, because the concentrations, properties, and sources of INPs are not well understood, especially at remote locations. In the following dissertation, the concentrations, properties, and sources of INPs in remote Canadian environments are investigated. The environments studied included three coastal marine sites (two at mid-latitude and one in the Arctic), one ground site in the Arctic boundary layer, and the Arctic free troposphere. The concentrations of INPs at -25 oC were found to range from 0.01 to 3 L-1, and the INP concentrations measured in the Arctic were lower than that at mid-latitude. At the three coastal marine sites, the ice nucleating ability of aerosol particles was found to be dependent on the particle size with larger particles being more efficient at nucleating ice. Mineral dust was likely a major component of the supermicron INPs, and sea spray aerosol was not likely the major source of INPs at these sites. At the ground site in the Arctic boundary layer, INP concentrations at -25 oC were correlated with tracers of mineral dust, anti-correlated with tracers of sea spray aerosols, and not correlated with tracers of anthropogenic aerosols, which suggest that mineral dust was a major contributor to the INP population at this site. The majority of the particles collected in the Arctic free troposphere were mineral dust, and aluminosilicates and silicates were the major mineral types. A large fraction of the mineral dust was internally mixed with inorganic species (e.g., sea salt and sulfates). Particle dispersion modelling suggested iii that mineral dust particles collected at both ground level and in the free troposphere were transported over long distances from East Asia. The results presented in this dissertation increase our understanding of the concentrations, properties, and sources of atmospheric INPs, and should be useful to constrain models of INPs.
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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 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| 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".