Uptake and Mobilization of Organic Chemicals with Clouds: Evidence from a Hail Sample
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) were measured in hail samples collected during a storm that occurred on a spring morning in Toronto, Canada. The presence of these organic chemicals in hail suggests that clouds likely provide an atmospheric transport pathway for these substances in the free atmosphere. Results reported here may carry significant implications for atmospheric transport, mass balance, tropospheric cold trapping, and environmental fate of organic chemicals. Backward trajectories along with measured and modeled cloud cover show that clouds causing the hail event were formed and advected from the midwestern and southeastern United States. After being emitted to the atmosphere, the organic chemicals were likely lifted by atmospheric ascending motions to a higher atmospheric elevation and partitioned onto clouds. These clouds then carry the organic chemicals to a downwind location where they are deposited to the ground surface via precipitation. We found that the organic chemicals with high solubility and vapor pressure tend to partition into clouds through sorption to cloudwater droplets and ice particles. It was found that approximately 7-30% of pyrene could be sorbed into cloudwater droplets and ice particles in this hail event at the expense of reduced gas-phase concentrations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".