Evaporation of aerosol droplets from contaminated cooling tower water
Bibliographic record
Abstract
The evaporation dynamics of water-based aerosol droplets carrying pathogens, such as Legionella from cooling towers, is critical for assessing the risks of airborne transmission. Yet, the evaporation of contaminated aerosol droplets remains poorly understood and is often overlooked by current risk assessment models. Changes in water properties, such as viscosity and surface tension, induced by the presence of nonvolatile solids or contaminants, affect the evaporation time, the droplet nuclei size, and the time resolved size evolution. The effect of these parameters was experimentally and analytically studied. Surfactants lowering surface tension introduced non-linearity in droplet size evolution, extending evaporation time by up to 14% and halting it at high concentrations. Increased viscosity delayed evaporation onset without affecting nuclei size, which remained around 8–9 μm compared to 0.5 μm for reference water droplets. High concentration of solids, covering over 60% of the droplet surface, nearly doubled the evaporation time and increased nuclei size to 20 μm. Existing evaporation models do not fully account for temporal size changes and the variability in nuclei size due to solids concentration. Improving evaporation models and incorporating them into microbial contamination risk assessments are critical to develop effective mitigation strategies, such as using efficient drift eliminators for cooling towers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".