Dispersion of bioaerosols from composting facilities.
Why this work is in the frame
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Bibliographic record
Abstract
The promotion of composting as an option for sustainable waste management has \nraised concerns regarding public health impacts of exposures to potentially \nhazardous bioaerosols. Recent source term experiments show that bioaerosol \nemissions are episodic and that peak emissions are related to compost agitation. \nThe Environment Agency requires risk assessments for facilities that have \nsensitive receptors within 250m of their boundary. In order to improve current \nrisk assessment methodologies, improved predictions of bioaerosol dispersal are \nrequired. Dispersion modelling has been successfully used to determine \ndispersion of odours from waste management. In this paper, bioaerosol \nconcentration data measured at a composting facility is analysed in an ongoing \nseries of model experiments, using the ADMS air dispersion model. Initial \nmodelling results reveal that the concentrations of bioaerosols decrease rapidly \nwith distance from the site, although under certain circumstances, it is \npossible that higher concentrations may still be present at 200m from the site \nboundary. However, dispersion models are not yet able to take into account all \nthe properties of bioaerosols, in particular, their viability and their ability \nto aggregate and form clumps, which will affect the rate of dispersal. A series \nof experiments were designed to examine how the options within dispersion model \naffect the dispersion of bioaerosols and under which circumstances high \nconcentrations may disperse to sensitive receptors. The results will be compared \nwith bioaerosol measurements taken downwind of a composting facility, to \ndetermine the accuracy of the model predictions. This is the first stage in an \nattempt to design a best practice method for modelling bioaerosols.
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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) | 0.001 | 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 it