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However, in contrast to temperature, this energy cannot be regarded as an independent variable, but rather represents a function of mean particle concentration and of physical parameters.
To calculate the number of particles from one breath, 0.5 liters of air was multiplied to the mean particle concentration, which assumed complete release of tidal volume from a typical person [53].
To calculate the number of particles from one cough, 3.56 liters of air was multiplied by the mean particle concentration; the 3.56 liter value was based on the forced expiratory volume in one second reported from normal subjects [20].
The mean particle concentration in the chamber was 190 ± 37 μg/m.
We multiplied the mean particle concentration per puff by 50, to attain the particle number per 50-ml puff volume.
The mean particle concentration in the diesel engine chambers was 0.7, 2.2 and 6.6 mg/m3 for the low-, medium- and high- concentration chambers, respectively.
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The correct prediction of mean particle concentrations within ventilated airspaces is an important practical problem.
When used in conjunction with the statistical properties of the air flow predicted by the k−ε model, Thomson's model is shown to predict mean particle concentrations in close accord with experimental findings.
Prompted by the success of this model in predicting particle dispersion in one-dimensional and two-dimensional inhomogeneous turbulent flows, an assessment is made of the ability of the model to predict correctly mean particle concentrations in a three-dimensional inhomogeneous turbulent flow within a mechanically ventilated airspace.
For example, personal dust exposure levels measured during various operations such as land planning and disking yielded geometric mean particle concentrations of 57.3 and 98.6 mg/m, respectively.
After analysis of the concentration and mean particle size of fines collected from these wells, it was concluded that the more developed the tectonically deformed coal, the higher the fines concentrations and the smaller the fines mean particle sizes, which was consistent with the experimental results.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com