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Five basic characteristics of Taylor dispersion and vertical mean concentration distribution with skewness and kurtosis modifications are also analyzed.
The concentration moments are intensively derived for an accurate presentation of the mean concentration distribution, up to the effect of kurtosis.
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The numerical prediction of the statistical properties of contaminant dispersion, e.g. the mean concentration distributions, lateral and vertical spreads of the contaminant an so forth, is in good agreement with wind tunnel experiment measurements.
The numerical results, which include the statistical properties of pollutant dispersion, e.g. mean concentration distributions, time-evolution and three-dimensional spreads of the pollutant, are then compared to wind-tunnel (WT) measurements.
Prior studies illustrating the wind effect on environmental dispersion in wetland flows simply focused on the mean longitudinal concentration distribution.
The effects of Peclet number, Reynolds number, nanoparticle size and nanofluid mean concentration on the distribution of nanoparticles have been evaluated.
For these types of disease incidence models, only the mean of the concentration distribution is needed to estimate population impact.
The mean concentration of the seronegative distribution (the distribution with the smallest mean) +2 SDs was considered the seropositivity cutoff (15 ).
The central objective, as in Taylor's approach, is to predict the turbulent diffusion (mean square displacement and/or concentration distribution) given certain statistical information about the turbulent velocity field.
Good agreement is obtained for the distribution of mean concentration and the concentration correlation coefficient.
The uniform shear leads to a special symmetrical distribution of mean concentration free of skewness.
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