Handbook on atmospheric diffusion

Abstract

Vertical distribution of concentration, Vertical plume 47,4a buoyancy conservation equation, 12 entrainment velocity, 12 momentum conservation equation, 13 rise in stable environment, 14 trajectory near source, 13 volume flux, 11 Virtual source, 14, 17 Visible plume dimensions for cooling Volume flux of plume, 11, 12 von Ka'rmin's constant, 6 tower, 76-77 Wake cavity, 20-24 Washout ratio, 71, 72 Wavelength of maximum energy, 8 Weighting scheme for winds, 88, 90 Wet deposition, 71, 72 Wet removal of sulfur, 88 Widows Creek Steam Plant, 81, 82 Wind direction shear, 5, 6 Wind profile in surface layer, 6, 7 Wind-speed power law, 32 Wind-tunnel experiments, 19-22 DISC LA1 M E R This book was prepared as an account of work sponsored b y an agency of the United States Government.

Seasonal variation of the temperature inversions over Athens, Greece

“…Inversions are closely related to the stability conditions of the lower atmosphere, where they play a significant role in the dispersion of pollutants. The reduced dispersion of pollutants, caused by the great stability of inversion layers, often leads to the formation of atmospheric pollution episodes (Hanna et al, 1982).…”

A review of back-calculation techniques and their potential to inform mitigation strategies with application to non-transmissible acute infectious diseases

“…For example, population data tend to be snap-shots in time, and therefore, larger population aggregations might be less prone to the fluctuations which will inevitably occur on a daily basis. In addition, the puff models given by equations (4.1)/(4.2) and equations (4.3)/ (4.4) do not capture small-scale changes (of the order of metres) in meteorology and are more generally applicable over larger distances (of the order of hundreds of metres upwards) [73]. Moreover, the computational run-time of the model tends to be faster when using larger spatial units, because there are fewer of them to consider, which could be critically important in a response situation.…”

“…the number of spores released) and location vector of the release, respectively, x is the distance downwind in the direction of the wind, y is the crosswind distance and z is the vertical distance. d ¼ fb, u, s x , s y , s z , zg are the input parameters, where b is the breathing rate, u is the wind speed and s x , s y , s z are the downwind, crosswind and vertical standard deviations of the concentration distribution (also known as the dispersion parameters [72]), respectively, which predominantly depend on whether the release occurs during the day or at night and also on the wind speed and distance from the release location [71,73]. z is the decay rate of the pathogen which similarly varies with the time of day, c 1 ¼ s x z/u and c 2 ¼ (x 2 X )/s x .…”

“…Equations (4.3) and (4.4) are equivalent to using this modified Gaussian plume model, because by using the dispersion parameters given by the Briggs formulations [73], it can be shown that F(c 2 ) % 1 for all distances downwind of the release location; indeed, it was this version that was used in the original Sverdlovsk analysis [69,72]. The prospective likelihood function for an instantaneous aerosolized release, regardless of the form of the equation describing the inhaled dose d, is given by…”

The GDS model—a rapid computational technique for the calculation of aircraft spray drift buffer distances

“…Gaussian type equations which simulate the atmospheric diffusion (or dispersion) of particulate materials are described in texts including Turner (1970), Csanady (1973), Hanna et al (1982), Pasquill and Smith (1983) and Panofsky and Dutton (1984). Elevated line source versions of these equations to simulate aerial release were developed and validated by Cramer et al (1972) and Bache and Sayer (1975).…”