Variations in Measured Values of Lateral Diffusion Parameters

Doran, J. C.; Horst, Thomas; Nickola, P.W.

doi:10.1175/1520-0450(1978)017<0825:vimvol>2.0.co;2

Cited by 19 publications

(6 citation statements)

References 11 publications

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“…Once the universal functions f, and f, have been determined, then uy and u, are completely determined by observations of 0 6 and ue. Presumably T, and T, are similarity functions of z/zg, zi/L, and Pasquill (1976), Draxler (1976), Doran, Horst, and Nickola (1978), and Irwin (1979a) are among those actively investigating the best form for the universal functions f, and f,. Although Taylor's (1921) statistical diffusion equation (see Chap.…”

Section: The Ag and O E Methodsmentioning

confidence: 99%

“…5.14, diffusion can be calculated by using basic wind-speed observations, which makes this equation a very practical but so far underused model. Doran, Horst, and Nickola (1978) assume a standard form for the spectrum F(n) for stable and unstable conditions and integrate Eqs. 4.14 and 5.13, which thus accounts for the effects of averaging timet and sampling time T, on 6.…”

Section: -3 Influence Of Eddy Size Onmentioning

confidence: 99%

See 1 more Smart Citation

Handbook on atmospheric diffusion

Hanna¹,

Briggs²,

Hosker³

et al. 1982

594

352

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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.

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Section: The Ag and O E Methodsmentioning

confidence: 99%

Section: -3 Influence Of Eddy Size Onmentioning

confidence: 99%

Handbook on atmospheric diffusion

Hanna¹,

Briggs²,

Hosker³

et al. 1982

594

352

View full text Add to dashboard Cite

show abstract

“…Pasquill 1976;Draxler 1976;Doran et al 1978;Irwin 1979). In our study we compare our data with the models proposed by Phillips and Panofsky (1982) and Degrazia et al (2005).…”

Section: Introductionmentioning

confidence: 84%

Scaling of the Vertical Spreading of a Plume of a Passive Tracer in a Rough-Wall Neutral Boundary Layer

Salizzoni

Liefferinge²,

Méjean³

et al. 2010

Boundary-Layer Meteorol

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The influence of surface roughness on the dispersion of a passive scalar in a rough wall turbulent boundary layer has been studied using wind-tunnel experiments. The surface roughness was varied using different sizes of roughness elements, and different spacings between the elements. Vertical profiles of average concentration were measured at different distances downwind of the source, and the vertical spread of the plume was computed by fitting a double Gaussian profile to the data. An estimate of the integral length scale is derived from the turbulence characteristics of the boundary layer and is then used to scale the measured values of plume spread. This scaling reduces the variability in the data, confirming the validity of the model for the Lagrangian integral time scale, but does not remove it entirely. The scaled plume spreading shows significant differences from predictions of theoretical models both in the near and in the far field. In the region immediately downwind of the source this is due to the influence of the wake of the injector for which we have developed a simple model. In the far field we explain that the differences are mainly due to the absence of large-scale motions. Finally, further downwind of the source the scaled values of plume spread fall into two distinct groups. It is suggested that the difference between the two groups may be related to the lack of dynamical similarity between the boundary-layer flows for varying surface roughness or to biased estimates of the plume spread.

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“…Lagrangian similarity theory, summarized by Horst et al (1979) and statistical theory discussed by Pasquill (1974), Draxler (1976), Doran et al (1978a and1978b), Irwin (1979), Pasquill (1979) and Horst et al (1979) among others estimate diffusion coefficients directly from turbulence measurements. Using diffusion data from several major experiments, Horst et al (1979) demonstrated that estimation of diffusion coefficients directly from turbulence data significantly reduces the uncertainty in the estimates when compared with the uncertainties associated with the use of stability classification schemes.…”

Section: Diffusion Coefficient Estimatesmentioning

confidence: 99%