Simulation of diffusion experiments under light wind, stable conditions by a variable K-theory model

An analytical solution of three dimensional advection–diffusion equation, including longitudinal diffusion, for dispersion of air pollutants from a point source at a height close to the surface is used to simulate the field tracer data collected at Idaho Falls, ID, USA, during low wind, stable conditions. The apparent eddy diffusivities are parameterized in terms of downwind distance for near-source dispersion. The model predictions with two different parameterizations (u* and σΘ) of turbulence parameters and two different approaches (hourly and segmented plume or short-term averaging) are compared with the observations and the predictions from constant diffusivities solutions (including the standard Gaussian plume solution). The best results are obtained from segmented plume approach (dividing the test period into smaller intervals) with σΘ-parameterization of turbulence parameters. This method uses actual measurements of turbulent wind fluctuations (in terms of σΘ) and the slow but large variability in the wind direction (leading to multiple peaks in the concentration distribution) is accounted for by the segmented plume approach. Simulations based on hourly averaged data are satisfactory especially in terms of peak values. The results from u*-parameterization of turbulence parameters are not as good as those from σΘ-parameterization because of usage of indirect and rough estimates of u* and some empirical relations which may be questionable in low wind conditions.