When modeling pollutant transport and dispersion using gridded meteorological flow fields on an hourly basis, significant parts of the turbulence spectra are not resolved in space and time. Parameterizations of puff or plume dispersion commonly account for this by estimating one-hour averaged dispersion. For risk assessments and odor impact analyses, the highest possibly occurring concentration during a time considerably shorter than one hour is more decisive. For this, the probability density function of concentration for a given location and a specific averaging time is required.
To estimate concentration probability density functions, dispersion has to be split up into its two components: the instantaneous puff/plume growth (driven by turbulent eddies being smaller than the size of the puff) and the dispersion caused by meandering (large eddies displace the puff without enlarging it) of the puff during the averaging time. This contribution presents predicted higher moments of near-source concentrations for different averaging times, using the Lagrangian Puff-Particle Model (PPM). The performance of the PPM in predicting one-hour averaged concentration has been extensively validated using the so-called Model Validation Kit, and intercompared with other dispersion models (de Haan, P., and Rotach, M.W., 1998: A novel approach to atmospheric dispersion modelling: The Puff-Particle Model. Quart. J. Roy. Meteorol. Soc., 124, 2771-2792) The use of the PPM to estimate concen-tration fluctuations was first discussed in (de Haan P. and Scire J.S. 1999: Prediction of higher moments of near-source concentration by simulating the meandering of pollutant puffs. Preprints 13th Conference on Boundary Layers and Turbulence, pp. 653-656).
The Z6849Z ASTM Draft Standard Practice for Statistical Evaluation of Atmospheric Dispersion Models (Irwin J.S, and Rosu M.-R., 1998: Comments on a Draft Practice for Statistical Evaluation of Atmospheric Dispersion Models. In: Proceedings 10th joint Conf. Applications of Air Pollution Meteorology, pp. 6-10) currently is in a test phase. Although the underlying philosophy is not limited to only plume dispersion models, up to now it has been mostly used for standard Gaussian plume models. The Draft Practice describes how comparisons might be made of simulated centerline concentration values with observed concentration data collected on arcs of receptors. The philosophy of the Draft Practice can be extended to assess performance for other features like the prediction of the variance of observed concentration values averaged over short times.
In this presentation, the concentration fluctuations predicted by the PPM are compared with observations of the standard deviation of concentration fluctuations. This evaluation is done following the Draft Practice scheme. It is shown that the PPM can effectively be used to predict concentration fluctuations, and that the Draft Practice is a suitable method to assess the ability of dispersion models for the estimation of concentration fluctuations.