Gaussian plume computations

In Gaussian plume computations the change in wind velocity with height is a function both of the terrain and of the time of day. We model the air flow as turbulent flow, with turbulence represented by eddy motion. The effect of eddy motion is important in diluting concentrations of pollutants. If a parcel of air is displaced from one level to another, it can carry momentum and thermal energy with it. It also carries whatever has been placed in it from pollution sources. Eddies exist in different sizes in the atmosphere, and these turbulent eddies are most effective in dispersing the plume. 

The earliest and still widely used dispersion model to compute pollutant concentration profiles is the Gaussian plume model for single or multiple source pollution problems. Box-type model techniques, which can take into account nonlinear interactions among different species arising from chemical reactions, have been used in longer-range dispersion computations. 

Using the Gaussian plume model and the other relations presented, it is possible to compute ground level concentrations C, at any receptor point (Xq, in the region resulting from each of the isolated sources in the emission inventory. Since Equation (2) is linear for zero or linear decay terms, superposition of solutions applies. The concentration distribution is available by computing the values of C, at various receptors and summing over all sources. 

The AGDISP model is run until the released material becomes a spray cloud. Then the FSCBG model uses the AGDISP predictions to create a Gaussian plume model. This gives a complete predictive code, accurate from the time of release until long after the released material can be treated as a cloud. All important forces influencing the evolution of the released material are accounted for and the increase in computer time is nominal. 

The General Structure of Multiple-Source Plume Models Multiple-source plume (and particularly Gaussian plume) models (Calder 1977) are commonly used for predicting concentrations of inert pollutants over urban areas. Although there are many special-puipose computational algorithms currently in use, the basic element that is common to most is the single-point-source release. The spatial concentration distribution from such a source is the underlying component and the multiple-source model is then developed by simple superposition of the individual plumes from each of the sources. 

Gaussian puff models These models are designed to overcome the time independence of the Gaussian plume models. A puff of pollutant is modeled from a point source. The wind field and source emission rate are periodically updated Time-dependent plume measurement Not useful for reactive pollutants More difficult to apply than plume model, since time-dependent data are required Computer assistance required 114... 

Our computations are based on the release estimates provided by the authorities (Lithuanian State Committee for Environmental Protection, 1989). We have applied a long-range dispersion model that uses a Gaussian plume model up to a specified transition distance, and... 

The model applies a Gaussian plume model up to a specified transition distance, which is dependent on atmospheric stability 200 m for unstable, 500 m for neutral, and 1000 m for stable stratification, respectively. Outside this nearby zone, the gradient-transfer approach is used for computing the diffusion in the vertical direction. 

Finding 9. Gaussian puff/plume dispersion modeling techniques embedded in the D2PC computer model used to pre-... 

The Gaussian dispersion model has several strengths. The methodology is well defined and well validated. It is suitable for manual calculation, is readily computerized on a personal computer, or is available as standard software packages. Its main weaknesses are that it does not accurately simulate dense gas discharges, validation is limited from 0.1 to 10 km, and puff models are less well estabUshed than plume models. The predictions relate to 10 min averages (equivalent to 10 min sampling times). While this may be adequate for most emissions of chronic toxicity, it can underestimate distances to the lower flammable limit where instantaneous concentrations are of interest. More discussion will follow. 

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