Dispersion models Britter-McQuaid model

Empirical modek Empirical models rely on the correlation of atmospheric dispersion data for characteristic release types. Two examples of empirically based models are the Pasquill-Ginord model (for passive contaminants) and the Britter-McQuaid model (for denser-than-air contaminants) both of which are described below. Empirical models can be useful for the validation of other mathematical models but are limited to the characteristic release scenarios considered in the correlation. Selected empirical models are discussed in greater detail below because they can provide a reasonable first approximation of the hazard extent for many release scenarios and can be used as screening tools to indicate which release scenarios are most important to consider. 

Britter-McQuaid Model A model for dense gas dispersion using dimensional analysis coupled with actual dense gas release data. 

A complete analysis of dense gas dispersion is much beyond the scope of this treatise. More detailed references are available (Britter and McQuaid, Workbook on the Dispersion of Dense Gases, Health and Safety Executive Report No. 17/1988, England, 1988 Lees, 1986, pp. 455 61 Hanna and Drivas, 1987 Workbook of Test Cases for Vapor Cloud Source Dispersion Models, AlChE, 1989 Guidelines for Chemical Process Quantitative Risk Analysis, 1989, pp. 96-103). 

Use the Britter-McQuaid dense gas dispersion model to determine the distance to the 1% concentration for a release of chlorine gas. Assume that the release occurs over a duration of 500 s with a volumetric release rate of 1 m3/s. The wind speed at 10 m height is 10 m/s. The boiling point for the chlorine is —34°C, and the density of the liquid at the boiling point is 1470 kg/m3. Assume ambient conditions of 298 K and 1 atm. 

The Britter and McQuaid model was developed by performing a dimensional analysis and correlating existing data on dense cloud dispersion. The model is best suited for instantaneous or continuous ground-level area or volume source releases of dense gases. Atmospheric stability was found to have little effect on the results and is not a part of the model. Most of the data came from dispersion tests in remote, rural areas, on mostly flat terrain. Thus, the results would not be applicable to urban areas or highly mountainous areas. 

Many computer codes, both public and private, are available to model dense cloud dispersion. A detailed review of these codes, and how they perform relative to actual field test data, is available (Hanna, Chang, and Strimaitis, Atmospheric Environment, vol. 27A, no. 15, 1993, pp. 2265-2285). An interesting result of this review is that a simple nomograph method developed by Britter and McQuaid (1988) matches the available data as well as any of the computer codes. This method will be presented here. 

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