Record Display for the EPA National Library Catalog

RECORD NUMBER: 8 OF 11

OLS Field Name OLS Field Data
Main Title Evaluation of Selected Air Pollution Dispersion Models Applicable to Complex Terrain.
Author Lantz, Ronald B. ; Settari, Antonin ; Hoffnable., Gale F. ;
CORP Author Intercomp, Houston, Tex.;Environmental Protection Agency, Research Triangle Park, N.C. Office of Air Quality Planning and Standards.
Year Published 1974
Report Number EPA-68-02-1085; EPA/450/3-75-059;
Stock Number PB-246 640
Additional Subjects Air pollution ; Atmospheric diffusion ; Mathematical models ; Mathematical prediction ; Turbulent flow ; Viscosity ; Numerical analysis ; Concentration(Composition) ; Wind velocity ; Wind direction ; Texas ; Utah ; Huntington Canyon ; Navier-Stokes equations ; Terrain models ; El Paso(Texas)
Internet Access
Description Access URL
http://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=20015EF6.PDF
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
NTIS  PB-246 640 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. NTIS 06/23/1988
Collation 108p
Abstract
A comparison has been made of three models which attempt to predict the dispersion of pollutants in situations with complex terrain. The three models are (1) a Gaussian calculation with terrain assumptions known as the NOAA model, (2) an EPA model, C4M3D also known as the 'valley' model, which substitutes different terrain assumptions in the Gaussian calculations, and (3) the INTERCOMP combined wind flow and plume dispersion model which uses a numerical calculational method. Predictions made by each of these models are compared to measurements of ambient concentration data taken in Huntington Canyon, Utah and at El Paso, Texas. The results indicate that the INTERCOMP model has a predictive accuracy for terrain situations comparable to that normally expected for Gaussian predictions in flat terrain, i.e. a factor of two to three. For stable atmospheres, however, the Gaussian predictions of the NOAA model averaged a factor of fifteen higher than the measured results.