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RECORD NUMBER: 27 OF 64

OLS Field Name OLS Field Data
Main Title Field Validation of Exposure Assessment Models. Volume 2. Analysis.
Author Doran, J. C. ; Horst, T. W. ;
CORP Author Battelle Pacific Northwest Labs., Richland, WA.;Environmental Sciences Research Lab., Research Triangle Park, NC.
Year Published 1984
Report Number EPA/600/3-84/092B;
Stock Number PB85-107217
Additional Subjects Air pollution ; Mathematical models ; Field tests ; Exposure ; Assessments ; Performance evaluation ; Concentration(Composition) ; Design criteria ; Experimental design ; Gaussian plume models ; Tracer studies
Holdings
Library Call Number Additional Info Location Last
Modified
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Status
NTIS  PB85-107217 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. 06/23/1988
Collation 54p
Abstract
This is the second of two volumes describing a series of dual tracer experiments designed to evaluate the PAL-DS model, a Gaussian diffusion model modified to take into account settling and deposition, as well as three other deposition models. In this volume, an analysis of the data summarized in Volume 1 is given. The four models are described, and an evaluation of the performance of each is given. The evaluation is based on an analysis of C sub d/C sub o, the ratio of the crosswind-integrated concentrations of a depositing and nondepositing tracer, respectively, at a height of 1.5 m. The PAL-DS model is found to overestimate this ratio; a corrected source depletion model appears to give significantly better results. A novel method of determining the effective deposition velocity of the depositing tracer, based on a surface depletion approach, is described. A discussion of model sensitivities, experimental design, and the effects of measurement errors on the model evaluation is also given. Experimental uncertainties may well affect the performances of the models, but it is doubtful that their relative performances would be significantly changed. Errors in describing the diffusion meteorology are likely to be more important in predicting depleted concentrations than errors introduced by the choice of a particular deposition model, which are apt to be more systematic.