Buoyant Plume Dispersal in the Convective Boundary Layer: Analysis of Experimental Data and Lagrangian ModelingEPA Grant Number: R826160
Title: Buoyant Plume Dispersal in the Convective Boundary Layer: Analysis of Experimental Data and Lagrangian Modeling
Investigators: Weil, Jeffrey C.
Institution: University of Colorado at Boulder
EPA Project Officer: Shapiro, Paul
Project Period: February 3, 1998 through February 2, 2001 (Extended to February 2, 2003)
Project Amount: $244,000
RFA: Exploratory Research - Physics (1997) RFA Text | Recipients Lists
Research Category: Water , Land and Waste Management , Air , Engineering and Environmental Chemistry
The aim of this research program is to improve our knowledge and predictive capability of buoyant plume dispersion in the convective boundary layer (CBL) with emphasis on the mean (C) and root-mean-square (?c) concentration fields. The CBL turbulence leads to large random fluctuations in concentration over short time periods. Thus, concentration estimates should be made on a statistical basis using a probability distribution, which requires predictions of C and ?c. There are three key objectives of our research: 1) to increase our understanding of highly buoyant plumes that loft near the CBL top, 2) to further develop a hybrid Lagrangian dispersion model for buoyant plumes, and 3) to improve an analytical probability density function (p.d.f.) dispersion model and extend its range of applicability.
The first objective will be pursued by a) analysis of recent data on buoyant plume dispersion in a laboratory convection tank, and b) developing a gravity current model to describe the enhanced lateral spread of the lofting plume. The hybrid Lagrangian model couples a stochastic model for the plume meander due to the large CBL eddies with an entrainment model for the plume rise and growth. This model will be extended by improving the treatment of dispersion near the CBL top and including the new lofting model. The p.d.f. model also will be extended by coupling it with the lofting model. The extended models will be compared with laboratory and field data and modified as necessary.
It is expected that this effort will increase the realism and range of conditions over which these dispersion models provide credible estimates of C and ?c. The investigation will provide basic understanding necessary for dealing with and estimating the peak concentration of toxic and hazardous substances; such estimates are needed in risk assessments.