Evaluation of the QUIC Urban Dispersion Model using the Salt Lake City URBAN 2000 Tracer Experiment Data – IOP 10 Akshay Gowardhan 1 , Michael Brown 2 , Michael Williams 2 and Eric Pardyjak 1 1 University of Utah, Salt Lake City, Utah 2 Los Alamos National Laboratory, Los Alamos, New Mexico 1. INTRODUCTION Computational fluid dynamics (CFD) models hold great promise for simulating transport and dispersion in cities. Comparisons to field and laboratory measurements show that these models work fairly well in many cases (e.g., DeCroix and Brown 2002, Camelli et al. 2004). At the present time, however, CFD models are computationally very intensive and because turn around time is very important for some applications, faster alternatives are being developed which will generate flow fields in less time. Diagnostic-empirical models are one such option; they attempt to account for the dominant building-induced circulations through empirical algorithms (e.g., Röckle 1990, Kaplan and Dinar 1996). Our team has developed the Quick Urban and Industrial Complex (QUIC) dispersion modeling system with a wind solver based on the Röckle approach. These types of models have been fairly well evaluated for simple building arrangements (Williams et al. 2004). However, for more complex building arrangements, such as those that exist in real cities, less model testing has been reported. In this paper, we compare QUIC model-produced concentration fields with tracer measurements obtained from one of the intensive operating periods (IOP 10) in the Salt Lake City URBAN 2000 field experiment (Allwine et al. 2002). We will focus on the near-source concentration field in the immediate vicinity of the buildings and within several blocks of the release area and highlight similarities and differences between the model computations and experimental measurements. 2. MODEL DESCRIPTION The QUIC fast response dispersion modeling system produces high-resolution wind and concentration fields in cities. It consists of an urban wind model QUIC-URB, a Lagrangian dispersion model QUIC-PLUME, and a graphical user interface QUIC-GUI. Such models, which can quickly produce the required velocity and concentration field, have many applications. Some of the applications are as follows: 1. Vulnerability assessments (where many simulations must be performed). 2. Training, table top exercises (where feedback or interaction is desired). 3. Emergency response. 4. Sensor sitting & source inversion tools. a) QUIC-URB QUIC–URB is based on the dissertation of Röckle (1990) in which a mass consistent diagnostic wind model for computing the 3D flow field around building obstacles was developed. In this model, an initial wind field is prescribed based on an incident flow and superimposed on this are various time-averaged flow effects associated with buildings. QUIC-URB utilizes empirical algorithms for determining initial wind fields in the rooftop and upstream recirculation zones (Bagal et al. 2004), the downwind cavity and wake for a single building (Singh et al. 2006) and in the street canyon between buildings. A mass consistent wind field is produced similar to the traditional diagnostic wind model (e.g., Sherman, 1978), but special treatment of the boundary conditions are needed at the building walls (Pardyjak and Brown 2003). b) QUIC-PLUME The QUIC-PLUME dispersion model is a Lagrangian random-walk model which tracks the movement of particles as they disperse through the air. QUIC-PLUME uses the mean wind field computed by QUIC-URB and produces the turbulent dispersion of the airborne contaminant using random-walk equations with additional drift terms appropriate for the inhomogeneous nature of turbulence around buildings (Williams et al. 2004). The normal and shear stresses and turbulent dissipation are determined based on gradient transport and similarity theory. QUIC- PLUME also includes a non-local mixing formulation that better describes the turbulent mixing that occurs in building wakes or cavities (Williams et al. 2004b). J6.3 * Corresponding author address: Akshay Gowardhan, University of Utah, Salt Lake City UT-87545, e-mail: aagowardhan@yahoo.com