The potential effects of a terrorist attack involving the atmospheric release of chemical, biological, radiological, nuclear, or other hazardous materials continue to be of concern to the United States. The Defense Threat Reduction Agency has developed a Hazard Prediction Assessment Capability (HPAC) that includes initial features to address hazardous releases within an urban environment. Improved characterization and understanding of urban transport and dispersion are required to allow for more robust modeling. In 2001, a scaled urban setting was created in the desert of Utah using shipping containers, and tracer gases were released. This atmospheric tracer and meteorological study is known as the Mock Urban Setting Test (MUST). This paper describes the creation of sets of HPAC predictions and comparisons with the MUST field experiment. Strong consistency between the conclusions of this study and a previously reported HPAC evaluation that relied on urban tracer observations within the downtown area of Salt Lake City was found. For example, in both cases, improved predictions were associated with the inclusion of a simple empirically based urban dispersion model within HPAC, whereas improvements associated with the inclusion of a more computationally intensive wind field module were not found. The use of meteorological observations closest to the array and well above the obstacle array-the sonic anemometer measurements 16 m above ground level-resulted in predictions with the best fit to the observed tracer concentrations. The authors speculate that including meteorological observations or vertical wind profiles above or upwind of an urban region might be a sufficient input to create reasonable HPAC hazard-area predictions.
Chemical and biological (CB) defense systems require significant testing and evaluation before they are deployed for real-time use. Because it is not feasible to evaluate these systems with open-air testing alone, researchers rely on numerical models to supplement the defense-system analysis process. These numerical models traditionally describe the statistical properties of CB-agent atmospheric transport and dispersion (AT&D). While the statistical representation of AT&D is appropriate to use in some CB defense analyses, it is not appropriate to use this class of dispersion model for all such analyses. Many of these defense-system analyses require AT&D models that are capable of simulating dispersion properties with very short timeaveraging periods that more closely emulate a ''single realization'' of a contaminant or CB agent dispersing in a turbulent atmosphere. The latter class of AT&D models is superior to the former for performing CB-system analyses when one or more of the following factors are important in the analysis: high-frequency sampling of the contaminant, spatial and temporal correlations within the contaminant concentration field, and nonlinear operations performed on the contaminant concentration. This paper describes and contrasts these AT&D modeling tools and provides specific examples in which utilizing ensembles of single realizations of CB-agent AT&D is advantageous over using the statistical, ''ensemble-average'' representation of the agent AT&D. These examples demonstrate the importance of using an AT&D modeling tool that is appropriate for the analysis.
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