Characterizing Pollutant Transport in an Office Building With Limited Site-Specific Information: 1. Analysis and Uncertainty Reduction Techniques. M. D. Sohn, R. G. Sextro, A. J. Gadgil, and J. M. Daisey, Lawrence Berkeley National Laboratory
Response decisions must be made quickly in the event of an unexpected pollutant release in a building. However, the limited site- and event-specific information can be so inadequate that any effort to conduct a quantitative analysis would be ineffective or unacceptably slow. We develop a framework that couples indoor airflow and pollutant transport modeling with decision analysis to identify, and in some cases make, critical pre-event decisions. Recognizing that the lack of site-specific information limits our understanding, the framework is also supported with methods to (i) weigh the relative contributions of model input uncertainty on transport predictions and (ii) estimate the potential for reducing uncertainty by gathering additional site-specific information. As an illustrative application, we develop response decisions for a hypothetical pollutant release on the first floor of a commercial building. Representative, or prototypical, buildings are described, a priori, by the key features of the building stock that affect transport and exposure. Monte Carlo simulation modeling provides predictions of the pollutant concentrations in various zones of the building under a range of indoor and outdoor conditions. For the peak concentrations predicted on the first and fifth floors, information about the HVAC operation and the window usage (e.g., open or closed windows) would best reduce uncertainty in model predictions and can significantly affect stakeholder decisions.
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