A Probability Model for Evaluating Building Contamination from an Environmental Event

Abstract

ABSTRACT Asbestos dust and bioaerosol sampling data from suspected contaminated zones in buildings allowed development of an environmental data evaluation protocol based on the differences in frequency of detection of a target contaminant between zones of comparison. Under the assumption that the two test zones of comparison are similar, application of population proportion probability calculates the significance of observed differences in contaminant levels. This was used to determine whether levels of asbestos dust contamination detected after a fire were likely the result of smoke-borne contamination, or were caused by pre-existing/background conditions. Bioaerosol sampling from several sites was also used to develop the population proportion probability protocol. In this case, significant differences in indoor air contamination relative to the ambient conditions were identified that were consistent with the visual observations of contamination. Implicit in this type of probability analysis is a definition of “contamination” based on significant differences in contaminant levels relative to a control zone. Detection of a suspect contaminant can be assessed as to possible sources(s) as well as the contribution made by pre-existing (i.e., background) conditions, provided the test and control zones are subjected to the same sampling and analytical methods.