| Exposure to contaminated air has become an increased problem due to a variety of factors. Stachybotrys chartarum and other potentially harmful microorganisms implicated with indoor air problems have garnered national attention in recent years.{09}Accurate assessment of indoor contaminated air, however, has proven to be prohibitively labor, time, cost, and training intensive. This dissertation presents the development of a model that accurately predicts the levels of indoor air biological contaminants using a number of independent variables that can be quickly calculated without expensive, time-consuming scientific techniques.; Thirty-nine (39) residences were sampled in the Greater Cincinnati area using Andersen 2-stage air samplers loaded with Malt Extract Agar, Trypicase Soy Agar, Czapek's Cellulose Agar, and Corn Meal Agar. After air sampling, the Petri dishes were incubated, the number of colonies from each plate were enumerated and the total number of viable cells/m3 were calculated. Initial walk-through of each site included an investigation of any possible presence of fungi or evidence of water damage. Relative humidity and temperature inside the site and out were recorded. Building site, size, and type were also noted and residents of the house were given an indoor health quality questionnaire to fill out. Independent variables were then compared together to the dependent variable using multiple linear regression. This was done using Analyze-it® for Microsoft Excel®. The model compared independent variables like temperature and humidity to fungal and bacterial bioaerosol counts obtained from the Andersen samplers. The final air model predicts indoor cell counts with 96% accuracy. The goal for this model was 90% accuracy. |
