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Assessment and modeling of indoor fungal and bacterial bioaerosol concentrations
Authors:Christopher F. Green  Pasquale V. Scarpino  Shawn G. Gibbs
Affiliation:1. Department of Civil and Environmental, Engineering at the University of Cincinnati, P.O. Box 210071, Cincinnati, Ohio, 45221-0071, USA
2. School of Public Health, El Paso Regional Campus, The University of Texas Health Science Center at Houston, 1100 N. Stanton, El Paso, Texas, 79902, USA
Abstract:In recent years, potentially harmfulmicroorganisms such as Stachybotryschartarum have garnered national attentionwhen implicated with indoor air problems. However, accurate assessment of biologicallycontaminated indoor air has proven to beprohibitively labor, time, cost, and trainingintensive. The model developed in this studyaccurately predicts the levels of biologicalindoor air contaminants for the GreaterCincinnati area using a number of independentvariables that can be quickly calculatedwithout expensive, time-consuming methods. Thirty-nine single-family residences in theGreater Cincinnati area were sampled usingAndersen two-stage viable microbial particlesizing sampler instruments loaded with MaltExtract Agar, Trypicase Soy Agar, Czapek'sCellulose Agar, and Corn Meal Agar. After airsampling, the Petri dishes were incubated, thenumber of colonies from each plate wereenumerated, and the total number of viablecolony forming units per cubic meter of airwere calculated. Independent variables (indoorrelative humidity, indoor temperature, outdoormold, season, water damage, visible mold,damaged materials, home age, remediationfactors, health questionnaire, number ofoccupants, and indoor pets) were then compared tothe dependent variable (fungal and bacterialbioaerosol counts) by multiple linearregression using Analyze-it® for Microsoft Excel®. The final air model predicted thetotal number of viable colony forming units percubic meter with 97% accuracy; the goal forthis model was 90% accuracy.
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