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Updated: Aug 20, 2026

Composition and Distribution Analysis of Bioaerosols Under Different Environmental Conditions
Published on: January 7, 2019
Evaluation and determinants of airborne bacterial concentrations in school classrooms
Karen H Bartlett1, Susan M Kennedy, Michael Brauer
1School of Occupational and Environmental Hygiene, University of British Columbia, Vancouver, British Columbia, Canada. kbartlet@interchange.ubc.ca
Abstract:
A survey of 39 elementary schools was undertaken to determine indoor air concentrations of bioaerosols within a coastal, temperate climatic zone in British Columbia, Canada. This article reports the results for airborne bacteria. Determinants of exposure were grouped into environmental (outdoor temperature, relative humidity, season, weather), ventilation and comfort parameter (indoor relative humidity, temperature, indoor CO2 concentration, indoor fungal concentration), and occupancy (number of occupants, activity levels, occupancy patterns) variables. Regression modeling was used to evaluate the association between these factors and measured concentrations of indoor mesophilic bacteria. Naturally ventilated rooms (47% of the total rooms surveyed) had higher bacterial counts than mechanically ventilated rooms (geometric mean 325 vs. 166 CFU/m3, respectively, p < 0.001). In univariate analyses, bacterial counts were negatively correlated with supply and exhaust flow rates, air exchange rates, and the percentage of the day that occupants spent quietly sitting at their desks. Analysis of bacterial groups indicated various sources of the bacterial aerosol, with micrococci and staphylococci closely associated with occupancy variables, Bacillus with site and occupancy, and coryneform bacteria with site variables only. Approximately 60% of the variance in the outcome measurement of total bacteria was accountedfor by indoor CO2, lower air exchange rate, the age of the building, signs of current or old moisture stains, room volume, indoor relative humidity, and occupant activity level in a multiple linear regression model, with ventilation factors accounting for 40% of the variance.
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