Mapping Urban Aerosolized Fungi: Predicting Spatial and Temporal Indoor Concentrations

摘要

The prediction of bioaerosols, specifically airborne fungi, can be achieved using various mapping techniques, potentially enabling the determination of ambient indoor concentrations within environments where people spend most of their time. The concentration and composition of indoor air pollutants are determined by a multitude of variables, with building ventilation type being the most predominant factor in most scenarios. A predictive statistical model-based methodology for mapping airborne fungi was developed utilizing satellite-based technology. Mapping was carried out for total aerosolized fungal spores and the diversity of aerosolized fungi in Sydney, Australia, over four seasons. Corresponding data for a range of environmental parameters known to influence airborne fungi were also used, notably green space density, land cover, altitude, meteorological variables, and other locally determined factors. Statistical models previously developed from the combined meteorological and environmental variable data were used to establish spatiotemporal models for airborne fungi across the study area for each season. Results showed that the models produced reasonable predictions of monitored aeromycota concentrations; although, the accuracy of these predictions for individual survey periods was variable. Using known indoor/outdoor (I/O) ratios of airborne fungi for the area, the prevalence and concentrations of indoor aeromycota were modeled for buildings with both natural and mechanical ventilation. As accurate manual assessment of the aeromycota is labor, time, and cost intensive, the current findings should assist in the prediction of fungal aerosols in both urban and indoor environments. Additionally, understanding the indoor microbiome has great importance for the health and well-being of the occupants concerned.