Accurate exposure assessments are needed to evaluate health hazards caused by airborne microorganisms and require air samplers that efficiently capture representative samples. This highlights the need for samplers with well-defined performance characteristics. While generic aerosol performance measurements are fundamental to evaluate/compare samplers, the added complexity caused by the diversity of microorganisms, especially in combination with cultivation-based analysis methods, may render such measurements inadequate to assess suitability for bioaerosols. Specific performance measurements that take into account the end-toend sampling process, targeted bioaerosol and analysis method could help guide selection of air samplers.Nine different samplers (impactors/impingers/cyclones/ electrostatic precipitators/filtration samplers) were subjected to comparative performance testing in this work. Their end-to-end cultivation-based biological sampling efficiencies (BSEs) and PCR-/microscopy-based physical sampling efficiencies (PSEs) relative to a reference sampler (BioSampler) were determined for gram-negative and gram-positive vegetative bacteria, bacterial spores, and viruses.Significant differences were revealed among the samplers and shown to depend on the bioaerosol's stress-sensitivity and particle size. Samplers employing dry collection had lower BSEs for stresssensitive bioaerosols than wet collection methods, while nonfilterbased samplers showed reduced PSEs for 1 μm compared to 4 μm bioaerosols. Several samplers were shown to underestimate bioaerosol concentration levels relative to the BioSampler due to having lower sampling efficiencies, although they generally obtained samples that were more concentrated due to having higher concentration factors.Our work may help increase user awareness about important performance criteria for bioaerosol sampling, which could contribute to methodological harmonization/standardization and result in more reliable exposure assessments for airborne pathogens and other bioaerosols of interest.
Biological treatment plants are frequently used to degrade organic substances in wastewater from wood refinement processes. Aeration ponds in such plants provide an optimal growth environment for many microorganisms, including Legionella species. To investigate whether legionellae could be dispersed as aerosols from the ponds and transported by the wind, the wetted-wall cyclone SASS 2000(PLUS) and the impactors MAS-100 and STA-204 were used to collect air samples directly above, upwind, and downwind of aeration ponds during a 4-month period. Computational fluid dynamics was used a priori to estimate the aerosol paths and to determine suitable air-sampling locations. Several Legionella species, including Legionella pneumophila, were identified in air samples at the biological treatment plant using microbiological and molecular methods. L. pneumophila was identified up to distances of 200 m downwind from the ponds, but, in general, not upwind nor outside the predicted aerosol paths. The highest concentration level of viable legionellae was identified directly above the aeration ponds (3300 CFU/m3). This level decreased as the distance from the aeration ponds increased. Molecular typing indicated that a single clone of L. pneumophila was dispersed from the ponds during the period of the study. Thus, our study demonstrated that aerosols generated at aeration ponds of biological treatment facilities may contain L. pneumophila, which then can be transported by the wind to the surroundings. The methods used in this study may be generically applied to trace biological aerosols that may pose a challenge to environmental occupational health.
BackgroundMass transit environments, such as subways, are uniquely important for transmission of microbes among humans and built environments, and for their ability to spread pathogens and impact large numbers of people. In order to gain a deeper understanding of microbiome dynamics in subways, we must identify variables that affect microbial composition and those microorganisms that are unique to specific habitats.MethodsWe performed high-throughput 16S rRNA gene sequencing of air and surface samples from 16 subway stations in Oslo, Norway, across all four seasons. Distinguishing features across seasons and between air and surface were identified using random forest classification analyses, followed by in-depth diversity analyses.ResultsThere were significant differences between the air and surface bacterial communities, and across seasons. Highly abundant groups were generally ubiquitous; however, a large number of taxa with low prevalence and abundance were exclusively present in only one sample matrix or one season. Among the highly abundant families and genera, we found that some were uniquely so in air samples. In surface samples, all highly abundant groups were also well represented in air samples. This is congruent with a pattern observed for the entire dataset, namely that air samples had significantly higher within-sample diversity. We also observed a seasonal pattern: diversity was higher during spring and summer. Temperature had a strong effect on diversity in air but not on surface diversity. Among-sample diversity was also significantly associated with air/surface, season, and temperature.ConclusionsThe results presented here provide the first direct comparison of air and surface bacterial microbiomes, and the first assessment of seasonal variation in subways using culture-independent methods. While there were strong similarities between air and surface and across seasons, we found both diversity and the abundances of certain taxa to differ. This constitutes a significant step towards understanding the composition and dynamics of bacterial communities in subways, a highly important environment in our increasingly urbanized and interconnect world.
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