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Flood-damaged homes typically have elevated microbial loads, and their occupants have an increased incidence of allergies, asthma, and other respiratory ailments, yet the microbial communities in these homes remain under-studied. Using culture-independent approaches, we characterized bacterial and fungal communities in homes in Boulder, CO, USA 2-3 months after the historic September, 2013 flooding event. We collected passive air samples from basements in 50 homes (36 flood-damaged, 14 non-flooded), and we sequenced the bacterial 16S rRNA gene (V4-V5 region) and the fungal ITS1 region from these samples for community analyses. Quantitative PCR was used to estimate the abundances of bacteria and fungi in the passive air samples. Results indicate significant differences in bacterial and fungal community composition between flooded and non-flooded homes. Fungal abundances were estimated to be three times higher in flooded, relative to non-flooded homes, but there were no significant differences in bacterial abundances. Penicillium (fungi) and Pseudomonadaceae and Enterobacteriaceae (bacteria) were among the most abundant taxa in flooded homes. Our results suggest that bacterial and fungal communities continue to be affected by flooding, even after relative humidity has returned to baseline levels and remediation has removed any visible evidence of flood damage.

Our homes are microbial habitats, and although the amounts and types of bacteria in indoor air have been shown to vary substantially across residences, temporal variability within homes has rarely been characterized. Here, we sought to quantify the temporal variability in the amounts and types of airborne bacteria in homes, and what factors drive this variability. We collected filter samples of indoor and outdoor air in 15 homes over 1 year (approximately eight time points per home, two per season), and we used culture-independent DNA sequencing approaches to characterize bacterial community composition. Significant differences in indoor air community composition were observed both between homes and within each home over time. Indoor and outdoor air community compositions were not significantly correlated, suggesting that indoor and outdoor air communities are decoupled. Indoor air communities from the same home were often just as different at adjacent time points as they were across larger temporal distances, and temporal variation correlated with changes in environmental conditions, including temperature and relative humidity. Although all homes had highly variable indoor air communities, homes with the most temporally variable communities had more stable, lower average microbial loads than homes with less variable communities.

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An ultrafine, water-based condensation particle counter (U-WCPC, TSI Model 3786) has been compared to a butanol-based ultrafine counter (U-BCPC, TSI Model 3025) for measurement of atmospheric and freeway-tunnel aerosols. The U-WCPC utilizes a warm, wet-walled growth tube to activate and grow particles through water condensation in a laminar-flow. It has an aerosol sampling rate of 0.3 L/min, and a nominal detection limit near 3 nm. Several field comparisons were made to the butanol-based instrument with the same nominal detection limit. For measurements of size-selected aerosols with diameters of 5 nm and larger the two instruments generally agreed, with a mean response within 5%. At 3 nm particle size differences were observed, and these differences varied with the data set. Measurements of ambient aerosol in Boulder, Colorado showed higher counting efficiency at 3 nm with the U-BCPC, while in a California freeway tunnel the opposite trend was observed, with higher counting efficiencies at 3 nm observed by the U-WCPC. For direct measurement of atmospheric aerosols, the two types of instruments yielded equivalent concentrations, independent of particle number concentration.

Data from a different mobility particle sizer (DMPS) or an electrical aerosol analyzer ( E M ) has been combined with data from an aerodynamic particle sizer (APS) and converted to obtain aerosol mass distribution parameters on a near real-time basis. A low pressure impactor (LPI), a direct and independent measure of this mass distribution, provided information for comparison.The number distribution of particles within the electrical measurement range was obtained with the DMPS and E M . Data from the APS for particles greater than that size were used to complete the number distribution. Two methods of obtaining mass distribution parameters from this number data were attempted. The first was to convert the number data, channel by channel, to mass data and then fit a lognormal function to this new mass distribution. The

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