Nicholas Clements

Seasonal variability in bacterial and fungal diversity of the near-surface atmosphere.

Bacteria and fungi are ubiquitous throughout the Earths lower atmosphere where they often represent an important component of atmospheric aerosols with the potential to impact human health and atmospheric dynamics. However, the diversity, composition, and spatiotemporal dynamics of these airborne microbes remain poorly understood. We performed a comprehensive analysis of airborne microbes across two aerosol size fractions at urban and rural sites in the Colorado Front Range over a 14-month period. Coarse (PM10-2.5) and fine (PM2.5) particulate matter samples were collected at weekly intervals with both bacterial and fungal diversity assessed via high-throughput sequencing. The diversity and composition of the airborne communities varied across the sites, between the two size fractions, and over time. Bacteria were the dominant type of bioaerosol in the collected air samples, while fungi and plants (pollen) made up the remainder, with the relative abundances of fungi peaking during the spring and summer months. As bacteria made up the majority of bioaerosol particles, we analyzed the bacterial communities in greater detail using a bacterial-specific 16S rRNA gene sequencing approach. Overall, bacterial taxonomic richness and the relative abundances of specific bacterial taxa exhibited significant patterns of seasonality. Likewise, airborne bacterial communities varied significantly between sites and across aerosol size fractions. Source-tracking analyses indicate that soils and leaves represented important sources of bacteria to the near-surface atmosphere across all locations with cow fecal bacteria also representing an important source of bioaerosols at the more rural sites during early fall and early spring. Together, these data suggest that a complex set of environmental factors, including changes in atmospheric conditions and shifts in the relative importance of available microbial sources, act to control the composition of microbial bioaerosols in rural and urban environments.

Ambient Coarse Particulate Matter and Human Health: A Systematic Review and Meta-Analysis

Airborne particles have been linked to increased mortality and morbidity. As most research has focused on fine particles (PM2.5), the health implications of coarse particles (PM10-2.5) are not well understood. We conducted a systematic review and meta-analysis of associations for short- and long-term PM10-2.5 concentrations with mortality and hospital admissions. Using 23 mortality and 10 hospital admissions studies, we documented suggestive evidence of increased morbidity and mortality in relation to higher short-term PM10-2.5 concentrations, with stronger relationships for respiratory than cardiovascular endpoints. Reported associations were highly heterogeneous, however, especially by geographic region and average PM10-2.5 concentrations. Adjustment for PM2.5 and publication bias resulted in weaker and less precise effect estimates, although positive associations remained for short-term PM10-2.5 concentrations. Inconsistent relationships between effect estimates for PM10-2.5 and correlations between PM10-2.5 and PM2.5 concentrations, however, indicate that PM10-2.5 associations cannot be solely explained by co-exposure to PM2.5. While suggestive evidence was found of increased mortality with long-term PM10-2.5 concentrations, these associations were not robust to control for PM2.5. Additional research is required to better understand sources of heterogeneity of associations between PM10-2.5 and adverse health outcomes.

Impacts of flood damage on airborne bacteria and fungi in homes after the 2013 Colorado Front Range flood.

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.

Characterization and Nonparametric Regression of Rural and Urban Coarse Particulate Matter Mass Concentrations in Northeastern Colorado

The Colorado Coarse Rural Urban Sources and Health study (CCRUSH) is an ongoing study of the relationship between coarse particulate mass concentrations (PM10–2.5, particulate matter with diameter between 2.5 and 10 μm) and selected health effects. For two urban monitoring sites in Denver, CO, and two comparatively rural sites in Greeley, CO, hourly mass concentrations of PM10–2.5 and fine particulate matter (PM2.5, diameter less than 2.5 μm) have been measured by using dichotomous tapered element oscillating microbalances (TEOMs) with Filter Dynamics Measurement Systems (FDMS). This paper presents air quality results from just over a year of PM2.5 and PM10–2.5 measurements. Average PM2.5 concentrations ranged from 7.7 to 9.2 μg m−3 across the four sites with higher concentrations in Denver than Greeley. Average PM10–2.5 concentrations ranged from 9.0 to 15.5 μg m−3 with the highest values at the site in northeast Denver. Temporal variability in PM10–2.5 was higher than that in PM2.5 concentrations at all four sites. The two Greeley sites displayed moderate spatial correlation for PM2.5 and high correlation for PM10–2.5, whereas the two Denver sites showed lower spatial correlation for both PM sizes. PM10–2.5 concentrations in Denver were highest with winds from the direction of the citys urban core. PM10–2.5 concentrations in Greeley were moderately elevated with winds from the southwest to the northwest, coming from Denver and other large Front Range communities. Wind speed regressions for PM10–2.5 at the Denver sites primarily exhibited resuspension effects, while PM10–2.5 concentrations in Greeley showed relatively complex wind speed dependence. Copyright 2012 American Association for Aerosol Research

High temporal variability in airborne bacterial diversity and abundance inside single‐family residences

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.

Errors in coarse particulate matter mass concentrations and spatiotemporal characteristics when using subtraction estimation methods

In studies of coarse particulate matter (PM10-2.5), mass concentrations are often estimated through the subtraction of PM2.5 from collocated PM10 tapered element oscillating microbalance (TEOM) measurements. Though all field instruments have yet to be updated, the Filter Dynamic Measurement System (FDMS) was introduced to account for the loss of semivolatile material from heated TEOM filters. To assess errors in PM10-2.5 estimation when using the possible combinations of PM10 and PM2.5 TEOM units with and without FDMS, data from three monitoring sites of the Colorado Coarse Rural–Urban Sources and Health (CCRUSH) study were used to simulate four possible subtraction methods for estimating PM10-2.5 mass concentrations. Assuming all mass is accounted for using collocated TEOMs with FDMS, the three other subtraction methods were assessed for biases in absolute mass concentration, temporal variability, spatial correlation, and homogeneity. Results show collocated units without FDMS closely estimate actual PM10-2.5 mass and spatial characteristics due to the very low semivolatile PM10-2.5 concentrations in Colorado. Estimation using either a PM2.5 or PM10 monitor without FDMS introduced absolute biases of 2.4 µg/m3 (25%) to –2.3 µg/m3 (–24%), respectively. Such errors are directly related to the unmeasured semivolatile mass and alter measures of spatiotemporal variability and homogeneity, all of which have implications for the regulatory and epidemiology communities concerned about PM10-2.5. Two monitoring sites operated by the state of Colorado were considered for inclusion in the CCRUSH acute health effects study, but concentrations were biased due to sampling with an FDMS-equipped PM2.5 TEOM and PM10 TEOM not corrected for semivolatile mass loss. A regression-based model was developed for removing the error in these measurements by estimating the semivolatile concentration of PM2.5 from total PM2.5 concentrations. By estimating nonvolatile PM2.5 concentrations from this relationship, PM10-2.5 was calculated as the difference between nonvolatile PM10 and PM2.5 concentrations. Implications: Errors in the estimation of PM10-2.5 concentrations using subtraction methods were shown to be related to the unmeasured semivolatile mass when using certain combinations of TEOM instruments. For the northeastern Colorado region, the absolute bias associated with this error significantly affects mean and 95th percentile values, which would affect assessment of compliance if PM10-2.5 is regulated in the future. Estimating PM10-2.5 mass concentrations using nonvolatile mass concentrations from collocated PM10 and PM2.5 TEOM monitors closely estimates the total PM10-2.5 mass concentrations. A corrective model that removes the described error was developed and applied to data from two sites in Denver. Supplemental Materials: Supplemental materials are available for this paper. Go to the publishers online edition of the Journal of the Air & Waste Management Association.