Airborne particles have been linked to increased mortality and morbidity. As most research has focused on fine particles (PM_2.5), the health implications of coarse particles (PM_10-2.5) are not well understood. We conducted a systematic review and meta-analysis of associations for short- and long-term PM_10-2.5 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 PM_10-2.5 concentrations, with stronger relationships for respiratory than cardiovascular endpoints. Reported associations were highly heterogeneous, however, especially by geographic region and average PM_10-2.5 concentrations. Adjustment for PM_2.5 and publication bias resulted in weaker and less precise effect estimates, although positive associations remained for short-term PM_10-2.5 concentrations. Inconsistent relationships between effect estimates for PM_10-2.5 and correlations between PM_10-2.5 and PM_2.5 concentrations, however, indicate that PM_10-2.5 associations cannot be solely explained by co-exposure to PM_2.5. While suggestive evidence was found of increased mortality with long-term PM_10-2.5 concentrations, these associations were not robust to control for PM_2.5. Additional research is required to better understand sources of heterogeneity of associations between PM_10-2.5 and adverse health outcomes.

Coarse (PM_10−2.5) and fine (PM_2.5) particulate matter in the atmosphere adversely affect human health and influence climate. While PM_2.5 is relatively well studied, less is known about the sources and fate of PM_10−2.5. The Colorado Coarse Rural-Urban Sources and Health (CCRUSH) study measured PM_10−2.5 and PM_2.5 mass concentrations, as well as the fraction of semi-volatile material (SVM) in each size regime (SVM_2.5, SVM_10−2.5), from 2009 to early 2012 in Denver and comparatively rural Greeley, Colorado. Agricultural operations east of Greeley appear to have contributed to the peak PM_10−2.5 concentrations there, but concentrations were generally lower in Greeley than in Denver. Traffic-influenced sites in Denver had PM_10−2.5 concentrations that averaged from 14.6 to 19.7 µg m⁻³ and mean PM_10−2.5 ∕ PM₁₀ ratios of 0.56 to 0.70, higher than at residential sites in Denver or Greeley. PM_10−2.5 concentrations were more temporally variable than PM_2.5 concentrations. Concentrations of the two pollutants were not correlated. Spatial correlations of daily averaged PM_10−2.5 concentrations ranged from 0.59 to 0.62 for pairs of sites in Denver and from 0.47 to 0.70 between Denver and Greeley. Compared to PM_10−2.5, concentrations of PM_2.5 were more correlated across sites within Denver and less correlated between Denver and Greeley. PM_10−2.5 concentrations were highest during the summer and early fall, while PM_2.5 and SVM_2.5 concentrations peaked in winter during periodic multi-day inversions. SVM_10−2.5 concentrations were low at all sites. Diurnal peaks in PM_10−2.5 and PM_2.5 concentrations corresponded to morning and afternoon peaks of traffic activity, and were enhanced by boundary layer dynamics. SVM_2.5 concentrations peaked around noon on both weekdays and weekends. PM_10−2.5 concentrations at sites located near highways generally increased with wind speeds above about 3 m s⁻¹. Little wind speed dependence was observed for the residential sites in Denver and Greeley. The mass concentration data reported here are being used in ongoing epidemiologic studies for PM in northeastern Colorado.

Aerosol measurements were collected at fifteen homes over the course of one year in Colorado (USA) to understand the temporal variability of indoor air particulate matter and bacterial concentrations and their relationship with home characteristics, inhabitant activities, and outdoor air particulate matter (PM). Indoor and outdoor PM_2.5 concentrations averaged (±st. dev.) 8.1 ± 8.1 μg/m³ and 6.8 ± 4.5 μg/m³, respectively. Indoor PM_2.5 was statistically significantly higher during summer compared to spring and winter; outdoor PM_2.5 was significantly higher for summer compared to spring and fall. The PM_2.5 I/O ratio was 1.6 ± 2.4 averaged across all homes and seasons and was not statistically significantly different across the seasons. Average indoor PM₁₀ was 15.4 ± 18.3 μg/m³ and was significantly higher during summer compared to all other seasons. Total suspended particulate bacterial biomass, as determined by qPCR, revealed very little seasonal differences across and within the homes. The qPCR I/O ratio was statistically different across seasons, with the highest I/O ratio in the spring and lowest in the summer. Using one-minute indoor PM₁₀ data and activity logs, it was observed that elevated particulate concentrations commonly occurred when inhabitants were cooking and during periods with elevated outdoor concentrations.

In studies of coarse particulate matter (PM_10-2.5), mass concentrations are often estimated through the subtraction of PM_2.5 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 PM_10-2.5 estimation when using the possible combinations of PM₁₀ and PM_2.5 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 PM_10-2.5 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 PM_10-2.5 mass and spatial characteristics due to the very low semivolatile PM_10-2.5 concentrations in Colorado. Estimation using either a PM_2.5 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 PM_10-2.5. 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 PM_2.5 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 PM_2.5 from total PM_2.5 concentrations. By estimating nonvolatile PM_2.5 concentrations from this relationship, PM_10-2.5 was calculated as the difference between nonvolatile PM₁₀ and PM_2.5 concentrations. Implications: Errors in the estimation of PM_10-2.5 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 PM_10-2.5 is regulated in the future. Estimating PM_10-2.5 mass concentrations using nonvolatile mass concentrations from collocated PM₁₀ and PM_2.5 TEOM monitors closely estimates the total PM_10-2.5 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 publisher's online edition of the Journal of the Air & Waste Management Association.

Background: Isolation space must be expanded during pandemics involving airborne transmission. Little to no work has been done to establish optimal design strategies and implementation plans to ease surge capacity and expand isolation capacity over long periods in congregate living facilities. The COVID-19 pandemic has an airborne transmission component and requires isolation, which is difficult to accomplish in skilled nursing facilities. Purpose: In this study we designed, implemented, and validated an isolation space at a skilled nursing facility in Lancaster, PA. The overall goal was to minimize disease transmission between residents and staff within the facility. Basic Procedures: We created an isolation space by modifying an existing HVAC system of the SNF. We measured pressure on-site and performed computational fluid dynamics and Lagrangian particle-based modeling to test containment and possible transmission extent given the isolation space is considered negative rather than individual rooms. Main Findings: Pressure data shows the isolation space maintained an average hourly value of (standard deviation) -2.3 Pa (0.12 Pa) pressure differential between it and the external hallway connected to the rest of the facility. No transmission of SARS-CoV-2 between residents isolated to the space occurred, nor did any transmission to the staff or other residents occur. The isolation space was successfully implemented and, as of writing, continues to be operational through the pandemic. Highlights: Negative pressure isolation space is an effective method to meet needed surge capacity during the COVID-19 pandemic and future pandemics Planning for how and where to rapidly create a negative pressure isolation space is needed in congregate living areas such as skilled nursing facilities This demonstration shows the feasibility of using low-cost and in-house systems to quickly create negative pressure within a skilled nursing facility hallway and to maintain these conditions, minimizing disease transmission between residents and staff