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People generally spend more time indoors than outdoors resulting in a higher proportion of exposure to particulate matter (PM) occurring indoors. Consequently, indoor PM levels, in contrast to outdoor PM levels, may have a stronger relationship with lung function. To test this hypothesis, indoor and outdoor PM 2.5 and fungal spore data were simultaneously collected from the homes of forty-four asthmatic children aged 10-16 years. An optical absorption technique was utilized on the collected PM 2.5 mass to obtain concentrations of black carbon (BC) and ultraviolet light absorbing particulate matter, (UVPM; a marker of light absorbing PM 2.5 emitted from smoldering organics). Enrolled children completed spirometry after environmental measurements were made. Given the high correlation between PM 2.5 , BC, and UVPM, principal component analysis was used to obtain uncorrelated summaries of the measured PM. Separate linear mixed-effect models were developed to estimate the association between principal components of the PM variables and spirometry values, as well as the uncorrelated original PM variables and spirometry values. A one-unit increase in the first principal component variable representing indoor PM (predominantly composed of UVPM and PM 2.5 ) was associated with 4.1% decrease (99% CI = -6.9, -1.4) in FEV 1 /FVC ratio. 11.3 μg/m 3 increase in indoor UVPM was associated with 6.4% and 14.7% decrease (99% CI = -10.4, -2.4 and 99% CI = -26.3, -2.9, respectively) in percent predicted FEV 1 /FVC ratio and FEF 25-75 respectively. Additionally, 17.7 μg/m 3 increase in indoor PM 2.5 was associated with 6.1% and 12.9% decrease (99% CI = -10.2, -1.9 and 99% CI = -24.9, -1.0, respectively) in percent predicted FEV 1 /FVC ratio and FEF 25-75 , respectively. Outdoor PM, indoor BC, and indoor fungal spores were not significantly associated with lung function. The results indicate that indoor PM is more strongly associated with lung function in children with asthma as compared with outdoor PM., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The research project described in this article was undertaken to establish baseline information for a Health Impact Assessment (HIA) project of Interstate 75 road construction in Cincinnati, Ohio. The objective of the authors' study was to evaluate the concentrations of elemental and organic carbon (EC and OC), as well as characterize particle number concentrations using devices that measure the fine fraction in the range of 0.02-1 microm and the coarse fraction up to 20 pm. The measurements were conducted at two sites located in the proximity of an interstate highway (at 124 and 277 m) as well as at a remote control site (at >2000 m from any interstate highway). Samples were collected for 24 hours over 12 days in each season (i.e., summer, fall, and winter). Wind data were obtained from the area weather station. Data were analyzed using mixed linear models. Significant increases in concentrations of EC, OC, and fine particles as well as in EC/OC ratios were observed with decreased distance to the highway; this difference was more pronounced in the fall. These results suggest that residents and workers in areas near high-traffic highways may be exposed to elevated levels of airborne fine particles. The results can be used as a baseline for future HIAs of road construction in the area.

A time series model was fitted to the pollen concentration data collected in the Greater Cincinnati area for the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). A traditional time series analysis and temporal variogram approach were applied to the regularly spaced databases (collected in 2003) and irregularly spaced ones (collected in 2002), respectively. The aim was to evaluate the effect of the sampling frequency on the sampling precision in terms of inverse of standard error of the overall level of mean value across time. The presence of high autocorrelation in the data was confirmed and indicated some degree of temporal redundancy in the pollen concentration data. Therefore, it was suggested that sampling frequency could be reduced from once a day to once every several days without a major loss of sampling precision of the overall mean over time. Considering the trade-offs between sampling frequency and the possibility of sampling bias increasing with larger sampling interval, we recommend that the sampling interval should take values from 3 to 5 days for the pollen monitoring program, if the goal is to track the long-term average.

In an effort to better understand the relationship between different fungal sampling methods in the indoor environment, four methods were used to quantify mold contamination in 13 homes with visible mold. Swab, fungal spore source strength tester (FSSST), and air samples (total of 52 samples) were analyzed using both the microscopic (total spore count) and culture-based (CFU count) enumeration techniques. Settled dust samples were analyzed for culturable fungi only, as the microscopic enumeration was restricted by the masking effect. The relationships between the data obtained with the different sampling methods were examined using correlation analysis. Significant relationships were observed between the data obtained from swab and FSSST samples both by the total counting (r = 0.822, p < 0.05) and by the CFU counting (r = 0.935, p < 0.01). No relationships were observed between air and FSSST samples or air and settled dust samples. Percentage culturability of spores for each sampling method was also calculated and found to vary greatly for all three methods (swab: 0.03% to 63%, FSSST: 0.1% to > 100%, air: 0.7% to 79%). These findings confirm that reliance on one sampling or enumeration method for characterization of an indoor mold source might not provide an accurate estimate of fungal contamination of a microenvironment. Furthermore, FSSST sampling appears to be an effective measurement of a mold source in the field, providing an upper bound estimate of potential mold spore release into the indoor air. Because of the small sample size of this study, however, further research is needed to better understand the observed relationships in this study.

In this study, we have examined the relationships between the concentrations of ambient inhalable airborne fungi and pollen with PM10, PM2.5, ozone, organic carbon, selected trace metals (cadmium, copper, lead, and zinc), temperature, and relative humidity. The database was collected in Cincinnati, Ohio, USA, during two consecutive years. Measurements of all environmental variables were performed at the same site continuously 5 days a week except during winter months. The airborne concentrations of biological and non-biological pollutants ranged as follows: total fungi: 184-16 979 spores m(-3); total pollen: 0-6692 pollen m(-3); PM10: 6.70-65.38 microg m(-3); PM2.5: 5.04-45.02 microg m(-3); and ozone: 2.54-64.17 ppb. Higher levels of total inhalable fungi and particulate matter were found during fall and summer months. In contrast, total pollen concentration showed elevated levels in spring. Peak concentrations of ozone were observed during summer and beginning of fall. Our study concluded that several types of inhalable airborne fungi and pollen, particulate matter, and ozone could be positively correlated as a result of the atmospheric temperature influence.

The objective of this study was to evaluate the PM(2.5) monitoring network established in the Greater Cincinnati and Northern Kentucky metropolitan area for measuring the 24 h integrated PM(2.5) concentration, as well as-at selected sites-hourly PM(2.5) concentration and 24 h integrated PM(2.5) speciation. The data collected during three years at 13 measurement sites were analyzed for spatial and temporal variations. It was found that both daily and hourly concentrations of PM(2.5) have low spatial variation due to a regional influence of secondary ammonium sulfate. In contrast, the trace element concentrations had high spatial variation. Seasonal variation accounted for most of the total temporal variation (60%), while yearly, monthly, weekly and daily variations were lower. The variance components and cluster analyses were applied to optimize the number of sites for measuring the 24 h PM(2.5) concentration. It was found that the 13-site network may be optimized by reducing the number of sites to 8, which would result in a relative precision reduction of 9% and a relative cost reduction of 36%. At the same time, the data suggest that the spatial resolution of speciation monitors and real-time PM(2.5) mass monitors should be increased to better represent spatial and temporal variations of the markers of local air pollution sources.

The objective of this study was to determine if there is an exposure gradient in particulate matter concentrations for people living near interstate highways, and to determine how far from the highway the gradient extends. Air samples were collected in a residential area of Greater Cincinnati in the vicinity of two major highways. The measurements were conducted at different distances from the highways by using ultrafine particle counters (measurement range: 0.02-1 microm), optical particle counters (0.3-20 microm), and PM2.5 Harvard Impactors (0.02-2.5 microm). The collected PM2.5 samples were analyzed for mass concentration, for elemental and organic carbon, and for elemental concentrations. The results show that the aerosol concentration gradient was most clearly seen in the particle number concentration measured by the ultrafine particle counters. The concentration of ultrafine particles decreased to half between the sampling points located at 50 m and 150 m downwind from the highway. Additionally, elemental analysis revealed a gradient in sulfur concentrations up to 400 m from the highway in a residential area that does not have major nearby industrial sources. This gradient was qualitatively attributed to the sulfate particle emissions from diesel engine exhausts, and was supported by the concentration data on several key elements indicative of traffic sources (road dust and diesel exhaust). As different particulate components gave different profiles of the diesel exposure gradient, these results indicate that no single element or component of diesel exhaust can be used as a surrogate for diesel exposure, but more comprehensive signature analysis is needed. This characterization is crucial especially when the exposure data are to be used in epidemiological studies.

This study investigated the evolution of airborne particle concentration and size distribution following abatement work in a controlled environment utilizing direct real-time particle monitoring and used it to project potential lead loadings as those particles settle. An 860 ft3 environmental test chamber with sophisticated ventilation and air purifying systems was built. Wooden doors with lead-based paint were dry sanded or scraped to generate the highest feasible airborne lead concentrations. Size-fractional airborne particle concentrations decreased exponentially with time in all tests, even with no air exchange, consistent with the stirred model of constantly mixed air, which predicts longer settling than for tranquil settling. Very low levels of air mixing generated by temperature gradients and initial room air turbulence affected particle settling. About 90% of airborne lead mass settled within 1 hour after active abatement, before final cleaning began. During the second waiting period of 1 hour, which followed cleaning of the floor, additional dust settled so that the additional potential lead loading from remaining airborne lead was less than 20 microg/ft2. For this worst case scenario, the underestimate of the lead loading done by the clearance sampling did not exceed about 30%. For more realistic conditions, the underestimates are projected to be much lower than the new 40 microg/ft2 Housing and Urban Development (HUD) clearance standards for floor dust lead. These results were obtained for the first waiting period (between the end of active abatement and the beginning of cleaning) of 1 hour, as recommended by HUD guidelines. Thus, this study demonstrates no need to increase either the first or second waiting period.