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Biomedical subjects

Dainius Martuzevicius

Publications and source records attributed to Dainius Martuzevicius.

4 recordsLinked to original sources

Correlation of ambient inhalable bioaerosols with particulate matter and ozone: a two-year 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.

Aerosols↗

Sampling over time: developing a cost effective and precise exposure assessment program.

Studies requiring ambient exposure assessments invariably ask: How often should measurements be taken? Answer to such questions is dictated by budgetary considerations as well as spatial and temporal variability in the data. For example, do we obtain measurements during all seasons, all months within seasons, weeks within months and days within weeks? On one hand, we can obtain a one-time snapshot sample and regard it as representing the "true" mean exposure. On the other hand, we may obtain a large number of measurements over time and then average these in order to represent this "true" mean exposure. The former estimate is the least expensive but may also be the least precise while the latter, may be very precise but prohibitively costly. In this paper, we demonstrate how a pilot study can be undertaken with a potentially promising and feasible sampling plan for the full-scale study. By applying the statistical methodology of variance component analysis (VCA) to the pilot study data and exploiting mathematical relationship between the variance of the overall mean exposure and posited variance components, we can develop a sampling design with decreased sampling costs and/or increased precision of the mean exposure. Our approach was applied to determine sampling design choices for an on-going study that aimed at assessing ambient particulate matter exposure. We conclude that a pilot study followed by the VCA analysis may often lead to sampling design choices that offer considerable cost savings and, at the same time, promise to provide relatively precise estimates of the mean exposure for the subsequent full-scale study.

Analysis of Variance↗

Evaluation and optimization of an urban PM2.5 monitoring network.

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.

Air Pollutants↗

Concentration gradient patterns of aerosol particles near interstate highways in the Greater Cincinnati airshed.

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.

Air Pollutants↗