Biomedical subjects

William E Wilson

Publications and source records attributed to William E Wilson.

10 recordsLinked to original sources

PubMed2006

Estimation of ambient and non-ambient components of particulate matter exposure from a personal monitoring panel study.

To provide additional insight into factors affecting exposure to airborne particulate matter and the resultant health effects, we developed a method to estimate the ambient and nonambient components of total personal exposure. The ambient (or outdoor) component of total personal exposure to particulate matter (PM) (called ambient exposure) includes exposure to the ambient PM concentration while outdoors and exposure while indoors to ambient PM that has infiltrated indoors. The nonambient component of total personal exposure to PM (called nonambient exposure) refers to exposure to PM generated by indoor sources and an individual's personal activity. We used data collected from a personal monitoring study in Vancouver, Canada to demonstrate the methodology. In this study, ambient PM(2.5) exposure was 71% of the measured ambient PM(2.5) concentration and was responsible for 44% of the measured total personal PM(2.5) exposure. Regression analysis of the pooled data sets for ambient and total exposure against outdoor concentrations yielded similar slopes (0.76 for ambient and 0.77 for total) but a higher coefficient of determination for ambient exposure (R(2)=0.62) than for total exposure (R(2)=0.072). As expected, the nonambient exposure was not related to the ambient concentration (R(2)<10(-6)). For longitudinal analyses of the relationship between measured personal exposure and ambient concentrations for individual subjects, the correlation of total personal exposure with ambient concentration yielded values of Pearson's r from 0.83 to -0.68 with an average of 0.36. The relationship was statistically significant for only five of the 16 subjects. In contrast, the correlation of the estimated ambient exposure with ambient concentration yielded values of Pearson's r from 0.92 to 0.77 with an average of 0.88; 14 were significant. An example, taken from an epidemiologic analysis using the exposure data from this paper, demonstrates the usefulness of separating total exposure into its ambient and nonambient components.

Air Pollutants↗

PubMed2006

The measurement of fine particulate semivolatile material in urban aerosols.

Ammonium nitrate and semivolatile organic material (SVOM) are significant components of fine particles in urban atmospheres. These components, however, are not properly determined with methods such as the fine particulate matter (PM2.5) Federal Reference Method (FRM) or other single filter samplers because of significant losses of semivolatile material (SVM) from particles collected on the filter during sampling. The R&P tapered element oscillating microbalance (TEOM) monitor also does not measure SVM, because this method heats the sample to remove particle bound water, which also results in evaporation of SVM. Recent advances in monitoring techniques have resulted in samplers for both integrated and continuous measurement of total PM2.5, including the particle concentrator-Brigham Young University organic sampling system (PC-BOSS), the real-time total ambient mass sampler (RAMS), and the R&P filter dynamics measurement system (FDMS) TEOM monitor. Results obtained using these samplers have been compared with those obtained with either a PM2.5 FRM sampler or a TEOM monitor in studies conducted during the past five years. These studies have shown the following: (1) the PC-BOSS, RAMS, and FDMS TEOM are all comparable. Each instrument measures both the nonvolatile material and the SVM. (2) The SVM is not retained on the heated filter of a regular TEOM monitor and is not measured by this sampling technique. (3) Much of the SVM is also lost during sampling from single filter samplers such as the PM2.5 FRM sampler. (4) The amount of SVM lost from single filter samplers can vary from less than one-third of that lost from heated TEOM filters during cold winter conditions to essentially all during warm summer conditions. (5) SVOM can only be reliably collected using an appropriate denuder sampler. (6) A PM2.5 speciation sampler can be easily modified to a denuder sampler with filters that can be analyzed for semivolatile organic carbon (OC), nonvolatile OC, and elemental carbon using existing OC/elemental carbon analytical techniques. The research upon which these statements are based for various urban studies are summarized in this paper.

Air Pollutants, Occupational↗

PubMed2005

Spatial variability of fine particle mass, components, and source contributions during the regional air pollution study in St. Louis.

Community time-series epidemiology typically uses either 24-hour integrated particulate matter (PM) concentrations averaged across several monitors in a city or data obtained at a central monitoring site to relate PM concentrations to human health effects. If the day-to-day variations in 24-hour integrated concentrations differ substantially across an urban area (i.e., daily measurements at monitors at different locations are not highly correlated), then there is a significant potential for exposure misclassification in community time-series epidemiology. If the annual average concentration differs across an urban area, then there is a potential for exposure misclassification in epidemiologic studies that use annual averages (or multi-year averages) as an index of exposure across different cities. The spatial variability in PM2.5 (particulate matter < or = 2.5 microm in aerodynamic diameter), its elemental components, and the contributions from each source category at 10 monitoring sites in St. Louis, Missouri were characterized using the ambient PM2.5 compositional data set of the Regional Air Pollution Study (RAPS) based on the Regional Air Monitoring System (RAMS) conducted between 1975 and 1977. Positive matrix factorization (PMF) was applied to each ambient PM2.5 compositional data set to estimate the contributions from the source categories. The spatial distributions of components and source contributions to PM2.5 at the 10 sites were characterized using Pearson correlation coefficients and coefficients of divergence. Sulfur and PM2.5 are highly correlated elements between all of the site pairs Although the secondary sulfate is the most highly correlated and shows the smallest spatial variability, there is a factor of 1.7 difference in secondary sulfate contributions between the highest and lowest site on average. Motor vehicles represent the next most highly correlated source component. However, there is a factor of 3.6 difference in motor vehicle contributions between the highest and lowest sites. The contributions from point source categories are much more variable. For example, the contributions from incinerators show a difference of a factor of 12.5 between the sites with the lowest and highest contributions. This study demonstrates that the spatial distributions of elemental components of PM2.5 and contributions from source categories can be highly heterogeneous within a given airshed and thus, there is the potential for exposure misclassification when a limited number of ambient PM monitors are used to represent population-average ambient exposures.

Air Pollutants↗

PubMed2005

Exposure to ambient and nonambient components of particulate matter: a comparison of health effects.

BACKGROUND: Numerous epidemiologic studies report associations between outdoor concentrations of particles and adverse health effects. Because personal exposure to particles is frequently dominated by exposure to nonambient particles (those originating from indoor sources), we present an approach to evaluate the relative impacts of ambient and nonambient exposures. METHODS: We developed separate estimates of exposures to ambient and nonambient particles of different size ranges (PM2.5, PM10-2.5 and PM10) based on time-activity data and the use of particle sulfate measurements as a tracer for indoor infiltration of ambient particles. To illustrate the application of these estimates, associations between cardiopulmonary health outcomes and the estimated exposures were compared with associations computed using measurements of personal exposures and outdoor concentrations for a repeated-measures panel study of 16 patients with chronic obstructive pulmonary disease conducted in the summer of 1998 in Vancouver. RESULTS: Total personal fine particle exposures were dominated by exposures to nonambient particles, which were not correlated with ambient fine particle exposures or ambient concentrations. Although total and nonambient particle exposures were not associated with any of the health outcomes, ambient exposures (and to a lesser extent ambient concentrations) were associated with decreased lung function, decreased systolic blood pressure, increased heart rate, and increased supraventricular ectopic heartbeats. Measures of heart rate variability showed less consistent relationships among the various exposure metrics. CONCLUSIONS: These results demonstrate the usefulness of separating total personal particle exposures into their ambient and nonambient components. The results support previous epidemiologic findings using ambient concentrations by demonstrating an association between health outcomes and ambient (outdoor origin) particle exposures but not with nonambient (indoor origin) particle exposures.

Aged↗

PubMed2005

Continuous determination of fine particulate matter mass in the Salt Lake City Environmental Monitoring project: a comparison of real-time and conventional TEOM monitor results.

Fine particulate matter (PM2.5) mass was determined on a continuous basis at the Salt Lake City Environmental Protection Agency Environmental Monitoring for Public Awareness and Community Tracking monitoring site in Salt Lake City, UT, using three different monitoring techniques. Hourly averaged PM2.5 mass data were collected during two sampling periods (summer 2000 and winter 2002) using a real-time total ambient mass sampler (RAMS), sample equilibration system (SES)-tapered element oscillating microbalance (TEOM), and conventional TEOM monitor. This paper compares the results obtained from the various monitoring systems, which differ in their treatment of semivolatile material (SVM; particle-bound water, semivolatile ammonium nitrate, and semivolatile organic compounds). PM2.5 mass results obtained by the RAMS were consistently higher than those obtained by the SES-TEOM and conventional TEOM monitors because of the RAMS ability to measure semivolatile ammonium nitrate and semivolatile organic material but not particle-bound water. The SES-TEOM monitoring system was able to account for an average of 28% of the SVM, whereas the conventional TEOM monitor loses essentially all of the SVM from the single filter during sampling. Occasional mass readings by the various TEOM monitors that are higher than RAMS results may reflect particle-bound water, which, under some conditions, is measured by the TEOM but not the RAMS.

Air Pollutants↗

PubMed2004

Ambient particulate air pollution, heart rate variability, and blood markers of inflammation in a panel of elderly subjects.

Epidemiologic studies report associations between particulate air pollution and cardiopulmonary morbidity and mortality. Although the underlying pathophysiologic mechanisms remain unclear, it has been hypothesized that altered autonomic function and pulmonary/systemic inflammation may play a role. In this study we explored the effects of air pollution on autonomic function measured by changes in heart rate variability (HRV) and blood markers of inflammation in a panel of 88 elderly subjects from three communities along the Wasatch Front in Utah. Subjects participated in multiple sessions of 24-hr ambulatory electrocardiographic monitoring and blood tests. Regression analysis was used to evaluate associations between fine particulate matter [aerodynamic diameter less than or equal to 2.5 microm (PM2.5)] and HRV, C-reactive protein (CRP), blood cell counts, and whole blood viscosity. A 100- microg/m3 increase in PM2.5 was associated with approximately a 35 (SE = 8)-msec decline in standard deviation of all normal R-R intervals (SDNN, a measure of overall HRV); a 42 (SE = 11)-msec decline in square root of the mean of the squared differences between adjacent normal R-R intervals (r-MSSD, an estimate of short-term components of HRV); and a 0.81 (SE = 0.17)-mg/dL increase in CRP. The PM2.5-HRV associations were reasonably consistent and statistically robust, but the CRP association dropped to 0.19 (SE = 0.10) after excluding the most influential subject. PM2.5 was not significantly associated with white or red blood cell counts, platelets, or whole-blood viscosity. Most short-term variability in temporal deviations of HRV and CRP was not explained by PM2.5; however, the small statistically significant associations that were observed suggest that exposure to PM2.5 may be one of multiple factors that influence HRV and CRP.

Aged↗

PubMed2002

Chapter one: exposure measurements.

Determining human exposure to suspended particulate concentrations requires measurements that quantify different particle properties in microenvironments where people live, work, and play. Particle mass, size, and chemical composition are important exposure variables, and these are typically measured with time-integrated samples on filters that are later submitted to laboratory analyses. This requires substantial sample handling, quality assurance, and data reduction. Newer technologies are being developed that allow in-situ, time-resolved measurements for mass, carbon, sulfate, nitrate, particle size, and other variables. These are large measurement systems that are more suitable for fixed monitoring sites than for personal applications. Human exposure studies need to be designed to accomplish specific objectives rather than to serve too many purposes. Resources need to be divided among study design, field sampling, laboratory analysis, quality assurance, data management, and data analysis phases. Many exposure projects allocated too little to the non-measurement activities.

Air Pollutants↗

PubMed2002

Designing monitoring networks to represent outdoor human exposure.

Measurements of outdoor human exposure to suspended particulate matter (PM) are always constrained by available resources. An effective network design requires tradeoffs between variables measured, the number of sampling locations, sample duration, and sampling frequency. Sampling sites are needed to represent neighborhood and urban spatial scales with minimal influences from nearby sources. Although most PM measurements for determining compliance with standards are taken over 24-h periods every third to sixth day, outdoor human exposure assessment requires measurements taken continuously throughout the day, preferably over durations of 1 h or less. More detailed particle size and chemistry data are also desirable, as smaller size fractions and specific chemicals may be better indicators of adverse health effects than total mass samples.

Air Pollutants↗

PubMed2002

Receptor modeling application framework for particle source apportionment.

Receptor models infer contributions from particulate matter (PM) source types using multivariate measurements of particle chemical and physical properties. Receptor models complement source models that estimate concentrations from emissions inventories and transport meteorology. Enrichment factor, chemical mass balance, multiple linear regression, eigenvector. edge detection, neural network, aerosol evolution, and aerosol equilibrium models have all been used to solve particulate air quality problems, and more than 500 citations of their theory and application document these uses. While elements, ions, and carbons were often used to apportion TSP, PM10, and PM2.5 among many source types, many of these components have been reduced in source emissions such that more complex measurements of carbon fractions, specific organic compounds, single particle characteristics, and isotopic abundances now need to be measured in source and receptor samples. Compliance monitoring networks are not usually designed to obtain data for the observables, locations, and time periods that allow receptor models to be applied. Measurements from existing networks can be used to form conceptual models that allow the needed monitoring network to be optimized. The framework for using receptor models to solve air quality problems consists of: (1) formulating a conceptual model; (2) identifying potential sources; (3) characterizing source emissions; (4) obtaining and analyzing ambient PM samples for major components and source markers; (5) confirming source types with multivariate receptor models; (6) quantifying source contributions with the chemical mass balance; (7) estimating profile changes and the limiting precursor gases for secondary aerosols; and (8) reconciling receptor modeling results with source models, emissions inventories, and receptor data analyses.

Air Pollutants↗

PubMedDate not supplied

Dosimetric comparisons of particle deposition and retention in rats and humans.

Much of the information on the toxicity of particulate matter (PM) comes from studies in which laboratory rats were exposed to PM by inhalation or instillation. Optimal use of these toxicologic data requires extrapolation to the human scenario. Assuming that comparable doses should cause comparable effects across species and that species respond similarly to a given dose at a target site, extrapolations only require that dose be defined and then characterized. Dose may be defined in terms of a PM indicator (e.g., particle number or mass), a respiratory region, and the time over which the dose is integrated (i.e., deposited versus retained dose and incremental versus accumulated dose). Dose must also be normalized: for example, unit of dose per body mass, respiratory region surface area, or number of alveolar macrophages. The parameters chosen to define a normalized dose can drastically affect the rat exposure concentration required to provide a normalized dose equivalent to that occurring in a human. The publicly available multiple path particle dosimetry model developed by CIIT Centers for Health Research was used to predict particle deposition and retention in rats and humans. Estimates of particle concentration and exposure duration required for a rat to receive the same dose as received by a human were obtained with consideration of daily activity levels and ambient PM size distributions. These techniques were also used to compare dose and response between rats and humans in several published studies. Results indicate that the relationship between PM dose and response may differ between rats and humans. For acute PM exposures, rats may be less susceptible to inflammatory responses than humans. For chronic exposures to high levels of PM, however, an overload of alveolar clearance in rats may cause them to become more susceptible than humans to adverse pulmonary effects. The dosimetric calculations indicate that to achieve nominally similar acute doses per surface area in rats, relative to humans undergoing moderate to high exertion, PM exposure concentrations for rats would need to be somewhat higher than for humans. Since the clearance of PM is faster from the lung of rats than humans, much higher exposure concentrations are required for the rat to simulate retained burdens. In other cases, rats will require lower exposures than humans to have comparable doses, illustrating the complexity of such analyses. To make accurate estimates of dose, it is essential to have accurate and complete information regarding exposure conditions-that is, not only concentration and duration of exposure, but also the aerosol size distribution. Establishing a firm linkage between exposure and dose requires that consideration be given to particle characteristics, definitions of dose metrics, and biological normalizing factors.

Air Pollutants↗