Biomedical subjects

Charles E Feigley

Publications and source records attributed to Charles E Feigley.

8 recordsLinked to original sources

PubMed2006

The effect of temperature differences on the distribution of an airborne contaminant in an experimental room.

Estimating exposure to contaminants emitted into workroom air is essential for worker protection. Although contaminant concentrations are often not spatially uniform within workrooms, many methods for estimating exposure do not adequately account for this variability. Here the impact of temperature differences within a room on spatial contaminant distribution was studied. Tracer gas (99.5% propylene) concentrations were monitored automatically at 144 sampling points with a photoionization detector. One wall was chosen to represent a building's external wall and was heated or cooled to simulate summer or winter conditions. Experiments were preformed at two flow rates (5.5 and 3.3 m(3) min(-1)) and six thermal conditions (isothermal, three summer conditions and two winter conditions). For 5.5 m(3) min(-1) and all thermal conditions, the coefficient of variation (CV) ranged from 0.34 to 0.45 and the normalized average concentrations were similar. For 3.3 m(3) min(-1), winter conditions produced greater spatial variability of concentration (CV = 0.72 and 1.10) than isothermal or summer conditions (CV range = 0.29-0.34). Tests simulating winter conditions suggest that the resulting stable temperature structure inhibited the dilution of the tracer and enhanced its segregation in the lower portion of the room, especially for the lower flow rate (3.3 m(3) min(-1)). Therefore, not explicitly addressing thermal effect in exposure modeling may impact the estimated accuracy and precision when used for rooms that are non-isothermal and not well mixed. These findings also have implications for air monitoring. Dispersion patterns for different thermal conditions were found to be substantially different, even when the mean concentrations were nearly the same. Thus, monitoring data from a single season should not be taken as representative of the entire year, when summer and winter conditions create temperature gradients in a room.

Air Movements↗

PubMed2006

A second look at the Palmes' diffusive sampler.

The Palmes' tube, the first diffusive sampler incorporating a fixed path length, has received wide usage for the sampling of a large number of gaseous pollutants. But despite numerous previous studies, questions remain regarding the accuracy of these inexpensive, simple-to-construct, open-ended samplers. Here the mass transfer resistance in a Palmes' diffusive sampler was measured using the loss of cyclohexane from a Palmes' tube containing liquid cyclohexane at its base. The average loss rates, at factorial combinations of five air incidence angles evenly spaced from 270 degrees to 90 degrees, and five air speeds from 0.5 m/sec to 2.5 m/sec ranged from 46% to 121% higher than rates calculated from the physical dimensions of the sampler, proving the need to calibrate these samplers rather than relying on a theoretical calculation. The mass transfer resistance was nearly constant when the airflow was perpendicular to the sampler and sufficiently high to avoid stagnation, a finding that may explain the widespread acceptance of the results obtained using this sampler.

Air Pollutants↗

PubMed2005

Scale and shape issues in focused cluster power for count data.

BACKGROUND: Interest in the development of statistical methods for disease cluster detection has experienced rapid growth in recent years. Evaluations of statistical power provide important information for the selection of an appropriate statistical method in environmentally-related disease cluster investigations. Published power evaluations have not yet addressed the use of models for focused cluster detection and have not fully investigated the issues of disease cluster scale and shape. As meteorological and other factors can impact the dispersion of environmental toxicants, it follows that environmental exposures and associated diseases can be dispersed in a variety of spatial patterns. This study simulates disease clusters in a variety of shapes and scales around a centrally located single pollution source. We evaluate the power of a range of focused cluster tests and generalized linear models to detect these various cluster shapes and scales for count data. RESULTS: In general, the power of hypothesis tests and models to detect focused clusters improved when the test or model included parameters specific to the shape of cluster being examined (i.e. inclusion of a function for direction improved power of models to detect clustering with an angular effect). However, power to detect clusters where the risk peaked and then declined was limited. CONCLUSION: Findings from this investigation show sizeable changes in power according to the scale and shape of the cluster and the test or model applied. These findings demonstrate the importance of selecting a test or model with functions appropriate to detect the spatial pattern of the disease cluster.

Journal Article↗

PubMed2005

Coastal terrorism: using tabletop discussions to enhance coastal community infrastructure through relationship building.

The unique vulnerability of the nation's ports to terrorist attacks and other major disasters requires development of specialized training approaches that integrate and connect critical stakeholders. In 2003, the University of South Carolina Center for Public Health Preparedness developed and held its first Coastal Terrorism workshop in conjunction with the National Oceanic and Atmospheric Administration. Key federal, regional, state, and coastal agency leaders were invited to the 2-day event to explore, in a no-risk environment, the crucial role that public health agencies would play in a covert biological agent incident aboard a cruise ship. The incident began as a possible outbreak of a Norwalk-like viral agent; however, as the scenario unfolded, evidence of a terrorist plot emerged. This immediately shifted the scenario from a public health-dominated incident to one directed by law enforcement. Communication and coordination issues surfaced illustrating potential conflicts between disciplines and jurisdictions in terms of roles and responsibilities of responding agencies. The goals of the workshop were to facilitate communication and interagency networking among coastal stakeholders while assessing their training and research needs and increasing their familiarity with resources and protocols regarding a bioterrorist coastal event. Positive systems changes were observed.

Bioterrorism↗

PubMed2002

Improving the use of mixing factors for dilution ventilation design.

In specifying dilution ventilation flow rate, a safety factor, K, is often used to provide a margin of safety and to compensate for uncertainties and health impact severity. In current practice, the selection of K is very subjective. Here the component of K accounting for imperfect mixing, Km, was studied to develop more effective and efficient design procedures. Air flow and contaminant distribution in a 10 m x 3 m x 7 m room with a single contaminant source on a 1-m high table were simulated for steady, isothermal conditions using computational fluid dynamics. A series of 10 simulations explored factorial combinations of air exchange rates (1, 2,4, 8, 16 ACH) and inlet types (a high wall jet and a ceiling diffuser). Nine additional simulations explored exhaust opening location effects and 13 other simulations investigated source location effects. Km was calculated at each of 25,600 grid locations within the room by linear regression of emission rate/flow rate (G/Q) on concentration (C). The linear relationship between C and G/Q at each of the points was nearly perfect (R2 > 0.97). For the simulations with varying dilution flow rate, Km ranged from 0.19 to 2.86 for the wall jet and from 0.94 to 4.34 for the ceiling diffuser. Holding G/Q at 100 ppm and varying source and exhaust location produced room average concentrations from 55.7 to 173 ppm. Unlike orthodox design approaches, this work suggests that air monitoring data often can be used to calculate dilution flow rate requirements. Also, dilution flow rate requirements may be reduced by enhancing room mixing with fans or altering air inlet configuration. However, mixing should not be increased if the altered room air currents could transport contaminant to an occupant's breathing zone or interfere with other control methods that depend on segregation of incoming air and contaminant.

Humans↗

PubMed2002

An investigation of air inlet velocity in simulating the dispersion of indoor contaminants via computational fluid dynamics.

Computational fluid dynamics (CFD) is potentially a valuable tool for simulating the dispersion of air contaminants in workrooms. However, CFD-estimated airflow and contaminant concentration patterns have not always shown good agreement with experimental results. Thus, understanding the factors affecting the accuracy of such simulations is critical for their successful application in occupational hygiene. The purposes of this study were to validate CFD approaches for simulating the dispersion of gases and vapors in an enclosed space at two air flow rates and to demonstrate the impact of one important determinant of simulation accuracy. The concentration of a tracer gas, isobutylene, was measured at 117 points in a rectangular chamber [1 (L) x 0.3 (H) x 0.7 m (W)] using a photoionization analyzer. Chamber air flow rates were scaled using geometric and kinematic similarity criteria to represent a full-sized room at two Reynolds numbers (Re = 5 x 10(2) and 5 x 10(3)). Also, CFD simulations were conducted to estimate tracer gas concentrations throughout the chamber. The simulation results for two treatments of air inlet velocity (profiled inlet velocity measured in traverses across the air inlet and the assumption that air velocity is uniform across the inlet) were compared with experimental observations. The CFD-simulated 3-dimensional distribution of tracer gas concentration using the profiled inlet velocity showed better agreement qualitatively and quantitatively with measured chamber concentration, while the concentration estimated using the uniform inlet velocity showed poor agreement for both comparisons. For estimating room air contaminant concentrations when inlet velocities can be determined, this study suggests that using the inlet velocity distribution to define inlet boundary conditions for CFD simulations can provide more reliable estimates. When the inlet velocity distribution is not known, for instance for prospective design of dilution ventilation systems, the trials of several velocity profiles with different source, air inlet and air outlet locations may be useful for determining the most efficient workroom layout.

Air Movements↗

PubMedDate not supplied

Performance of deterministic workplace exposure assessment models for various contaminant source, air inlet, and exhaust locations.

Contaminant concentration estimates from simple models were compared with concentration fields obtained by computational fluid dynamic (CFD) simulations for various room and source configurations under steady-state conditions. Airflow and contaminant distributions in a 10 x 3 x 7-m room with a single contaminant source on a 1-m high table were simulated using CFD for steady, isothermal conditions. For a high wall jet inlet, simulations were performed for nine room air exhaust locations and eight source locations. For a ceiling diffuser inlet the impact of two exhaust locations and eight source locations were investigated. Because CFD treats determinants of contaminant transport explicitly and agreed well with experimental results, it was used as the standard for comparison. Parameters of the one- and two-zone completely mixed models (CM-1 and CM-2) and the uniform turbulent diffusivity model (UD) were determined from CFD simulation results. Concentration estimates from these were compared with CFD results in the breathing zone (BZ) plane (1.5 m above the floor) for the entire BZ, the source "near field," and the source "far field." In the near field the mean percentage difference between the model concentration estimates and the CFD results for all room configurations were -21.9, 32.3, and 126% for the CM-1, CM-2, and UD models, respectively, with standard deviations of 26.8, 111, and 103%. In the far field the mean percentage difference between the model estimates and CFD results were -4.8, -2.3, and -36.3%. The CM-1 model had generally the best performance for applications such as occupational epidemiology for the conditions and configurations studied. However, CM-1 tended to underestimate the near field concentration; thus, CM-2 was judged to be better in the near field when underestimation is undesirable, such as when determining compliance with occupational exposure limits. The agreement of CM-2 estimates with CFD results in the near field was more variable than that of the CM-1. The UD model performed poorly on average in both near and far fields, and the difficulty in accurately estimating the turbulent diffusivity presents a significant impediment to UD model use for exposure estimation.

Air Pollutants, Occupational↗

PubMedDate not supplied

Comparison of emission models with computational fluid dynamic simulation and a proposed improved model.

Understanding source behavior is important in controlling exposure to airborne contaminants. Industrial hygienists are often asked to infer emission information from room concentration data. This is not easily done, but models that make simplifying assumptions regarding contaminant transport are frequently used. The errors resulting from these assumptions are not yet well understood. This study compares emission estimates from the single-zone completely mixed (CM-1), two-zone completely mixed (CM-2), and uniform diffusivity (UD) models with the emissions set as boundary conditions in computational fluid dynamic (CFD) simulations of a workplace. The room airflow and concentration fields were computed using Fluent 4. These numerical experiments were factorial combinations of three source locations, five receptor locations, three dilution airflow rates, and two generation rate profiles, constant and time-varying. The aim was to compute plausible concentration fields, not to simulate exactly the processes in a real workroom. Thus, error is defined here as the difference between model and CFD predictions. For the steady-state case the UD model had the lowest error. When the source near-field contained the breathing zone receptor, the CM-2 model was applied. Then, in decreasing agreement with CFD were UD, CM-2, and CM-1. Averaging over all source and receptor locations (CM-2 applied for only one), in decreasing order of agreement with CFD were UD, CM-1, and CM-2. Source and receptor location had large effects on emission estimates using the CM-1 model and some effect using the UD model. A location-specific mixing factor (location factor) derived from steady-state concentration gradients was used to build a more accurate time-dependent emission model, CM-L. Total mass emitted from a time-varying source was modeled most accurately by CM-L, followed by CM-1 and CM-2.

Air Movements↗