Modeling an irritant gas plume for epidemiologic study.

Plume dispersion modeling systems are often used in assessing human exposures to chemical hazards for epidemiologic study. We modeled the 2005 Graniteville, South Carolina, 54,915 kg railcar chlorine release using both the Areal Locations of Hazardous Atmospheres and Hazard Prediction and Assessment Capability (HPAC) plume modeling systems. We estimated the release rate by an engineering analysis combining semi-quantitative observations and fundamental physical principles. The use of regional meteorological conditions was validated by comparing concentration estimates generated by two source-location weather data-sets. The HPAC model estimated a chlorine plume with 20 ppm outdoor concentrations up to 7 km downwind and 0.25 km upwind/downgrade. A comparative analysis of our two models showed that HPAC was the best candidate for use as a model system on which epidemiologic studies could be based after further model validation. Further validation studies are needed before individual exposure estimates can be reliable and the chlorine plume more definitively modeled.

Exposure models for the prior distribution in bayesian decision analysis for occupational hygiene decision making.

This study introduces two semi-quantitative methods, Structured Subjective Assessment (SSA) and Control of Substances Hazardous to Health (COSHH) Essentials, in conjunction with two-dimensional Monte Carlo simulations for determining prior probabilities. Prior distribution using expert judgment was included for comparison. Practical applications of the proposed methods were demonstrated using personal exposure measurements of isoamyl acetate in an electronics manufacturing facility and of isopropanol in a printing shop. Applicability of these methods in real workplaces was discussed based on the advantages and disadvantages of each method. Although these methods could not be completely independent of expert judgments, this study demonstrated a methodological improvement in the estimation of the prior distribution for the Bayesian decision analysis tool. The proposed methods provide a logical basis for the decision process by considering determinants of worker exposure.

Characterization and control of the microbial community affiliated with copper or aluminum heat exchangers of HVAC systems.

Microbial growth in heating ventilation and air-conditioning (HVAC) systems with the subsequent contamination of indoor air is of increasing concern. Microbes and the subsequent biofilms grow easily within heat exchangers. A comparative study where heat exchangers fabricated from antimicrobial copper were evaluated for their ability to limit microbial growth was conducted using a full-scale HVAC system under conditions of normal flow rates using single-pass outside air. Resident bacterial and fungal populations were quantitatively assessed by removing triplicate sets of coupons from each exchanger commencing the fourth week after their installation for the next 30 weeks. The intrinsic biofilm associated with each coupon was extracted and characterized using selective and differential media. The predominant organisms isolated from aluminum exchangers were species of Methylobacterium of which at least three colony morphologies and 11 distinct PFGE patterns we found; of the few bacteria isolated from the copper exchangers, the majority were species of Bacillus. The concentrations and type of bacteria recovered from the control, aluminum, exchangers were found to be dependent on the type of plating media used and were 11,411-47,257 CFU cm(-2) per coupon surface. The concentration of fungi was found to average 378 CFU cm(-2). Significantly lower concentrations of bacteria, 3 CFU cm(-2), and fungi, 1 CFU cm(-2), were recovered from copper exchangers regardless of the plating media used. Commonly used aluminum heat exchangers developed stable, mixed, bacterial/fungal biofilms in excess of 47,000 organisms per cm(2) within 4 weeks of operation, whereas the antimicrobial properties of metallic copper were able to limit the microbial load affiliated with the copper heat exchangers to levels 99.97 % lower during the same time period.

Deriving realistic source boundary conditions for a CFD simulation of concentrations in workroom air.

Computational fluid dynamics (CFD) is used increasingly to simulate the distribution of airborne contaminants in enclosed spaces for exposure assessment and control, but the importance of realistic boundary conditions is often not fully appreciated. In a workroom for manufacturing capacitors, full-shift samples for isoamyl acetate (IAA) were collected for 3 days at 16 locations, and velocities were measured at supply grills and at various points near the source. Then, velocity and concentration fields were simulated by 3-dimensional steady-state CFD using 295K tetrahedral cells, the k-ε turbulence model, standard wall function, and convergence criteria of 10(-6) for all scalars. Here, we demonstrate the need to represent boundary conditions accurately, especially emission characteristics at the contaminant source, and to obtain good agreement between observations and CFD results. Emission rates for each day were determined from six concentrations measured in the near field and one upwind using an IAA mass balance. The emission was initially represented as undiluted IAA vapor, but the concentrations estimated using CFD differed greatly from the measured concentrations. A second set of simulations was performed using the same IAA emission rates but a more realistic representation of the source. This yielded good agreement with measured values. Paying particular attention to the region with highest worker exposure potential-within 1.3 m of the source center-the air speed and IAA concentrations estimated by CFD were not significantly different from the measured values (P = 0.92 and P = 0.67, respectively). Thus, careful consideration of source boundary conditions greatly improved agreement with the measured values.

Association between barracks type and acute respiratory infection in a gender integrated Army basic combat training population.

BACKGROUND: Acute respiratory infections (ARIs) are the leading cause of acute morbidity and lost work time in the United States. Few studies have looked at building design and transmission of ARIs. OBJECTIVES: This study explores the association of ventilation design, room occupancy numbers, and training week with ARI rates in Army Basic Combat Training barracks. METHODS: This observational study captured the overall incidence of ARI in a cohort of 16,258 individuals attending basic combat training at Fort Jackson, South Carolina. RESULTS: ARI risk was higher among trainees living in the 60-person room barracks compared with those living in 8-person rooms, which increased rapidly for the first few weeks of training and then declined to baseline. CONCLUSIONS: Findings support direct contact as primary ARI transmission mode in this study population based on observed lower ARI risk in smaller room barracks and similar risk in large room barracks despite heating, ventilation, and air conditioning system variability.

Emission and dispersal of antibiotic resistance genes through bioaerosols generated during the treatment of municipal sewage.

Wastewater treatment plants act as socio-ecological couplers through the concentration, treatment, and subsequent environmental release of sewage collected from surrounding communities and are often considered hotspots for antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs). While studies have identified the release of ARB/ARGs in treated liquid sewage, little is known about potential dispersal through wastewater bioaerosol emissions. The aim of this study was to better define the contribution of WWTP bioaerosols to potential environmental distribution of ARB/ARGs. Bioaerosols were collected immediately upwind and downwind from the aeration tanks of a municipal wastewater treatment plant and liquid sludge samples were obtained from the aeration tanks. From the bioaerosol and liquid samples, qPCR assays identified 44 ARGs that confer resistance to a wide range of antibiotics. Comparison of the ARG profiles across samples showed that the downwind bioaerosol profile was 68% similar to the profile found in liquid sludge samples. Community 16S rRNA gene sequencing also showed that downwind bioaerosols had similar taxonomic profiles as those generated from liquid sludge while the upwind profiles showed a distinct difference. Preliminary ARG dispersion modeling estimated an ARG emission rate of ~10,620 genes per hour from the liquid sludge and indicated that the bioaerosols have the potential to be carried kilometers away from the WWTP source based on wind speed. The overall results from this study suggest that bioaerosols generated during WWTP processes can aid in the emission and dispersal of bacteria and ARGs, resulting in a possible route of human exposure and deposition into surrounding environments.

Estimation of required monitoring time for obtaining validation data in enclosed spaces.

Methods for estimating airborne contaminant concentrations at specific locations within enclosed spaces, such as mathematical models and computational fluid dynamics (CFD), often are validated against directly measured concentrations. However, concentration variation with time introduces uncertainty into the measured concentration. Failure to determine monitoring time requirements can lead to errors in quantifying representative concentrations, which are likely to be attributed to errors in the method being validated. In the current study, to obtain the representative concentrations at multiple locations with a direct reading instrument, we used the standard deviation ratio (SDR) method to determine the required minimum monitoring time within a specified precision limit. To demonstrate the use of the SDR approach in constructing precision confidence intervals, tracer gas concentrations at nine sampling locations in an experimental room were measured to obtain population parameters. Three flow rates of 0.9, 3.3 and 5.5 m(3) min(-1) were employed and contaminant concentrations were measured using a photoionization analyser. Monitoring time requirements varied substantially with location within the room and were strongly dependent upon the flow rate of air through the room. The proposed method would be very useful for industrial hygienists and indoor air researchers who sometimes need to obtain several hundred measured concentrations for validation purposes or to perform tests under repeatable conditions in enclosed spaces. This study also showed that the proposed method can be used to devise efficient indoor monitoring strategies.

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.

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.

The effect of worker's location, orientation, and activity on exposure.

The impact of a worker's location, orientation, and activity was studied in an experimental room (2.86 m x 2.35 m x 2.86 m) at known flow rates of 5.5 m(3)/min and 3.3 m(3)/min. A person in the room, wearing a full-facepiece, air-supplied respirator represented a worker. Propylene tracer gas was emitted at a constant rate from a 1-m pedestal at the center of the room and a continuous air sample was drawn from a point midway between the worker's mouth and nose. Breathing zone concentration (BZC) was monitored at 12 worker locations within the room for a stationary worker. At each location, BZCs were measured separately for four worker orientations: east, west, south, and north. BZCs of a walking worker were also monitored along the path defined by the 12 worker locations used in the stationary experiments. In a separate set of experiments, area concentration was monitored to see whether the worker's activity disturbed the contaminant concentrations at a fixed sampling point located behind the source looking from the direction of air inlet (location: 1.34 m, 1.20 m, 0.45 m). The following average differences in BZC over the 12 fixed locations were observed: 43% higher for near-field than for far-field locations; 20% higher when the worker was facing the source than when facing away (p-values for all four conditions: < 0.033), and 30% higher for a moving worker than for a stationary worker (p-values for all four conditions: < 0.01). When the worker was walking, the concentration at the fixed area sampling point was generally lower than the area concentration when the worker was absent or stationary in the room, possibly due to greater mixing of room air by the worker's movement. Because a worker's activities may be irregular and complicated, incorporating them as parameters in mathematical models is often not feasible. Instead, these findings may be used to assess uncertainty or adjust exposure estimates from simple models.

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.

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.

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.

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.

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.

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.