A 3D Lagrangian particle model for direct plume gamma dose rate calculations.

A fully 3D Lagrangian particle model has been presented for calculating the direct gamma dose rates due to a radionuclide plume in the atmosphere. A continuous release of radionuclides into the atmosphere was simulated by liberating a series of puffs (each containing 100 Lagrangian particles). These puffs were released with a constant time lag between the successive puffs. The Lagrangian particle trajectories were tracked for about 25 h in a turbulent atmosphere, with a specified wind field. The atmosphere turbulent/stability characteristics like wind velocity fluctuations, eddy lifetime, etc, were obtained from the reported data in the published literature. For calculating the direct plume gamma dose rates, a point isotropic source formula has been used with appropriate attenuation and build-up factors for the air medium. Each Lagrangian particle represented a point source whose radioactive strength was calculated from the known release rate. The dose rates at ground due to the radionuclide plume were calculated by adding the contribution from each Lagrangian particle in the domain. The numerically calculated dose rates were compared with the numerical results reported in the literature. An excellent comparison was observed for downwind distances up to about 20 km. However, for distances exceeding 20 km, the numerical data were below the reported results for the Gaussian plume model. This discrepancy was due to the vertical wind shear. It is concluded that a Gaussian plume model can be used for the concentration calculations provided the lateral dispersion parameter, sigma(gamma), includes the effect of wind shear, for distances exceeding 20 km.     

Sporadic cases of community acquired legionnaires' disease: an ecological study to identify new sources of contamination

STUDY OBJECTIVE: To explore the relation between incidence of sporadic and community acquired legionnaires' disease and exposure to potentially contaminated industrial aerosols. DESIGN: Geographical ecological approach using the postcode as the statistical unit. A multivariate Poisson regression model was used to model the relation between exposure to industrial aerosols and legionnaires' disease. SETTING: Metropolitan France. MAIN RESULTS: More than 1000 sources of industrial exposure (aerosol and plume of smoke) were identified in 42 French departments. After adjusting for confounding factors, there was a statistically increased incidence of legionnaires' disease in postcodes with plume of smoke in comparison with postcodes without (RR=1.45, 95% CI=1.12 to 1.87), and in postcodes with more than one aerosol in comparison with postcodes without (RR=1.37, 95% CI=1.04 to 1.79). CONCLUSION: These findings highlight that any industrial systems generating water aerosols should be regarded as potential sources of contamination for legionnaires' disease.     

Dispersion of radionuclides released into a stable planetary boundary layer using a Monte Carlo model.

In this paper a Monte Carlo model for describing the atmospheric dispersion of radionuclides (represented by Lagrangian particles/neutral tracers) continuously released into a stable planetary boundary layer is presented. The effect of variation in release height and wind directional shear on plume dispersion is studied. The resultant plume concentration and dose rate at the ground is also calculated. The turbulent atmospheric parameters, like vertical profiles of fluctuating wind velocity components and eddy lifetime, were calculated using empirical relations for a stable atmosphere. The horizontal and vertical dispersion coefficients calculated by a numerical Lagrangian model are compared with the original and modified Pasquill-Gifford and Briggs empirical sigmas. The comparison shows that the Monte Carlo model can successfully predict dispersion in a stable atmosphere using the empirical turbulent parameters. The predicted ground concentration and dose rate contours indicate a significant increase in the affected area when wind shear is accounted for in the calculations.     

放射性释放源项反演模型的初步研究

目的 基于监测数据、高斯烟羽模型和优化算法,初步研究放射性释放源项反演模型.方法 通过比较几种优化算法的适用条件和性能,并对相同条件下不同算法源项反演计算结果的准确性进行比较验证.结果 通过对放射性释放源项反演模型初步研究,发现基于高斯烟羽的反演模型,采用最小二乘法优化后进行释放源项反演计算是可行的.该优化模型对于简单...     

An impact-effect mathematical model incorporating the influence of exposures to fluctuating concentrations in a dispersing plume of pollutant in the atmosphere.

The statistical properties of the impact or toxic load (pollutant concentration raised to an exponent and multiplied by exposure duration), obtained from fluctuating concentrations in a plume dispersing in the atmosphere, are investigated both analytically and experimentally. A general expression for the kth order moment of the impact is derived in terms of the k-time point joint moment of the nth power of the fluctuating plume concentration field. Special cases of this general relationship are treated explicitly: (i) a simple model for the ensemble-mean impact (or equivalently, the ensemble-mean impact ratio) is derived on the basic hypothesis that the higher moments of concentration can be adequately modelled using an exponential probability density function (PDF), and this hypothesis is shown to give results that agree remarkably well with an extensive new set of concentration fluctuation measurements; and (ii) a model for the integral time scale of the process obtained by raising the concentration to the nth power is formulated using Gifford's meandering plume model, and the latter is subsequently used to derive a simple expression for estimating the impact variance for all exposure times, given the mean and mean-square concentrations and the plume concentration integral time scale only. The results of this model for impact variance are favorably compared with some data from full-scale field experiments. The impact PDF is found to be reasonably well-characterized by a clipped-normal PDF for exposure times, t(e), of practical interest (e.g., t(e) approximately >5 s). The implications of these results, for determining the fraction of an exposed population that will experience a specified level of effect from a random impact arising from exposure to a fluctuating plume of pollutant, are discussed briefly.     

A comparison of pregnancy history recall and medical records. Implications for retrospective studies

Using data from the Diethylstilbestrol-Adenosis (DESAD) Project, a study of the effects of diethylstilbestrol (DES) exposure during fetal life, the authors compared prenatal records with obstetric history from mother's questionnaires completed 10 or more years after the birth of their daughters. Except for the history of hospitalization and trunk x-ray, no differences were observed in agreement (questionnaire compared with record) between the group of DES-exposed mothers identified through review of their prenatal records and the comparison group of mothers who were not exposed. The authors also compared data from mothers of DES-exposed daughters who initiated their own enrollment in the study (walk-ins and referrals). To obtain prenatal records for these women, physicians were contacted. They would usually supply drug exposure data but not the other obstetric history requested. Mothers of these walk-ins and referrals had slightly better agreement between questionnaire and records when compared with the two groups identified by review of prenatal records. In general, there was good to excellent agreement for all groups when mothers' recall of personal history (past miscarriage, past pregnancy, etc.) was compared with their medical records. However, for medical intervention such as drugs and x-rays, agreement was poor. Of the DES-exposed mothers identified through review of their prenatal records, 29% could not remember whether they took DES. An additional 8% said they did not take DES when it was recorded in their charts.     

Measured and modeled personal and environmental NO2 exposure

ABSTRACT: BACKGROUND: Measured or modeled levels of outdoor air pollution are being used as proxies for individual exposure in a growing number of epidemiological studies. We studied the accuracy of such approaches, in comparison with measured individual levels, and also combined modeled levels for each subject's workplace with the levels at their residence to investigate the influence of living and working in different places on individual exposure levels. METHODS: A GIS-based dispersion model and an emissions database were used to model concentrations of NO2 at the subject's residence. Modeled levels were then compared with measured levels of NO2. Personal exposure was also modeled based on levels of NO2 at the subject's residence in combination with levels of NO2 at their workplace during working hours. RESULTS: There was a good agreement between measured facade levels and modeled residential NO2 levels (rs = 0.8, p > 0.001); however, the agreement between measured and modeled outdoor levels and measured personal exposure was poor with overestimations at low levels and underestimation at high levels (rs = 0.5, p > 0.001 and rs = 0.4, p > 0.001) even when compensating for workplace location (rs = 0.4, p > 0.001). CONCLUSION: Modeling residential levels of NO2 proved to be a useful method of estimating facade concentrations. However, the agreement between outdoor levels (both modeled and measured) and personal exposure was, although significant, rather poor even when compensating for workplace location. These results indicate that personal exposure cannot be fully approximated by outdoor levels and that differences in personal activity patterns or household characteristics should be carefully considered when conducting exposure studies. This is an important finding that may help to correct substantial bias in epidemiological studies.     

Site-specific data confirm arsenic exposure predicted by the U.S. Environmental Protection Agency.

The EPA uses an exposure assessment model to estimate daily intake to chemicals of potential concern. At the Anaconda Superfund site in Montana, the EPA exposure assessment model was used to predict total and speciated urinary arsenic concentrations. Predicted concentrations were then compared to concentrations measured in children living near the site. When site-specific information on concentrations of arsenic in soil, interior dust, and diet, site-specific ingestion rates, and arsenic absorption rates were used, measured and predicted urinary arsenic concentrations were in reasonable agreement. The central tendency exposure assessment model successfully described the measured urinary arsenic concentration for the majority of children at the site. The reasonable maximum exposure assessment model successfully identified the uppermost exposed population. While the agreement between measured and predicted urinary arsenic is good, it is not exact. The variables that were identified which influenced agreement included soil and dust sample collection methodology, daily urinary volume, soil ingestion rate, and the ability to define the exposure unit. The concentration of arsenic in food affected agreement between measured and predicted total urinary arsenic, but was not considered when comparing measured and predicted speciated urinary arsenic. Speciated urinary arsenic is the recommended biomarker for recent inorganic arsenic exposure. By using site-specific data in the exposure assessment model, predicted risks from exposure to arsenic were less than predicted risks would have been if the EPA's default values had been used in the exposure assessment model. This difference resulted in reduced magnitude and cost of remediation while still protecting human health.     

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.     

Modeling of the dispersion of depleted uranium aerosol

Depleted uranium is a low-cost radioactive material that, in addition to other applications, is used by the military in kinetic energy weapons against armored vehicles. During the Gulf and Balkan conflicts concern has been raised about the potential health hazards arising from the toxic and radioactive material released. The aerosol produced during impact and combustion of depleted uranium munitions can potentially contaminate wide areas around the impact sites or can be inhaled by civilians and military personnel. Attempts to estimate the extent and magnitude of the dispersion were until now performed by complex modeling tools employing unclear assumptions and input parameters of high uncertainty. An analytical puff model accommodating diffusion with simultaneous deposition is developed, which can provide a reasonable estimation of the dispersion of the released depleted uranium aerosol. Furthermore, the period of the exposure for a given point downwind from the release can be estimated (as opposed to when using a plume model). The main result is that the depleted uranium mass is deposited very close to the release point. The deposition flux at a couple of kilometers from the release point is more than one order of magnitude lower than the one a few meters near the release point. The effects due to uncertainties in the key input variables are addressed. The most influential parameters are found to be atmospheric stability, height of release, and wind speed, whereas aerosol size distribution is less significant. The output from the analytical model developed was tested against the numerical model RPM-AERO. Results display satisfactory agreement between the two models.     

Calculation of immersion doses from external exposure to a plume of radioactive material

The immersion doses from external exposure to a Gaussian plume of noble gases accidentally released into the atmosphere have been calculated. A numerical integration procedure employing Gauss-Legendre of 64th order has been used. The numerical procedure allows calculating the dose rate at any downwind horizontal or vertical distance. The dose rates were calculated using various forms of gamma dose build-up factors, including Linear, Berger and Geometric Progression (GP). The GP form, having an extraordinarily precise formulation, is a favored choice because the build-up factor levels off for large distances and does not increase exponentially as does the Berger form. The Linear form much under predicts the build-up and subsequently the dose rates for large distances from the source. The dose predictions using a simple uniform cloud model (that does not use any form of build-up factor) is also presented for comparison purposes. The comparison of dose rates with the already reported results indicated that the numerical procedure could be used for dose calculations from a Gaussian plume for all downwind and crosswind distances. The comparison of dose rates obtained using different forms of the build-up factors indicated that the Geometric Progression form was a favored choice and has a wider range of applicability as compared to the Linear or Berger form. The simple uniform cloud model for dose calculations is only suitable for plume centerline doses and should be used with caution for off-center distances.     

Experimental evaluation of an environmental CAT scanning system for mapping chemicals in air in real-time

An innovative method is being developed which creates real-time, two-dimensional maps of chemical concentrations in air for environmental and occupational applications. This method, we call environmental CAT scanning, combines the real-time measuring technique of open-path Fourier transform infrared spectroscopy with the mapping capabilities of computed tomography to produce accurate spatial and temporal information about contaminant concentrations and dispersion patterns. With this system, a network of open-path measurements is obtained over an area; measurements are then processed using a tomographic algorithm to reconstruct the concentrations. This article describes a thorough experimental evaluation of an environmental CAT scanning system using a field-ready prototype system deployed in a room-size exposure chamber; point sample measurements were taken simultaneously in the chamber along with the CAT measurements. Twenty-eight experiments were performed using single or multiple plumes of a tracer gas in the chamber. Tomographic maps were compared with the point sample reference maps to evaluate the CAT scanning system for accuracy of concentration measurement and plume location. Quantitative agreement was very good; concentrations reconstructed with the tomographic maps agreed to within 17 percent of the point sample maps, and plume locations were reconstructed to within six inches of the plumes in the point sample maps. This technique shows real promise as a rapid and accurate method for mapping chemicals over large areas.     

Reliability of a semi-quantitative method for dermal exposure assessment (DREAM)

Valid and reliable semi-quantitative dermal exposure assessment methods for epidemiological research and for occupational hygiene practice, applicable for different chemical agents, are practically nonexistent. The aim of this study was to assess the reliability of a recently developed semi-quantitative dermal exposure assessment method (DREAM) by (i) studying inter-observer agreement, (ii) assessing the effect of individual observers on dermal exposure estimates for different tasks, and (iii) comparing inter-observer agreement for ranking of body parts according to their exposure level. Four studies were performed in which a total of 29 observers (mainly occupational hygienists) were asked to fill in DREAM while performing side-by-side observations for different tasks, comprising dermal exposures to liquids, solids, and vapors. Intra-class correlation coefficients ranged from 0.68 to 0.87 for total dermal exposure estimates, indicating good to excellent inter-observer agreement. The effects of individual observers on task estimates were estimated using a linear mixed effect model with logged DREAM estimates as explanatory variable; "task", "company/department", and the interaction of "task" and "company/department" as fixed effects; and "observer" as a random effect. Geometric mean (GM) dermal exposure estimates for different tasks were estimated by taking the exponent of the predicted betas for the tasks. By taking the exponent of the predicted observer's intercept (exp(omega i)), a multiplier (M(O)) was estimated for each observer. The effects of individual observers on task estimates were relatively small, as the maximum predicted mean observers' multiplier was only a factor 2, while predicted GMs of dermal exposure estimates for tasks ranged from 0 to 1226, and none of the predicted individual observers' multipliers differed significantly from 1 (t-test alpha = 0.05). Inter-observer agreement for ranking of dermal exposure of nine body parts was moderate to good, as median values of Spearman correlation coefficients for pairs of observers ranged from 0.29 to 0.93. DREAM provides reproducible results for a broad range of tasks with dermal exposures to liquids, solids, as well as vapors. DREAM appears to offer a useful advance for estimations of dermal exposure both for epidemiological research and for occupational hygiene practice.     

Ethnic differences in biological monitoring of several organic solvents II. A simulation study with a physiologically based pharmacokinetic model

To improve the reliability of biological monitoring and the development of biological limit values, ethnic differences in the biological monitoring of several organic solvents were studied in Orientals and Caucasians. Six Caucasian and six Oriental volunteers were exposed to each organic solvent in an exposure chamber for 6 h at rest. The exposure concentrations were 50 ppm for perchloroethylene, 50 ppm for styrene, and 100 ppm for m-xylene, respectively. Experimental results were compared with simulation results of a physiologically based pharmacokinetic (PB-PK) model. Differences between Orientals and Caucasians under occupational exposure were also estimated by extrapolation. The simulation results obtained for the Caucasian group showed good agreement with the experimental results. However, the Oriental group did not show good agreement when the same metabolic parameters values applied to Caucasians were used in the PB-PK model. By modification of the metabolic parameters it was possible to get a good fit between the model and the results of the Oriental group. The simulation results obtained for occupational exposure also showed differences in biological levels between the two ethnic groups. Implications of these differences between experimental and simulation results are discussed in the context of the application of biological monitoring and in the development of biological limit values. Received: 14 October 1996 / Accepted: 29 November 1996     

Correcting for exposure measurement error in a reanalysis of lung cancer mortality for the Colorado Plateau Uranium Miners cohort.

The exposure estimates used to date for the analysis of lung cancer mortality in the Colorado Plateau Uranium Miners cohort were developed from radon progeny measurements taken in mines beginning in 1951. Since uranium miners were often exposed over long periods of time and since mines were not continuously monitored, much extrapolation and/or interpolation of measured dose-rates was needed in order to develop estimates of exposure for each of the miners in the cohort. We have recently re-examined the interpolation scheme used to create the histories in the light of the fit of a statistical model for the radon progeny measurements taken in mines within the Plateau, and we have computed revised exposure estimates for the large majority of miners in the cohort. This report describes the use of these new model-based revised exposure estimates in the analysis of lung cancer mortality, using follow-up data current through 1990. Specific issues addressed here are (1) the strength of the association between exposure and risk of lung cancer mortality; (2) effects of attained age and time since exposure upon risk of lung cancer mortality; and (3) exposure-rate effects upon risk. Results using the revised exposure estimates are compared to those obtained fitting the same models using the original Public Health Service (PHS) exposure estimates. We found evidence that the new exposure histories provide a better fit to the lung cancer mortality data than do the histories based upon the original PHS dose-rate estimates. In general, the new results show a stronger overall relationship (larger slope estimate) between lung cancer mortality and exposure per unit exposure compared to those obtained with the original estimates, while displaying similar age at exposure and time since exposure effects. In the reanalysis the impact of low dose-rate exposure is found to be relatively unchanged before and after exposure error correction, while the estimate of the effect of high dose-rate exposure is considerably increased. Even after applying our measurement error corrections, evidence of inverse dose-rate effects is found, since the estimate of the impact of high dose-rate exposure is still below that of the low dose-rates. The magnitude and statistical significance, however, of the dose-rate effect estimates are diminished when fit using the revised exposure estimates.     

Morbidity among employees engaged in the manufacture or formulation of chlorpyrifos.

The prevalence of selected illnesses and symptoms during 1977-85 was compared between 175 employees potentially exposed to the organophosphate insecticide chlorpyrifos and 335 matched controls with no history of exposure to organophosphates. Subjects were subdivided into three exposure intensity groups on the basis of job title and air monitoring data for dose response testing. This classification scheme was shown roughly to correlate with plasma cholinesterase inhibition in the workers. No statistically significant differences in illness or prevalence of symptoms were observed between the exposed and unexposed groups or among the three exposure subgroups. Potentially exposed employees did report symptoms of dizziness and of malaise and fatigue relatively more often than subjects from the comparison group; however, further analyses by exposure level, process area, or time did not support a relation with exposure. No cases of peripheral neuropathy were seen among the exposed workers. Although the sample size was small and the statistical power limited, the cumulative exposures likely to have been experienced by this workforce exceed those to be expected for individuals using the product as recommended. The absence of exposure related adverse effects, including neurological impairment, is reassuring.     

Morbidity among employees engaged in the manufacture or formulation of chlorpyrifos

The prevalence of selected illnesses and symptoms during 1977-85 was compared between 175 employees potentially exposed to the organophosphate insecticide chlorpyrifos and 335 matched controls with no history of exposure to organophosphates. Subjects were subdivided into three exposure intensity groups on the basis of job title and air monitoring data for dose response testing. This classification scheme was shown roughly to correlate with plasma cholinesterase inhibition in the workers. No statistically significant differences in illness or prevalence of symptoms were observed between the exposed and unexposed groups or among the three exposure subgroups. Potentially exposed employees did report symptoms of dizziness and of malaise and fatigue relatively more often than subjects from the comparison group; however, further analyses by exposure level, process area, or time did not support a relation with exposure. No cases of peripheral neuropathy were seen among the exposed workers. Although the sample size was small and the statistical power limited, the cumulative exposures likely to have been experienced by this workforce exceed those to be expected for individuals using the product as recommended. The absence of exposure related adverse effects, including neurological impairment, is reassuring.     

Pre-natal blood lead levels and learning difficulties in children: an analysis of non-randomly missing categorical data.

This paper presents an analysis of categorical variables subject to non-response. We incorporate the incomplete data into the analysis by modelling the distribution of the variables of interest and the non-response mechanism. We discuss issues of model selection and interpretation and the effect of discarding incomplete observations. In addition, we describe how to perform all of the computations with standard statistical software. We discuss the problem of incomplete categorical data within the context of a study of the effect of lead exposure on learning difficulties in children. In this study, many of the children are not observed on some of the variables of interest. It is particularly important in this study to incorporate the incomplete data, since there is evidence that non-response is related to the variables of interest. We reach different conclusions when we incorporate the incomplete data into the analysis than we reach when we discard the incomplete data. We also examine the sensitivity of our conclusions to the choice of a model for the non-response mechanism.     

The Precautionary Principle and statistical approaches to uncertainty

The central challenge from the Precautionary Principle to statistical methodology is to help delineate (preferably quantitatively) the possibility that some exposure is hazardous, even in cases where this is not established beyond reasonable doubt. The classical approach to hypothesis testing is unhelpful, because lack of significance can be due either to uninformative data or to genuine lack of effect (the Type II error problem). Its inversion, bioequivalence testing, might sometimes be a model for the Precautionary Principle in its ability to "prove the null hypothesis". Current procedures for setting safe exposure levels are essentially derived from these classical statistical ideas, and we outline how uncertainties in the exposure and response measurements affect the no observed adverse effect level, the Benchmark approach and the "Hockey Stick" model. A particular problem concerns model uncertainty: usually these procedures assume that the class of models describing dose/response is known with certainty; this assumption is, however, often violated, perhaps particularly often when epidemiological data form the source of the risk assessment, and regulatory authorities have occasionally resorted to some average based on competing models. The recent methodology of the Bayesian model averaging might be a systematic version of this, but is this an arena for the Precautionary Principle to come into play?     

Comparison of average estimated metabolic rates for styrene in previously exposed and unexposed groups with pharmacokinetic modelling.

OBJECTIVE: To understand whether previous styrene exposure increases the human liver's ability to convert styrene into styrene oxide. METHODS: The hypothesis was tested that the average linear metabolic rate constant kappa was the same in both exposed and unexposed groups, when the exposed group comprised people with a history of styrene exposure and the unexposed group had no exposure. In an experimental chamber, these two groups of subjects were exposed to a concentration of 80 ppm styrene for two hours. A three compartment pharmacokinetic model was used to define kappa. Based on large sample theory, the comparison of estimated mean values of kappa in the exposed and unexposed groups was shown to be equivalent to a comparison of the estimated mean values of the hepatic clearance X in the two groups. A method was developed to estimate X for each subject in both groups from the subject's height, weight, and estimated asymptotic styrene decay constant alpha. Here, alpha was estimated individually from observed blood concentrations over time when sufficient time had elapsed after the controlled exposure. RESULTS: The proposed methodology of comparing the estimated mean values of kappa in exposed and unexposed groups reduced the number of specific physiological variables involved to three, all of which were estimable from data based on simple direct measurements. In contrast, other methods based on pharmacokinetic models usually involved many variables that were non-estimable on an individual basis. Consequently, statistical comparisons were impossible. These methods were applied to analyse previously published data on the time course of styrene concentrations in arterial blood of subjects in both exposed and unexposed groups. A Wilcoxon non-parametric rank sum test with the individually estimated X values was used, and no significant difference in the means of X in the two groups was found. CONCLUSION: The linear metabolic rate constant kappa for humans is probably not altered by previous exposure to styrene. This result is in agreement with some experimental studies on animals. However, in the data analysis, it was noted that the number of subjects in each group was small (6-7) and that the styrene concentration data did not exactly reflect true behaviour of asymptotic decay. Further studies are still needed to draw more definitive conclusions.