bluuebunny/crossref_metadata_2025 huggingface dataset:
“Down and Dirty:” The Use and Abuse of Public Trust in Risk Communication
Authors: Leiss William
Published: May 2006

Many recent contributions to risk communication research stress the importance of the element of “trust” in the process of successful communication. This paper uses that theme in considering risk communication within the context of seeking consensus on matters of health and environmental risk controversies through stakeholder negotiation. It suggests that there are very good reasons, based on historical experience, for the parties to mistrust each other deeply in such settings. For example there is abundant evidence involving episodes in which risk promoters have concealed or ignored relevant risk data or simply have sought to advance their own interests by selective use of such data. These well‐established practices compound the difficulties other stakeholders face, in all such negotiation, by virtue of the inescapable uncertainties (as well as absence of needed data) inherent in risk assessments. These factors encourage the participants to treat such negotiations as poker games in which bluffing, raising the ante, and calling the perceived bluffs of others are matters of survival. In the end we should recognize the genuine dilemmas that citizens face in trying to figure out who and what to believe in making sensible decisions among the range of risks, benefits, and tradeoffs that confront us.
Exposure‐Response Functions for Health Effects of Air Pollutants Based on Epidemiological Findings
Authors: Aunan Kristin
Published: May 2006

Quantitative knowledge about health damage due to air pollution is an important element in analyses of cost‐effective abatement strategies, and is also essential for setting Air Quality Standards. Epidemiological studies, in spite of the numerous problems connected to them, provide a reasonable basis for exposure‐response functions in this context. On the basis of a literature review, exposure‐response functions that relate ambient air pollutant concentrations to the frequency of various health effects are recommended in this paper. The following end‐points were examined: Acute and chronic respiratory symptoms in children and adults, crude mortality, and lung cancer incidence. The effects are attributed to one indicator component, which in most cases is particles. A calculation procedure is suggested which makes it possible to estimate excess annual symptom‐days for short‐term effects using the annual average concentration.
Hybrid Processing of Stochastic and Subjective Uncertainty Data
Authors: Cooper J. Arlin , Ferson Scott , Ginzburg Lev
Published: May 2006

Uncertainty analyses typically recognize separate stochastic and subjective sources of uncertainty, but do not systematically combine the two, although a large amount of data used in analyses is partly stochastic and partly subjective. We have developed methodology for mathematically combining stochastic and subjective sources of data uncertainty, based on new “hybrid number” approaches. The methodology can be utilized in conjunction with various traditional techniques, such as PRA (probabilistic risk assessment) and risk analysis decision support. Hybrid numbers have been previously examined as a potential method to represent combinations of stochastic and subjective information, but mathematical processing has been impeded by the requirements inherent in the structure of the numbers, e.g., there was no known way to multiply hybrids. In this paper, we will demonstrate methods for calculating with hybrid numbers that avoid the difficulties. By formulating a hybrid number as a probability distribution that is only fuzzily known, or alternatively as a random distribution of fuzzy numbers, methods are demonstrated for the full suite of arithmetic operations, permitting complex mathematical calculations. It will be shown how information about relative subjectivity (the ratio of subjective to stochastic knowledge about a particular datum) can be incorporated. Techniques are also developed for conveying uncertainty information visually, so that the stochastic and subjective components of the uncertainty, as well as the ratio of knowledge about the two, are readily apparent. The techniques demonstrated have the capability to process uncertainty information for independent, uncorrelated data, and for some types of dependent and correlated data. Example applications are suggested, illustrative problems are shown, and graphical results are given.
Public Perceptions of Everyday Food Hazards: A Psychometric Study
Authors: Fife‐Schaw Chris , Rowe Gene
Published: May 2006

In this paper, we discuss the conduct and results of a study aimed at eliciting public perceptions of food‐related hazards. This study employs the psychometric approach of Paul Slovic and colleagues and aims to extend the recent work of Sparks and Shepherd(1) on defining the primary dimensions of food‐related risk perceptions. The study surveyed a nationally representative sample of the general public (respondents = 293; adjusted response rate = 30.1%). Respondents provided ratings on subsets of 22 potential food hazards (e.g., food irradiation and presence of listeria) on a total of 19 risk characteristics (e.g., “perceived severity of risk” and “adequacy of governmental regulations”). In spite of the use of a number of new characteristics and food hazards, Principal Components Analysis revealed a broadly similar factor structure to that obtained by Sparks and Shepherd,(1) suggesting the generalizability of the key dimensions (concerning the severity and awareness of hazards). Interestingly, the positioning in the factor space of potential hazards about which little was generally known (e.g., campylobacter) as being serious and in need of regulation, may suggest a possible “starting position” in the perception of new hazards that have not previously been the subject of risk communications.
Application of a Biologically‐Based RFD Estimation Method to Tetrachlorodibenzo‐P‐Dioxin (TCDD) Mediated Immune Suppression and Enzyme Induction
Authors: McGrath Lynne Fahey , Georgopoulos Panos , Gallo Michael A.
Published: May 2006

The current methods for a reference dose (RfD) determination can be enhanced through the use of biologically‐based dose‐response analysis. Methods developed here utilizes information from tetrachlorodibenzo‐p‐dioxin (TCDD) to focus on noncancer endpoints, specifically TCDD mediated immune system alterations and enzyme induction. Dose‐response analysis, using the Sigmoid‐Emax (EMAX) function, is applied to multiple studies to determine consistency of response. Through the use of multiple studies and statistical comparison of parameter estimates, it was demonstrated that the slope estimates across studies were very consistent. This adds confidence to the subsequent effect dose estimates. This study also compares traditional methods of risk assessment such as the NOAEL/safety factor to a modified benchmark dose approach which is introduced here. Confidence in the estimation of an effect dose (ED10) was improved through the use of multiple datasets. This is key to adding confidence to the benchmark dose estimates. In addition, the Sigmoid‐Emax function when applied to dose‐response data using nonlinear regression analysis provides a significantly improved fit to data increasing confidence in parameter estimates which subsequently improve effect dose estimates.
Cardiac Sensitization Thresholds of Halon Replacement Chemicals Predicted in Humans by Physiologically‐Based Pharmacokinetic Modeling
Authors: Vinegar Allen , Jepson Gary W.
Published: May 2006

Human exposure to halons and halon replacement chemicals is often regulated on the basis of cardiac sensitization potential. The dose‐response data obtained from animal testing are used to determine the no observable adverse effect level (NOAEL) and lowest observable adverse effect level (LOAEL) values. This approach alone does not provide the information necessary to evaluate the cardiac sensitization potential for the chemical of interest under a variety of exposure concentrations and durations. In order to provide a tool for decision‐makers and regulators tasked with setting exposure guidelines for halon replacement chemicals, a quantitative approach was established which allowed exposures to be assessed in terms of the chemical concentrations in blood during the exposure. A physiologically‐based pharmacokinetic (PBPK) model was used to simulate blood concentrations of Halon 1301 (bromotrifluoromethane, CF3Br), HFC‐125 (pentafluoroethane, CHF2CF3), HFC‐227ea (heptafluoropropane, CF3CHFCF3), HCFC‐123 (dichlorotrifluoroethane, CHCl2CF3), and CF3I (trifluoroiodomethane) during inhalation exposures. This work demonstrates a quantitative approach for use in linking chemical inhalation exposures to the levels of chemical in blood achieved during the exposure.
Plausible Upper Bounds: Are Their Sums Plausible?1
Authors: Cogliano Vincent James
Published: May 2006

Quantitative cancer risk assessments are typically expressed as plausible upper bounds rather than estimates of central tendency. In analyses involving several carcinogens, these upper bounds are often summed to estimate overall risk. This begs the question of whether a sum of upper bounds is itself a plausible estimate of overall risk. This question can be asked in two ways: whether the sum yields an improbable estimate of overall risk (that is, is it only remotely possible for the true sum of risks to match the sum of upper bounds), or whether the sum gives a misleading estimate (that is, is the true sum of risks likely to be very different from the sum of upper bounds). Analysis of four case studies shows that as the number of risk estimates increases, their sum becomes increasingly improbable, but not misleading. Though the overall risk depends on the independence, additivity, and number of risk estimates, as well as the shapes of the underlying risk distributions, sums of upper bounds provide useful information about the overall risk and can be adjusted downward to give a more plausible [perhaps probable] upper bound, or even a central estimate of overall risk.
On the Effect of Probability Distributions of Input Variables in Public Health Risk Assessment
Authors: Hamed Maged M. , Bedient Philip B.
Published: May 2006

A central part of probabilistic public health risk assessment is the selection of probability distributions for the uncertain input variables. In this paper, we apply the first‐order reliability method (FORM)(1–3) as a probabilistic tool to assess the effect of probability distributions of the input random variables on the probability that risk exceeds a threshold level (termed the probability of failure) and on the relevant probabilistic sensitivities. The analysis was applied to a case study given by Thompson et al.(4) on cancer risk caused by the ingestion of benzene contaminated soil. Normal, lognormal, and uniform distributions were used in the analysis. The results show that the selection of a probability distribution function for the uncertain variables in this case study had a moderate impact on the probability that values would fall above a given threshold risk when the threshold risk is at the 50th percentile of the original distribution given by Thompson et al.(4) The impact was much greater when the threshold risk level was at the 95th percentile. The impact on uncertainty sensitivity, however, showed a reversed trend, where the impact was more appreciable for the 50th percentile of the original distribution of risk given by Thompson et al.4 than for the 95th percentile. Nevertheless, the choice of distribution shape did not alter the order of probabilistic sensitivity of the basic uncertain variables.
Computer Simulation of Clonal Growth Cancer Models. I. Parameter Estimation Using an Iterative Absolute Bisection Algorithm
Authors: Kramer David A. , Conolly Rory B.
Published: May 2006

Quantitative models of the relationship between exposure to chemical carcinogens and carcinogenic response are useful for hypothesis evaluation and risk assessment. The degree to which such models accurately depict the underlying biology is often a function of the need for mathematical tractability. When closed‐form expressions are used, the need for tractability may significantly limit their complexity. This problem can be minimized by using numerical computer simulation methods to solve the model, thereby allowing more complex and realistic descriptions of the biology to be used. Unfortunately, formal methods of parameter estimation for numerical models are not as well developed as they are for analytical models. In this report, we develop a formal parameter estimation routine and apply it to a numerical clonal growth simulation (CGS) model of the growth of preneoplastic lesions consisting of initiated cells. An iterative bisection algorithm was used to estimate parameters from time‐course data on the number of initiated cells and the number of clones of these cells. The algorithm successfully estimated parameter values to give a best fit to the observed dataset and was robust vis‐à‐vis starting values of the parameters. Furthermore, the number of data points to which the model was fit, the number of stochastic repetitions and other variables were examined with respect to their effects on the parameter estimates. This algorithm facilitates the application of CGS models for hypothesis evaluation and risk assessment by ensuring uniformity and reproducibility of parameter estimates.
Multimedia Benchmarking Analysis for Three Risk Assessment Models: RESRAD, MMSOILS, and MEPAS
Authors: Mills William B. , Cheng J. J. , Droppo James G. , Faillace Ernest R. , Gnanapragasam Emmanuel K. , Johns Robert A. , Laniak Gerard F. , Lew Christine S. , Strenge Dennis L. , Sutherland Jonna F. , Whelan Gene , Yu Charley
Published: May 2006

This paper is one in a series that describes results of a benchmarking analysis initiated by the Department of Energy (DOE) and the United States Environmental Protection Agency (EPA). An overview of the study is provided in a companion paper by Laniaket al.presented in this journal issue. The three models used in the study—RESRAD (DOE), MMSOILS (EPA), and MEPAS (DOE)—represent analytically‐based tools that are used by the respective agencies for performing human exposure and health risk assessments. Both single media and multimedia benchmarking scenarios were developed and executed. In this paper, the multimedia scenario is examined. That scenario consists of a hypothetical landfill that initially contained uranium‐238 and methylene chloride. The multimedia models predict the fate of these contaminants, plus the progeny of uranium‐238, through the unsaturated zone, saturated zone, surface water, and atmosphere. Carcinogenic risks are calculated from exposure to the contaminants via multiple pathways. Results of the tests show that differences in model endpoint estimates arise from both differences in the models’ mathematical formulations and assumptions related to the implementation of the scenarios.
On the Solution Approach for Bayesian Modeling of Initiating Event Frequencies and Failure Rates
Authors: Hofer Eduard , Hora Stephen C. , Iman Ronald L. , Peschke Jörg
Published: May 2006

There is a need for plant‐specific distributions of incidence and failure rates rather than distributions from pooled data which are based on the “common incidence rate” assumption. The so‐called superpopulation model satisfies this need through a practically appealing approach that accounts for the variability over the population of plants. Unfortunately, the chosen order in which the integrals with respect to the individual plant rates λi, (i= 0, 1…, m) and the parameters a, β of the Γ‐population distribution are solved seems to drive the solution close to the common incidence rate distribution. It is shown that the solution obtained from interchanging the order and solving the integrals with respect to the individual plant rates by Monte Carlo simulation very quickly provides the plant specific distribution. This differing solution behaviour may be due to the lack of uniform convergence over (α, β, λI, (i= 1,…, m))‐space. Examples illustrate the difference that may be observed.
Comparing Estimates of the Effects of Air Pollution on Human Mortality Obtained Using Different Regression Methodologies
Authors: Baxter Laurence A. , Finch Stephen J. , Lipfert Frederick W. , Yu Qiqing
Published: May 2006

Studies using regression techniques report their results using a variety of statistics. Evaluation of the consistency of findings, such as in a metaanalysis, requires calculating the statistical estimates of the effect reported in each study in a comparable manner. In this paper, we consider multiple linear regression, multiple Poisson regression, and logistic regression estimates. We present results that are needed to calculate, on a common basis, the slope of the regression function at a specified value, the elasticity function of the regression function at a specified value, the relative risk at a specified value, and the odds ratio at a specified value. We apply these results to studies of the association of daily mortality in an area to the daily air pollution level of ozone and PM10. We calculate the estimated slope of the number of deaths per billion population associated with an increase of 1 ppb of ozone level in studies of daily mortality in three urban areas. These studies, in Los Angeles, New York, and St. Louis, produced very comparable results on a common basis, especially when compared to the coefficients as reported. We also calculated the estimated elasticity function of the daily mortality and daily PM10 level for eight areas and found that the elasticities varied within a factor of roughly two, much less than the variability in the coefficients as reported.
Perception of Ecological Risk to Water Environments
Authors: McDaniels Timothy L. , Axelrod Lawrence J. , Cavanagh Nigel S. , Slovic Paul
Published: May 2006

This paper examines lay and expert perceptions of the ecological risks associated with a range of human activities that could adversely affect water resource environments. It employs the psychometric paradigm pioneered in characterizing perceptions of human health risks, which involves surveys to obtain judgments from subjects about risk items in terms of several important characteristics of the risks. The paper builds on a previous study that introduced ecological risk perception. This second study employs a larger, more diverse sample, a more focused topic area, and comparisons between lay and expert judgments. The results confirm that a small set of underlying factors explain a great deal of variability in lay judgments about ecological risks. These have been termed Ecological Impact, Human Benefits, Controllability, and Knowledge. The results are useful in explaining subjects’ judgments of the general riskiness of, and need for regulation of, various risk items. The results also indicate several differences and areas of agreement among the lay and expert samples that point to potential key issues in future ecological risk management efforts for water resources.
Residential House and Zone Volumes in the United States: Empirical and Estimated Parametric Distributions
Authors: Murray Donald M.
Published: May 2006

This research reports empirical distributions and estimated univariate parametric probability distributions for house volume and certain zone volumes within households for residential structures in the United States. The author derived the distributions from two separate databases. The volumes were found to be exceptionally well fit by lognormal distributions (adjusted R2 >> 0.95) in almost all cases. In addition, data from one database indicates that the correlation between house volume and air changes per hour is very weak.
Cross‐Cultural Differences in Risk Perception: A Model‐Based Approach
Authors: Bontempo Robert N. , Bottom William P. , Weber Elke U.
Published: May 2006

The present study assessed cross‐cultural differences in the perception of financial risks. Students at large universities in Hong Kong, Taiwan, the Netherlands, and the U.S., as well as a group of Taiwanese security analysts rated the riskiness of a set of monetary lotteries. Risk judgments differed with nationality, but not with occupation (students vs. security analysts) and were modeled by the Conjoint Expected Risk (CER) model.(1) Consistent with cultural differences in country uncertainty avoidance,(2) CER model parameters of respondents from the two Western countries differed from those of respondents from the two countries with Chinese cultural roots: The risk judgments of respondents from Hong Kong and Taiwan were more sensitive to the magnitude of potential losses and less mitigated by the probability of positive outcomes.
Mixed Messages in Risk Communication
Authors: Jardine Cynthia G. , Hrudey Steve E.
Published: May 2006

The exchange of risk information between risk managers and affected parties is frequently hampered by differences in the understanding or interpretation of many words and phrases. Much of the terminology used by risk practitioners may have different “technical” and “colloquial” meanings, resulting in “mixed messages” in risk communication. Several words and concepts commonly used in risk management that may be resulting in these “mixed messages” are discussed. These include primary underlying concepts, such as the various meanings of the word “risk” itself, as well as the perplexity of the notions of “safety vs. zero risk” and “probability”. The potential “mixed messages” of the derived concepts of “significant vs. nonsignificant”, “negative vs. positive results”, “conservative assumptions”, “population vs. individual risk”, “relative vs. absolute risk”, and “association vs. causation” are shown to range from mild confusion to the completely opposite interpretation of these words and expressions. Suggested strategies for recognizing and mitigating the use of words and phrases which may create unnecessary confusion are presented.
Evaluation of Methods for Assessing the Oral Bioavailability of Inorganic Mercury in Soil
Authors: Schoof Rosalind A. , Nielsen Jesper Bo
Published: May 2006

The risks associated with environmental exposures to inorganic mercury are typically assessed based on toxicity studies conducted with the soluble salt, mercuric chloride (HgCl2). Evidence indicates, however, that inorganic mercury is present in soil as a variety of compounds and that oral absorption of inorganic mercury decreases with a decrease in the solubility of the mercury compound being studied. Thus, while HgCl2 is approximately 15–20% bioavailable, the bioavailability of cinnabar (HgS) may be 30‐ to 60‐fold less. The solubility and, hence, bioavailability of inorganic mercury in soil is expected to be substantially less than that of HgCl2 due to the presence of less soluble compounds and their interactions with soil constituents. Quantification of this difference in bioavailability is important in assessing potential risks associated with exposure to mercury‐containing soil. A review of available studies supports the expectation that mercury bioavailability in soils will be reduced. This paper reviews methods for assessing soil metal absorption with consideration of the characteristics of the oral absorption of elemental and inorganic mercury that should be evaluated in designing additional studies. Because of the very slow elimination of mercury in some species, it is recommended that a repeated‐dose study be conducted. Such a study would yield an estimate of relative bioavailability based on a comparison of tissue mercury concentrations in animals ingesting soil with those of animals receiving HgCl2. The dose, age, gender, and species of animal selected are not expected to affect relative bioavailability estimates; however, it is recommended that studies be conducted in two animal species. Rats should be used because they have been used in many studies of mercury absorption and toxicity. A species of large animals such as monkeys, swine, or dogs should also be used to provide confirmation in a species with greater similarities to humans in gastrointestinal physiology and anatomy. Other critical factors in designing these studies, such as selection and characterization of soil samples, are also addressed.
A Physiologically‐Based Pharmacokinetic Model Assessment of Methyl t‐Butyl Ether in Groundwater for a Bathing and Showering Determination
Authors: Rao Hari V. , Ginsberg Gary L.
Published: May 2006

Methyl t‐butyl ether (MTBE) is a gasoline additive that has appeared in private wells as a result of leaking underground storage tanks. Neurological symptoms (headache, dizziness) have been reported from household use of MTBE‐affected water, consistent with animal studies showing acute CNS depression from MTBE exposure. The current research evaluates acute CNS effects during bathing/showering by application of physiologically‐based pharmacokinetic (PBPK) techniques to compare internal doses in animal toxicity studies to human exposure scenarios. An additional reference point was the delivered dose associated with the acute Minimum Risk Level (MRL) for MTBE established by the Agency for Toxic Substances and Disease Registry. A PBPK model for MTBE and its principal metabolite, t‐butyl alcohol (TBA) was developed and validated against published data in rats and humans. PBPK analysis of animal studies showed that acute CNS toxicity after MTBE exposure can be attributed principally to the parent compound since the metabolite (TBA) internal dose was below that needed for CNS effects. The PBPK model was combined with an exposure model for bathing and showering which integrates inhalation and dermal exposures. This modeling indicated that bathing or showering in water containing MTBE at 1 mg/L would produce brain concentrations ˜1000‐fold below the animal effects level and twofold below brain concentrations associated with the acute MRL. These findings indicate that MTBE water concentrations of 1 mg/L or below are unlikely to trigger acute CNS effects during bathing and showering. However, MTBE's strong odor may be a secondary but deciding factor regarding the suitability of such water for domestic uses.
Variability in PAH‐DNA Adduct Measurements in Peripheral Mononuclear Cells: Implications for Quantitative Cancer Risk Assessment
Authors: Dickey Christopher , Santella Regina M. , Hattis Dale , Tang Deliang , Hsu Yanzhi , Cooper Tom , Young Tie‐Lan , Perera Frederica P.
Published: May 2006

Biomarkers such as DNA adducts have significant potential to improve quantitative risk assessment by characterizing individual differences in metabolism of genotoxins and DNA repair and accounting for some of the factors that could affect interindividual variation in cancer risk. Inherent uncertainty in laboratory measurements and within‐person variability of DNA adduct levels over time are putatively unrelated to cancer risk and should be subtracted from observed variation to better estimate interindividual variability of response to carcinogen exposure. A total of 41 volunteers, both smokers and nonsmokers, were asked to provide a peripheral blood sample every 3 weeks for several months in order to specifically assess intraindividual variability of polycyclic aromatic hydrocarbon (PAH)‐DNA adduct levels. The intraindividual variance in PAH‐DNA adduct levels, together with measurement uncertainty (laboratory variability and unaccounted for differences in exposure), constituted roughly 30% of the overall variance. An estimated 70% of the total variance was contributed by interindividual variability and is probably representative of the true biologic variability of response to carcinogenic exposure in lymphocytes. The estimated interindividual variability in DNA damage after subtracting intraindividual variability and measurement uncertainty was 24‐fold. Inter‐individual variance was higher (52‐fold) in persons who constitutively lack the Glutathione S‐Transferase M1 (GSTM1) gene which is important in the detoxification pathway of PAH. Risk assessment models that do not consider the variability of susceptibility to DNA damage following carcinogen exposure may underestimate risks to the general population, especially for those people who are most vulnerable.
ASME Risk‐Based Inservice Inspection and Testing: An Outlook to the Future
Authors: Balkey Kenneth R. , Art Raymond J. , Bosnak Robert J.
Published: May 2006

Significant research work has been completed in the development of risk‐based inservice inspection (ISI) and testing (IST) technology for nuclear power plant applications through the ASME Center For Research and Technology Development. This paper provides technology that has been developed for these engineering applications. The technology includes risk‐based ranking methods, beginning with the use of plant probabilistic risk assessment (PRA), for the determination of risk‐significant and less risk‐significant components for inspection and the determination of similar populations for pumps and valves for inservice testing. Decision analysis methods are outlined for developing ISI and IST programs. This methodology integrates nondestructive examination data, structural reliability/risk assessment results, PRA results, failure data, and expert opinion to evaluate the effectiveness of ISI programs. Similarly, decision analysis uses the output of failure mode and causes analysis in combination with data, expert opinion, and PRA results to evaluate the effectiveness of IST programs. Results of pilot applications of these ASME methods to actual nuclear plant systems and components are summarized. The results of this work are already being used to develop recommended changes in ISI and IST requirements by the ASME Section XI and the ASME Operation and Maintenance Code organizations. A perspective on Code and regulatory adoption is also outlined. Finally, the potential benefits to the nuclear industry in terms of safety, person‐rem exposure, and costs are summarized.
A Lognormal Distribution for Time Spent Showering
Authors: Burmaster David E.
Published: May 2006

In 1987, James and Knuiman published their analysis of a comprehensive domestic water use study conducted in Perth, Western Australia to quantify the components of water usage in approximately 3000 households. This manuscript corrects errors and omissions about James and Knuiman's study in the U.S. EPA's Exposure Factors Handbook, and it shows James and Knuiman's results in a form and notation more readily used in Monte Carlo simulations.
Uncertainty and Variability Analysis in Multiplicative Risk Models
Authors: Rai S. N. , Krewski D.
Published: May 2006

Currently, there is a trend away from the use of single (often conservative) estimates of risk to summarize the results of risk analyses in favor of stochastic methods which provide a more complete characterization of risk. The use of such stochastic methods leads to a distribution of possible values of risk, taking into account both uncertainty and variability in all of the factors affecting risk. In this article, we propose a general framework for the analysis of uncertainty and variability for use in the commonly encountered case of multiplicative risk models, in which risk may be expressed as a product of two or more risk factors. Our analytical methods facilitate the evaluation of overall uncertainty and variability in risk assessment, as well as the contributions of individual risk factors to both uncertainty and variability which is cumbersome using Monte Carlo methods. The use of these methods is illustrated in the analysis of potential cancer risks due to the ingestion of radon in drinking water.
Quantifying the Distribution of Inhalation Exposure in Human Populations: 2. Distributions of Time Spent by Adults, Adolescents, and Children at Home, at Work, and at School
Authors: Funk Lisa M. , Sedman Richard , Beals Jill A. J. , Fountain Robert
Published: May 2006

Using distributions of time spent at various ventilation levels, ranges of inhalation exposure in the population can be established. Distributions of exposure time were determined using results of a study by the California Air Resources Board (CARB) which focused on time spent by humans participating in various activities and the locations where the activities occurred. The daily at‐home activities from the CARB study were assigned to one of three ventilation levels, generating aggregate time periods. Distinct age and gender populations were identified, and distributions for aggregate time were established for these populations at each of the ventilation levels. In addition to aggregate time spent at home, distributions for various ages and genders were established for aggregate time spent at school and work. By combining distributions of aggregate time with corresponding ventilation rates, the distribution of inhalation rates can be established for at home, at work, and at school exposures.
The EPA Health Risk Assessment of Methylcyclopentadienyl Manganese Tricarbonyl (MMT)
Authors: Davis J. Michael , Jarabek Annie M. , Mage David T. , Graham Judith A.
Published: May 2006

This paper describes the U.S. Environmental Protection Agency's assessment of potential health risks associated with the possible widespread use of a manganese (Mn)‐based fuel additive, methylcyclopentadienyl manganese tricarbonyl (MMT). This assessment was significant in several respects and may be instructive in identifying certain methodological issues of general relevance to risk assessment. A major feature of the inhalation health risk assessment was the derivation of Mn inhalation reference concentration (RfC) estimates using various statistical approaches, including benchmark dose and Bayesian analyses. The exposure assessment component used data from the Particle Total Exposure Assessment Methodology (PTEAM) study and other sources to estimate personal exposure levels of particulate Mn attributable to the permitted use of MMT in leaded gasoline in Riverside, CA, at the time of the PTEAM study; on this basis it was then possible to predict a distribution of possible future exposure levels associated with the use of MMT in all unleaded gasoline. Qualitative as well as quantitative aspects of the risk characterization are summarized, along with inherent uncertainties due to data limitations.
Compliance Strategies and Regulatory Effectiveness of Performance‐Based Regulation of Chemical Accident Risks
Authors: Chinander Karen R. , Kleindorfer Paul R. , Kunreuther Howard C.
Published: May 2006

This paper investigates the role that performance‐based regulations can play in linking a firm's environmental, health, and safety concerns with their corporate strategy. The specific focus is on the performance standards required by the Clean Air Act Amendments (CAAA) which require firms that store or use certain chemicals to develop a Risk Management Plan (RMP) for reducing the likelihood and impact of accidents at their plants. Data from a series of case studies and interviews of executives in chemical firms reveal that proactive companies integrated many of the requirements of the CAAA into their management systems prior to the regulatory requirements. Most of these firms tend to be large ones. Small firms often lack the resources to implement these regulations and hence have tended to have a more difficult time with compliance.
Influence of Prenatal Mercury Exposure Upon Scholastic and Psychologica Test Performance: Benchmark Analysis of a New Zealand Cohort
Authors: Grump Kenny S. , Kjellström Tord , Shipp Annette M. , Silvers Abraham , Stewart Alistair
Published: May 2006

This paper presents benchmark (BMD) calculations and additional regression analyses of data from a study in which scores from 26 scholastic and psychological tests administered to 237 6‐ and 7‐year‐old New Zealand children were correlated with the mercury concentration in their mothers' hair during pregnancy. The original analyses of five test scores found an association between high prenatal mercury exposure and decreased test performance, using category variables for mercury exposure. Our regression analyses, which utilized the actual hair mercury level, did not find significant associations between mercury and children's test scores. However, this finding was highly influenced by a single child whose mother's mercury hair level (86 mgkg) was more than four times that of any other mother. When that child was omitted, results were more indicative of a mercury effect and scores on six tests were significantly associated with the mothers' hair mercury level. BMDs calculated from five tests ranged from 32 to 73 mgkg hair mercury, and corresponding BMDLs (95% lower limits on BMDs) ranged from 17 to 24 mgkg. When the child with the highest mercury level was omitted, BMDs ranged from 13 to 21 mgkg, and corresponding BMDLs ranged from 7.4 to 10 mgkg.
Ecological and Economic Risk Analysis of Everglades: Phase I Restoration Alternatives
Authors: Englehardt James D.
Published: May 2006

Evaluating alternatives for restoring the Everglades involves analysis of a complex ecological and economic system for which current knowledge is limited. Uncertain benefits and impacts are analyzed probabilistically in this paper, following otherwise accepted principles of net present value (NPV) analysis. Ecological benefits and impacts were considered in monetary terms. Probabilities for selected uncertain parameters were found by maximizing entropy. The first ecological risk conceptual model for the Everglades ecosystem was developed to show ecological interactions. “Current Plans” for restoration involve discharge of phosphorus‐enriched water from artificial wetlands to relatively pristine Everglades marshes for 3–10 years, risking conversion of the ecosystem to a eutrophic cattail marsh. For two of the three areas studied, alternative “Bypass Plans” were shown to avoid the loss of up to 3000 acres of sawgrass marsh at a cost that is probabilistically justified by the value of the ecosystem preserved. Sensitivity of the results to projected ecological changes, eutrophic marsh valuation, natural marsh valuation, and future values as represented in the discount rate, was examined.
Principles for Conduct of Pest Risk Analyses: Report of an Expert Work hop
Authors: Gray George M. , Allen Jon C. , Burmaster David E. , Gage Stuart H. , Hammitt James K. , Kaplan Stanley , Keeney Ralph L. , Morse Joseph G. , North D. Warner , Nyrop Jan P. , Stahevitch Alina , Williamslau Richard
Published: May 2006

The North American Free Trade Agreement (NAFTA) and the General Agreement on Tariffs and Trade (GATT) have focused attention on risk assessment of potential insect, weed, and animal pests and diseases of livestock. These risks have traditionally been addressed through quarantine protocols ranging from limits on the geographical areas from which a product may originate, postharvest disinfestation procedures like fumigation, and inspections at points of export and import, to outright bans. To ensure that plant and animal protection measures are not used as nontariff trade barriers, GATT and NAFTA require pest risk analysis (PRA) to support quarantine decisions. The increased emphasis on PRA has spurred multiple efforts at the national and international level to design frameworks for the conduct of these analyses. As approaches to pest risk analysis proliferate, and the importance of the analyses grows, concerns have arisen about the scientific and technical conduct of pest risk analysis. In January of 1997, the Harvard Center for Risk Analysis (HCRA) held an invitation‐only workshop in Washington, D.C. to bring experts in risk analysis and pest characterization together to develop general principles for pest risk analysis. Workshop participants examined current frameworks for PRA, discussed strengths and weaknesses of the approaches, and formulated principles, based on years of experience with risk analysis in other setting and knowledge of the issues specific to analysis of pests. The principles developed highlight the both the similarities of pest risk analysis to other forms of risk analysis, and its unique attributes.
Urban Risks of Truck Transport of Radioactive Material
Authors: Mills G. Scott , Neuhauser K. Sieglinde
Published: May 2006

Truck transport of radioactive material (RAM), e.g., spent nuclear fuel (SNF), normally maximizes use of Interstate highways, which are safer and more efficient for truck transport in general. In the estimation of transportation risks, population bordering a route is a direct factor in determining consequences and an indirect factor in determining exposure times, accident probabilities and severities, and other parameters. Proposals to transport RAM may draw intense resistance from “stakeholders” based on concern for population concentrations along urban segments but the length of a route segment is also a determinative factor in estimating the transport risks. To quantify the relative importance of these two factors, a potential route for transport of SNF (strict use of Interstate highways) was selected and compared with a modified version that bypassed urban areas. The results suggest that emphasis on Interstate highways minimizes total route and urban segment risks.
Presenting Results from Model Based Studies to Decision‐Makers: Can Sensitivity Analysis Be a Defogging Agent?
Authors: Saltelli Andrea , Tarantola Stefano , Chad Karen
Published: May 2006

The motivation of the present work is to provide an auxiliary tool for the decision‐maker (DM) faced with predictive model uncertainty. The tool is especially suited for the allocation of R&Dresources. When taking decisions under uncertainties, making use of the output from mathematical or computational models, the DM might be helped if the uncertainty in model predictions be decomposed in a quantitative‐rather than qualitativefashion, apportioning uncertainty according to source. This would allow optimal use of resources to reduce the imprecision in the prediction. For complex models, such a decomposition of the uncertainty into constituent elements could be impractical as such, due to the large number of parameters involved. If instead parameters could be grouped into logical subsets, then the analysis could be more useful, also because the decision maker might likely have different perceptions (and degrees of acceptance) for different kinds of uncertainty. For instance, the decomposition in groups could involve one subset of factors for each constituent module of the model; or one set for the weights, and one for the factors in a multicriteria analysis; or phenomenological parameters of the model vs. factors driving the model configuratiodstructure aggregation level, etc.); finally, one might imagine that a partition of the uncertainty could be sought between stochastic (or aleatory) and subjective (or epistemic) uncertainty. The present note shows how to compute rigorous decomposition of the output's variance with grouped parameters, and how this approach may be beneficial for the efficiency and transparency of the analysis.
How Do People Evaluate Risk Reduction When They Are Told Zero Risk Is Impossible?
Authors: Nakayachi Kazuya
Published: May 2006

Two studies examined how people evaluate risk reduction when they believe zero risk to be impossible. Measures collected were willingness to pay (WTP) for risk reduction, and degree of trust in the risk management agency. The findings from the combined studies are: (1) participants were more willing to pay a higher amount for the same reduction in risk in the “zero risk possible” than in the “zero risk impossible” condition; and (2) people's trust in the risk management agency did not differ between the “zero risk impossible” and “zero risk possible” conditions. These results suggest that it might be viable for agencies to accurately communicate the unattainability of zero risk without suffering a loss in public faith or trust, and thus that excessive expenditure for risk reduction might be prevented.
Estimates of the Number of Liver Carcinogens in Bioassays Conducted by the National Toxicology Program
Authors: Crump Kenny S. , Krewski D. , Wang Y.
Published: May 2006

Estimates were made of the numbers of liver carcinogens in 390 long‐term bioassays conducted by the National Toxicology Program (NTP). These estimates were obtained from examination of the global pattern of p‐values obtained from statistical tests applied to individual bioassays. Representative estimates of the number of liver carcinogens (90% confidence interval in parentheses) obtained in our analysis compared to NTP's determination are as follows: female rats—49 (23, 76), NTP = 30; male rats—88 (59, 116), NTP = 35; female mice—131 (105, 157), NTP = 81; male mice—100 (73, 126), NTP = 61; overall—166 (135, 197), NTP = 108. The estimator from which these estimates were obtained is biased low by an unknown amount. Consequently, this study provides persuasive evidence of the existence of more rodent liver carcinogens than were identified by the NTP.
Chinese and Americans Agree on What Is Fair, but Disagree on What Is Best in Societal Decisions Affecting Health and Safety Risks
Authors: Bian Wen‐Qiang , Keller L. Robin
Published: May 2006

Through surveys of students and junior professionals and interviews with business and government executives, we studied Chinese choices and fairness perceptions in risky health and safety decisions. The survey responses were compared with American responses from an earlier study by Keller and Sarin.

The survey results show that the American and Chinese respondents had similar fairness perceptions, but the Chinese did not make decisions that were consistent with their fairness perceptions, whereas the Americans did. We found that the middle‐age Chinese professionals tended to make choices that were more different from the Americans than were the choices of the young Chinese management students. It is likely that these discrepancies were caused by cultural differences, with the younger Chinese tending to face a stronger Western influence.

The insights from the survey results were enriched by interviews that revealed fairness perceptions of Chinese business and government executives.A framework to interpret cultural influences on decision making was also proposed.
Evaluation of Atmospheric Transport Models for Use in Phase I1 of the Historical Public Exposures Studies at the Rocky Flats Plant
Authors: Rood Arthur S. , Killough George G. , Till John E.
Published: May 2006

Five atmospheric transport models were evaluated for use in Phase I1 ofthe Historical Public Exposures Studies at the Rocky Flats Plant. Models included a simple straight‐line Gaussian plume model (ISCST2), several integrated puff models (RATCHET, TRIAD, and INPUFF2), and a complex terrain mode (TRAC). Evaluations were based on how well model predictions compared with sulfur hexafluoride tracer measurements taken in the vicinity of Rocky Flats in February 1991. Twelve separate tracer experiments were conducted, eac lasting 9 hr and measured at 140 samplers in arcs 8 and 16 km from the release point at Rocky Flats. Four modeling objectives were defined based on the endpoints of the overall study: (1) the unpaired maximum hourly average concentration, (2) paired time‐averaged concentration, (3) unpaired time‐averaged concentration, and (4) arc‐integrated concentration. Performance measures were used to evaluate models and focused on the geometric mean and standard deviation of the predicted‐to‐observed ratio and the correlation coefficient between predicted and observed concentrations. No one model consistently outperformed the others in all modeling objectives and performance measures. About 75% of the maximum hourly concentration predictions were within a factor of 5 of the observations. About 64% of the paired and 80% of the unpaired time‐averaged model predictions were within a factor of 5 of theobservations. The overall performance of the RATCHET model was somewhat better than the other models. All models appeared to experience difficulty defining plume trajectories, which was attributed to the influence of multilayered flow initiated by terrain complexities and the diurnal flow patterns characteristic of the Colorado Front Range.