ALBERT

Notes: As part of its preparation to review a potential license application from the U.S. Department of Energy (DOE), the U.S. Nuclear Regulatory Commission (NRC) is examining the performance of the proposed Yucca Mountain nuclear waste repository. In this regard, we evaluated postclosure repository performance using Monte Carlo analyses with an NRC-developed system model that has 950 input parameters, of which 330 are sampled to represent system uncertainties. The quantitative compliance criterion for dose was established by NRC to protect inhabitants who might be exposed to any releases from the repository. The NRC criterion limits the peak-of-the-mean dose, which in our analysis is estimated by averaging the potential exposure at any instant in time for all Monte Carlo realizations, and then determining the maximum value of the mean curve within 10,000 years, the compliance period. This procedure contrasts in important ways with a more common measure of risk based on the mean of the ensemble of peaks from each Monte Carlo realization. The NRC chose the former (peak-of-the-mean) because it more correctly represents the risk to an exposed individual. Procedures for calculating risk in the expected case of slow repository degradation differ from those for low-probability cases of disruption by external forces such as volcanism. We also explored the possibility of risk dilution (i.e., lower calculated risk) that could result from arbitrarily defining wide probability distributions for certain parameters. Finally, our sensitivity analyses to identify influential parameters used two approaches: (1) the ensemble of doses from each Monte Carlo realization at the time of the peak risk (i.e., peak-of-the-mean) and (2) the ensemble of peak doses calculated from each realization within 10,000 years. The latter measure appears to have more discriminatory power than the former for many parameters (based on the greater magnitude of the sensitivity coefficient), but can yield different rankings, especially for parameters that influence the timing of releases.

Notes: Variability is the heterogeneity of values within a population. Uncertainty refers to lack of knowledge regarding the true value of a quantity. Mixture distributions have the potential to improve the goodness of fit to data sets not adequately described by a single parametric distribution. Uncertainty due to random sampling error in statistics of interests can be estimated based upon bootstrap simulation. In order to evaluate the robustness of using mixture distribution as a basis for estimating both variability and uncertainty, 108 synthetic data sets generated from selected population mixture log-normal distributions were investigated, and properties of variability and uncertainty estimates were evaluated with respect to variation in sample size, mixing weight, and separation between components of mixtures. Furthermore, mixture distributions were compared with single-component distributions. Findings include: (1) mixing weight influences the stability of variability and uncertainty estimates; (2) bootstrap simulation results tend to be more stable for larger sample sizes; (3) when two components are well separated, the stability of bootstrap simulation is improved; however, a larger degree of uncertainty arises regarding the percentiles coinciding with the separated region; (4) when two components are not well separated, a single distribution may often be a better choice because it has fewer parameters and better numerical stability; and (5) dependencies exist in sampling distributions of parameters of mixtures and are influenced by the amount of separation between the components. An emission factor case study based upon NOx emissions from coal-fired tangential boilers is used to illustrate the application of the approach.

Notes: Estimates of the lifetime-absorbed daily dose (LADD) of acrylamide resulting from use of representative personal-care products containing polyacrylamides have been developed. All of the parameters that determine the amount of acrylamide absorbed by an individual vary from one individual to another. Moreover, for some parameters there is uncertainty as to which is the correct or representative value from a range of values. Consequently, the parameters used in the estimation of the LADD of acrylamide from usage of a particular product type (e.g., deodorant, makeup, etc.) were represented by distributions evaluated using Monte Carlo analyses.(1–4) From these data, distributions of values for key parameters, such as the amount of acrylamide in polyacrylamide, absorption fraction, etc., were defined and used to provide a distribution of LADDs for each personal-care product. The estimated total acrylamide LADD (across all products) for males and females at the median, mean, and 95th percentile of the distribution of individual LADD values were 4.7 × 10−8, 2.3 × 10−7, and 7.3 × 10−7 mg/kg/day for females and 3.6 × 10−8, 1.7 × 10−7, and 5.4 × 10−7 mg/kg/day for males. The ratio of the LADDs to risk-specific dose corresponding to a target risk level of 1 × 10−5, the acceptable risk level for this investigation, derived using approaches typically used by the FDA, the USEPA, and proposed for use by the European Union (EU) were also calculated. All ratios were well below 1, indicating that all the extra lifetime cancer risk from the use of polyacrylamide-containing personal-care products, in the manner assumed in this assessment, are well below acceptable levels. Even if it were assumed that an individual used all of the products together, the estimated LADD would still provide a dose that was well below the acceptable risk levels.

Notes: The objective of this article is to compare the accuracy and numeric responses of breast cancer risk perception as measured by a frequency scale and percentage scale. A cross-sectional survey was conducted. Perceptions of five-year and lifetime breast cancer risk were measured using a frequency and a percentage scale. Estimation error was calculated as the absolute difference between actual breast cancer risk as determined by the Gail model and perceived risk. Agreement between scales was determined by calculating the mean and standard deviation of the difference between numeric responses. The study was conducted among women enrolled in two primary care clinics associated with an academic medical center. Two-hundred-fifty-four participants were recruited from one of the two participating internal medicine clinics. Inclusion criteria included female gender and age 40–84 years. Exclusion criteria included a history of breast cancer, dementia, or a life expectancy of less than two years. The frequency scale was more accurate than the percentage scale in estimating lifetime risk (p= 0.05), but less accurate in estimating five-year risk (p 〈 0.02). Only 79 participants (31%) were considered consistent scale users, providing identical responses when using the frequency and percentage scale for a given risk estimate. Although the mean difference (percentage-frequency scale) for estimates of breast cancer lifetime risk was only 2.4, the empirically determined 90% limits of agreement between the frequency and percentage scale for lifetime risk were wide, from –30 to 40. Higher numeracy was associated with consistent use of scales (OR 1.61, 95% CI; 1.09–2.37). We report disagreement in breast cancer risk perceptions when measured by a frequency and a percentage scale. The accuracy and direction of bias associated with each scale varies according to the time frame of risk being assessed.

Notes: A pragmatic quantitative risk assessment (QRA) of the risks of waterborne Cryptosporidium parvum infection and cryptosporidiosis in immunocompetent and immunodeficient French populations is proposed. The model takes into account French specificities such as the French technique for oocyst enumeration performance and tap water consumption. The proportion of infective oocysts is based on literature review and expert knowledge. The probability of infection for a given number of ingested viable oocysts is modeled using the exponential dose-response model applied on published data from experimental infections in immunocompetent human volunteers challenged with the IOWA strain. Second-order Monte Carlo simulations are used to characterize the uncertainty and variability of the risk estimates. Daily risk of infection and illness for the immunocompetent and the immunodeficient populations are estimated according to the number of oocysts observed in a single storage reservoir water sample. As an example, the mean daily risk of infection in the immunocompetent population is estimated to be 1.08 × 10−4 (95% confidence interval: [0.20 × 10−4; 6.83 × 10−4]) when five oocysts are observed in a 100 L storage reservoir water sample. Annual risks of infection and disease are estimated from a set of oocyst enumeration results from distributed water samples, assuming a negative binomial distribution of day-to-day contamination variation. The model and various assumptions used in the model are fully explained and discussed. While caveats of this model are well recognized, this pragmatic QRA could represent a useful tool for the French Food Safety Agency (AFSSA) to define recommendations in case of water resource contamination by C. parvum whose infectivity is comparable to the IOWA strain.

Notes: Assessments of aggregate exposure to pesticides and other surface contamination in residential environments are often driven by assumptions about dermal contacts. Accurately predicting cumulative doses from realistic skin contact scenarios requires characterization of exposure scenarios, skin surface loading and unloading rates, and contaminant movement through the epidermis. In this article we (1) develop and test a finite-difference model of contaminant transport through the epidermis; (2) develop archetypal exposure scenarios based on behavioral data to estimate characteristic loading and unloading rates; and (3) quantify 24-hour accumulation below the epidermis by applying a Monte Carlo simulation of these archetypal exposure scenarios. The numerical model, called Transient Transport through the epiDERMis (TTDERM), allows us to account for variable exposure times and time between exposures, temporal and spatial variations in skin and compound properties, and uncertainty in model parameters. Using TTDERM we investigate the use of a macro-activity parameter (cumulative contact time) for predicting daily (24-hour) integrated uptake of pesticides during complex exposure scenarios. For characteristic child behaviors and hand loading and unloading rates, we find that a power law represents the relationship between cumulative contact time and cumulative mass transport through the skin. With almost no loss of reliability, this simple relationship can be used in place of the more complex micro-activity simulations that require activity data on one- to five-minute intervals. The methods developed in this study can be used to guide dermal exposure model refinements and exposure measurement study design.

Notes: An interdisciplinary workshop was convened by the George Washington University in June 2001 to discuss how to incorporate new knowledge about susceptibility to microbial pathogens into risk assessment and management strategies. Experts from government, academic, and private sector organizations discussed definitions, methods, data needs, and issues related to susceptibility in microbial risk assessment. The participants agreed that modeling approaches need to account for the highly specific nature of host-pathogen relationships, and the wide variability of infectivity, immunity, disease transmission, and outcome rates within microbial species and strains. Concerns were raised about distinguishing between exposure and dose more clearly, interpreting experimental and outbreak data correctly, and using thresholds and possibly linearity at low doses. Recommendations were made to advance microbial risk assessment by defining specific terms and concepts more precisely, designing explicit conceptual frameworks to guide development of more complex models and data collection, addressing susceptibility in all steps of the model, measuring components of immunity to characterize susceptibility, reexamining underlying assumptions, applying default methods appropriately, obtaining more mechanistic data to improve default methods, and developing more biologically relevant and continuous risk estimators. The interrelated impacts of selecting specific subpopulations and health outcomes, and of increasing model complexity and data demands, were considered in the contexts of public policy goals and resources required. The participants stated that zero risk is unattainable, so targeted and effective risk reduction and communication strategies are essential not only to raise pubic awareness about water quality but also to protect the most susceptible members of the population.

Notes: Public opposition to genetically modified (GM) food and crops is widely interpreted as the result of the public's misperception of the risks. With scientific assessment pointing to no unique risks from GM crops and foods, a strategy of accurate risk communication from trusted sources has been advocated. This is based on the assumption that the benefits of GM crops and foods are self-evident. Informed by the interpretation of some qualitative interviews with lay people, we use data from the Eurobarometer survey on biotechnology to explore the hypothesis that it is not so much the perception of risks as the absence of benefits that is the basis of the widespread rejection of GM foods and crops by the European public. Some respondents perceive both risks and benefits, and may be trading off these attributes along the lines of a rational choice model. However, for others, one attribute—benefit—appears to dominate their judgments: the lexicographic heuristic. For these respondents, their perception of risk is of limited importance in the formation of attitudes toward GM food and crops. The implication is that the absence of perceived benefits from GM foods and crops calls into question the relevance of risk communication strategies for bringing about change in public opinion.

Notes: The introduction of classical swine fever virus (CSFV) into a country free of disease without vaccination may have huge consequences in terms of both disease spread and economic losses. More quantitative insight into the main factors determining the probability of CSFV introduction (PCSFV) is needed to optimally use resources for the prevention of CSFV introduction. For this purpose a spreadsheet model was constructed that calculates the annual PCSFV into member states of the European Union (EU). The scenario pathway approach was used as most probabilities in the model are very small. Probability distributions were used to take into account inherent variability of input parameters. The model contained pathways of CSFV introduction including the import of pigs and pork products, returning livestock trucks, and contacts with wild boar. All EU member states were included as possible sources of CSFV. Default results for the Netherlands showed a mean overall annual PCSFV of approximately 0.06, indicating that the Netherlands can expect CSFV introduction on average once every 18 years from the pathways and countries included in the model. Almost 65% of this probability could be attributed to the pathway of returning livestock trucks. The most likely sources of CSFV introduction were Germany, Belgium, and the United Kingdom. Although the calculated probabilities were rather low when compared with expert estimates and recent history, the most likely causes of CSFV introduction indicated by the model were considered to be realistic. It was therefore concluded that the model is a useful tool to structure and analyze information for decision making concerning the prevention of CSFV introduction.

Notes: The streptogramin antimicrobial combination Quinupristin-Dalfopristin (QD) has been used in the United States since late 1999 to treat patients with vancomycin-resistant Enterococcus faecium (VREF) infections. Another streptogramin, virginiamycin (VM), is used as a growth promoter and therapeutic agent in farm animals in the United States and other countries. Many chickens test positive for QD-resistant E. faecium, raising concern that VM use in chickens might compromise QD effectiveness against VREF infections by promoting development of QD-resistant strains that can be transferred to human patients. Despite the potential importance of this threat to human health, quantifying the risk via traditional farm-to-fork modeling has proved extremely difficult. Enough key data (mainly on microbial loads at each stage) are lacking so that such modeling amounts to little more than choosing a set of assumptions to determine the answer. Yet, regulators cannot keep waiting for more data. Patients prescribed QD are typically severely ill, immunocompromised people for whom other treatment options have not readily been available. Thus, there is a pressing need for sound risk assessment methods to inform risk management decisions for VM/QD using currently available data. This article takes a new approach to the QD-VM risk modeling challenge. Recognizing that the usual farm-to-fork (“forward chaining”) approach commonly used in antimicrobial risk assessment for food animals is unlikely to produce reliable results soon enough to be useful, we instead draw on ideas from traditional fault tree analysis (“backward chaining”) to reverse the farm-to-fork process and start with readily available human data on VREF case loads and QD resistance rates. Combining these data with recent genogroup frequency data for humans, chickens, and other sources (Willems et al., 2000, 2001) allows us to quantify potential human health risks from VM in chickens in both the United States and Australia, two countries where regulatory action for VM is being considered.We present a risk simulation model, thoroughly grounded in data, that incorporates recent nosocomial transmission and genetic typing data. The model is used to estimate human QD treatment failures over the next five years with and without continued VM use in chickens. The quantitative estimates and probability distributions were implemented in a Monte Carlo simulation model for a five-year horizon beginning in the first quarter of 2002. In Australia, a Q1-2002 ban of virginiamycin would likely reduce average attributable treatment failures by 0.35 × 10−3 cases, expected mortalities by 5.8 × 10−5 deaths, and life years lost by 1.3 × 10−3 for the entire population over five years. In the United States, where the number of cases of VRE is much higher, a 1Q-2002 ban on VM is predicted to reduce average attributable treatment failures by 1.8 cases in the entire population over five years; expected mortalities by 0.29 cases; and life years lost by 6.3 over a five-year period. The model shows that the theoretical statistical human health benefits of a VM ban range from zero to less than one statistical life saved in both Australia and the United States over the next five years and are rapidly decreasing. Sensitivity analyses indicate that this conclusion is robust to key data gaps and uncertainties, e.g., about the extent of resistance transfer from chickens to people.

Notes: One of the lay public's concerns about genetically modified (GM) organisms (GMO) and related emerging technologies is that not all the important risks are evaluated or even identified yet—and that ignorance of the unanticipated risks could lead to severe environmental or public health consequences. To some degree, even the scientists who participated in the analysis of the risks from GMOs (arguably the people most qualified to critique these analyses) share some of this concern. To formally explore the uncertainty in the risk assessment of a GM crop, we conducted detailed interviews of seven leading experts on GM oilseed crops to obtain qualitative and quantitative information on their understanding of the uncertainties associated with the risks to agriculture from GM oilseed crops (canola or rapeseed). The results of these elicitations revealed three issues of potential concern that are currently left outside the scope of risk assessments. These are (1) the potential loss of the agronomic and environmental benefits of glyphosate (a herbicide widely used in no-till agriculture) due to the combined problems of glyphosate-tolerant canola and wheat volunteer plants, (2) the growing problem of seed lot contamination, and (3) the potential market impacts. The elicitations also identified two areas where knowledge is insufficient. These are: the occurrence of hybridization between canola and wild relatives and the ability of the hybrids to perpetuate themselves in nature, and the fate of the herbicide-tolerance genes in soil and their interaction with soil microfauna and -flora. The methodological contribution of this work is a formal approach to analyzing the uncertainty surrounding complex problems.

Notes: A method for combining multiple expert opinions that are encoded in a Bayesian Belief Network (BBN) model is presented and applied to a problem involving the cleanup of hazardous chemicals at a site with contaminated groundwater. The method uses Bayes Rule to update each expert model with the observed evidence, then uses it again to compute posterior probability weights for each model. The weights reflect the consistency of each model with the observed evidence, allowing the aggregate model to be tailored to the particular conditions observed in the site-specific application of the risk model. The Bayesian update is easy to implement, since the likelihood for the set of evidence (observations for selected nodes of the BBN model) is readily computed by sequential execution of the BBN model. The method is demonstrated using a simple pedagogical example and subsequently applied to a groundwater contamination problem using an expert-knowledge BBN model. The BBN model in this application predicts the probability that reductive dechlorination of the contaminant trichlorethene (TCE) is occurring at a site—a critical step in the demonstration of the feasibility of monitored natural attenuation for site cleanup—given information on 14 measurable antecedent and descendant conditions. The predictions for the BBN models for 21 experts are weighted and aggregated using examples of hypothetical and actual site data. The method allows more weight for those expert models that are more reflective of the site conditions, and is shown to yield an aggregate prediction that differs from that of simple model averaging in a potentially significant manner.

Notes: As a result of the legacy of the Cold War, the Departments of Energy and Defense are involved in massive cleanup and remediation projects. While health risk to humans and ecological receptors is perceived to be the basis for remediation, this assumption is rarely examined. In this article, we examine the role of risk and future land-use designations in cleanup decisions, using the Department of Energy's self-assessment of 36 sites. We then discuss the risk-related tools that might be required to address the cleanup challenge. Much of the current cleanup program is driven by compliance with federal and state statutes and regulations, presumably to protect human health and the environment. Compliance, however, is not synonymous with cleanup. Although some of these laws and regulations take risk into account, the lack of site-specific data on exposures and risk scenarios, and the lack of attention to future land use or end states, has often resulted in disconnects between risk and cleanup goals, risk and final end states, and cleanup levels and end state or subsequent land use. Partly, these disconnects result from the need for a range of technical, economic, sociological, and public policy tools to address the issues. A better transfer of information among and within Department of Energy facilities, operations offices, and DOE headquarters is required. Further, linking cleanup decisions and goals with the final end state involves a number of risk tradeoffs, including (1) ecological versus human health, (2) worker versus public health, (3) among competing contaminated areas, (4) among temporal patterns of cleanup, (5) among different ecological receptors (plants vs. animals, one animal vs. another), and (6) among the sites across the DOE complex. For the nation, balancing among risks is essential within sites and among Department of Energy sites, as well as among other remediation sites (such as those of Department of Defense and Superfund sites).

Notes: Developmental neurotoxicity concerns the adverse health effects of exogenous agents acting on neurodevelopment. Because human brain development is a delicate process involving many cellular events, the developing fetus is rather susceptible to compounds that can alter the structure and function of the brain. Today, there is clear evidence that early exposure to many neurotoxicants can severely damage the developing nervous system. Although in recent years, there has been much attention given to model development and risk assessment procedures for developmental toxicants, the area of developmental neurotoxicity has been largely ignored. Here, we consider the problem of risk estimation for developmental neurotoxicants from animal bioassay data. Since most responses from developmental neurotoxicity experiments are nonquantal in nature, an adverse health effect will be defined as a response that occurs with very small probability in unexposed animals. Using a two-stage hierarchical normal dose-response model, upper confidence limits on the excess risk due to a given level of added exposure are derived. Equivalently, the model is used to obtain lower confidence limits on dose for a small negligible level of risk. Our method is based on the asymptotic distribution of the likelihood ratio statistic (cf. Crump, 1995). An example is used to provide further illustration.

Notes: In regression analysis failure to adjust for imprecision in the exposure variable is likely to lead to underestimation of the exposure effect. However, the consequences of exposure error for determination of safe doses of toxic substances have so far not received much attention. The benchmark approach is one of the most widely used methods for development of exposure limits. An important advantage of this approach is that it can be applied to observational data. However, in this type of data, exposure markers are seldom measured without error. It is shown that, if the exposure error is ignored, then the benchmark approach produces results that are biased toward higher and less protective levels. It is therefore important to take exposure measurement error into account when calculating benchmark doses. Methods that allow this adjustment are described and illustrated in data from an epidemiological study on the health effects of prenatal mercury exposure.

Notes: Economic cost-benefit optimization of technical facility requires suitable “life saving cost” and/or an appropriate acceptance criterion if human life and limb are at risk. Traditionally, acceptance criteria implicit in codes of practice, standards, or regulations for well-defined fields of application are calibrated against past and present practice. This is all but satisfying. It is unclear whether present rules are already optimal. Extrapolations into new fields of application are extremely difficult. Direct cost-benefit analysis is proposed as an alternative. Based on the recently proposed “life quality index” (LQI), a rational acceptance criterion and so-called life saving cost are derived. The classical life quality index is reviewed, modified, and imbedded in modern economics theory. The results are then applied to technical facilities. The relation between optimization and the LQI-based acceptance criterion is discussed. The relevant economics literature is reviewed with respect to discount rates applicable for long-term investments into risk reduction. They should be as low as possible according to a recent mathematical result. Modern economic growth theory decomposes the output growth rate into the rate of time preference of consumption and the rate of economical growth multiplied by the elasticity of marginal utility of consumption. It is found that the rate of time preference of consumption should be a little larger than the long-term population growth rate. The public benefit rate (output growth rate) on the other hand should be smaller than the sum of the population growth rate and the long-term growth rate of a national economy, which is around 2% for most industrial countries. Accordingly, the rate of time preference of consumption is about 1%, which is also intergenerationally acceptable from an ethical point of view. Given a certain output growth rate there is a corresponding maximum financial interest rate in order to maintain nonnegativity of the objective function at the optimum. Finally, a simple demonstration example is added.

Notes: This article reports a quantitative risk assessment of human listeriosis linked to the consumption of soft cheeses made from raw milk. Risk assessment was based on data purposefully acquired inclusively over the period 2000–2001 for two French cheeses, namely: Camembert of Normandy and Brie of Meaux. Estimated Listeria monocytogenes concentration in raw milk was on average 0.8 and 0.3 cells/L, respectively, in Normandy and Brie regions. A Monte Carlo simulation was used to account for the time-temperature history of the milk and cheeses from farm to table. It was assumed that cell progeny did not spread within the solid cheese matrix (as they would be free to do in liquid broth). Interaction between pH and temperature was accounted for in the growth model. The simulated proportion of servings with no L. monocytogenes cell was 88% for Brie and 82% for Camembert. The 99th percentile of L. monocytogenes cell numbers in servings of 27 g of cheese was 131 for Brie and 77 for Camembert at the time of consumption, corresponding respectively to three and five cells of L. monocytogenes per gram. The expected number of severe listeriosis cases would be ≤10−3 and ≤2.5 × 10−3 per year for 17 million servings of Brie of Meaux and 480 million servings of Camembert of Normandy, respectively.

Notes: Food safety objectives (FSOs) are established in order to minimize the risk of foodborne illnesses to consumers, but these have not yet been incorporated into regulatory policy. An FSO states the maximum frequency and/or concentration of a microbiological hazard in a food at the time of consumption that provides an acceptable level of protection to the public and leads to a performance criterion for industry. However, in order to be implemented as a regulation, this criterion has to be achievable by the affected industry. In order to determine an FSO, the steps to produce and store that food need to be known, especially where they have an impact on contamination, growth, and destruction. This article uses existing models for growth of Listeria monocytogenes in conjunction with calculations of FSOs to approximate the outcome of more than one introduction of the foodborne organism throughout the food-processing path from the farm to the consumer. Most models for the growth and reduction of foodborne illnesses are logarithmic in nature, which fits the nature of the growth of microorganisms, spanning many orders of magnitude. However, these logarithmic models are normally limited to a single introduction step and a single reduction step. The model presented as part of this research addresses more than one introduction of food contamination, each of which can be separated by a substantial amount of time. The advantage of treating the problem this way is the accommodation of multiple introductions of foodborne pathogens over a range of time durations and conditions.

Notes: Risk assessment provides a formalized process to evaluate human, animal, and ecological responses associated with exposure to environmental agents. The purpose of risk assessment is to answer two related questions.〈list xml:id="l1" style="custom"〉• How likely is an (adverse) event to occur?• If it does, how severe will the impact be?In the United States, the science of risk assessment has evolved out of the necessity to make public health decisions in the face of scientific uncertainty. Its basic propositions have been established over the past three decades and its applications have impacted virtually every aspect of public health and environmental protection in many countries, including the United States. More recently, the World Trade Organization's (WTO) dispute-settlement process has provided additional incentive for the reliance on risk assessments internationally through the requirement that member countries be able to provide scientific justification, based on a risk assessment, for public health and environmental regulatory measures that are challenged. The purpose of this article is to review the history of risk assessment in the United States, emphasizing the development of both its scientific and policy aspects, as one example of the development of institutional capacity for risk assessment. This article discusses the importance of the social, political, and economic contexts of risk assessment and risk management in shaping the approaches taken while highlighting the reality that the analytic or risk assessment part of the decision-making process, in the absence of scientific data, can be completed only by inserting inferences, or policy judgments, which may differ among countries. This article recognizes these differences, and the consequent difference between risk assessment that incorporates public health protective assumptions and the rules of evidence that seek to answer questions of causality, and discusses implications for the WTO dispute-settlement process. It further explores the value of country-specific risk assessment guidelines to facilitate consistency within a country along with the appropriateness and feasibility of international risk assessment guidelines.

Notes: Data from a human feeding trial with healthy men were used to develop a dose-response model for 13 strains of Salmonella and to determine the effects of strain variation on the shape of the dose-response curve. Dose-response data for individual strains were fit to a three-phase linear model to determine minimum, median, and maximum illness doses, which were used to define Pert distributions in a computer simulation model. Pert distributions for illness dose of individual strains were combined in an Excel spreadsheet using a discrete distribution to model strain prevalence. In addition, a discrete distribution was used to model dose groups and thus create a model that simulated human feeding trials. During simulation of the model with @Risk, an illness dose and a dose consumed were randomly assigned to each consumption event in the simulated feeding trial and if the illness dose was greater than the dose consumed then the model predicted no illness, otherwise the model predicted that an illness would occur. To verify the dose-response model predictions, the original feeding trial was simulated. The dose-response model predicted a median of 69 (range of 43–101) illnesses compared to 74 in the original trial. Thus, its predictions were in agreement with the data used to develop it. However, predictions of the model are only valid for eggnog, healthy men, and the strains and doses of Salmonella used to develop it. When multiple strains of Salmonella were simulated together, the predicted dose-response curves were irregular in shape. Thus, the sigmoid shape of dose-response curves in feeding trials with one strain of Salmonella may not accurately reflect dose response in naturally contaminated food where multiple strains may be present.

Notes: CCA-treated wood is widely used in the fabrication of outdoor decks and playground equipment. Because arsenic can be removed from the surface of CCA-treated wood both by physical contact and by leaching, it is important to determine whether children who play on such structures may ingest arsenic in quantities sufficient to be of public health concern. Based on a review of existing studies, it is estimated that arsenic doses in amounts of tens of micrograms per day may be incurred by children having realistic levels of exposure to CCA-treated decks and playground structures. The most important exposure pathway appears to be oral ingestion of arsenic that is first dislodged from the wood by direct hand contact, then transferred to the mouth by children's hand-to-mouth activity. The next most important pathway appears to be dermal absorption of arsenic, while ingestion of soil that has become contaminated by leaching from CCA-treated structures appears to be of lesser importance, except possibly in the case of children with pica. Considerable uncertainty, however, is associated with quantitative estimates of children's arsenic exposure from CCA-treated wood. Priorities for refining estimates of arsenic dose include detailed studies of the hand-to-mouth transfer of arsenic, studies of the dermal and gastrointestinal absorption of dislodgeable arsenic, and studies in which doses of arsenic to children playing in contact with CCA-treated wood are directly determined by measurement of arsenic in their urine, hair, and nails.

Notes: There are two general theories of trust in risk management. One, derived from normative considerations, claims that trust is based on universally applicable factors such as fairness and objectivity. According to the second, social-psychological theory, trust is based on agreement or similarity and is context specific. Although the first theory is normative, it also claims, along with the second, to be a descriptive account of how trust judgments are made. The present study was designed to test the adequacy of these two theories by using a think-aloud procedure to examine the thinking associated with trust judgments in an experimental simulation of a typical risk management context. Contrary to the universalist theory, results supported two hypotheses derived from the social-psychological theory. First, study participants—who read brief policy statements designed to address global climate change—based their trust judgments on specific forms of agreement, ranging from agreement on the importance of the issue to agreement on values inferred from the policy statement. Second, the extent and depth of participants' conscious information processing was negatively related to the level of trust. Disagreement and distrust generated more conscious consideration than agreement and trust. These results provide a more detailed understanding than previously available of how trust in risk management is based on local forms of agreement that vary across people, contexts, and time.

Notes: There is increasing interest in the development of a microbial risk assessment methodology for regulatory and operational decision making. This document presents a methodology for assessing risks to human health from pathogen exposure using a population-based model that explicitly accounts for properties unique to an infectious disease process, specifically secondary transmission and immunity. To demonstrate the applicability of this risk-based method, numerical simulations were carried out for a case study example in which the route of exposure was direct consumption of biosolids-amended soil and the pathogen present in the soil was enterovirus. The output from the case study yielded a decision tree that differentiates between conditions in which the relative risk from biosolids exposure is high and those conditions in which the relative risk from biosolids is low. This decision tree illustrates the interaction among the important factors in quantifying risk. For the case study example, these factors include biosolids treatment processes, the pathogen shedding rate of infectious individuals, secondary transmission, and immunity. Further refinement in methods for determining biosolids exposures under field conditions would certainly increase the utility of these approaches.

Notes: Proposed applications of increasingly sophisticated biologically-based computational models, such as physiologically-based pharmacokinetic models, raise the issue of how to evaluate whether the models are adequate for proposed uses, including safety or risk assessment. A six-step process for model evaluation is described. It relies on multidisciplinary expertise to address the biological, toxicological, mathematical, statistical, and risk assessment aspects of the modeling and its application. The first step is to have a clear definition of the purpose(s) of the model in the particular assessment; this provides critical perspectives on all subsequent steps. The second step is to evaluate the biological characterization described by the model structure based on the intended uses of the model and available information on the compound being modeled or related compounds. The next two steps review the mathematical equations used to describe the biology and their implementation in an appropriate computer program. At this point, the values selected for the model parameters (i.e., model calibration) must be evaluated. Thus, the fifth step is a combination of evaluating the model parameterization and calibration against data and evaluating the uncertainty in the model outputs. The final step is to evaluate specialized analyses that were done using the model, such as modeling of population distributions of parameters leading to population estimates for model outcomes or inclusion of early pharmacodynamic events. The process also helps to define the kinds of documentation that would be needed for a model to facilitate its evaluation and implementation.

Notes: The affiliation. assessment and management of risks is a traditional part of veterinary medicine. In the past, veterinary services involved in this type of activity usually assessed risks qualitatively. However, since the 1990s, quantitative methods have become increasingly important. The establishment of the World Trade Organization in 1994, and the promulgation of its Agreement on the Application of Sanitary and Phytosanitary Measures (the “SPS Agreement”) led to an increased application of import risk analysis and to significant improvements in the methodology of risk analysis as applied to international trade policy for animals and animal products. However, there was very little development of risk analysis in veterinary fields other than international trade and management of health risks to consumers of animal products and little has been published on its use in the choice and definition of control or prophylaxis strategies for animal diseases. This article describes a quantitative risk assessment, which was undertaken in Italy to help choose an appropriate national response strategy following an incursion of bluetongue, an infectious disease of sheep and goats. The results obtained in this study support the use of risk analysis as a tool to assist in choosing an appropriate animal disease management strategy. The use of risk analysis in the evaluation of disease management strategies also offers advantages in international trade. It makes easier the comparison of different strategies applied in the various countries, and thus facilitates the assessment of equivalence of the guarantees provided by different strategies.

Notes: The purpose of this investigation was to estimate excess lifetime risk of lung cancer death resulting from occupational exposure to hexavalent-chromium-containing dusts and mists. The mortality experience in a previously studied cohort of 2,357 chromate chemical production workers with 122 lung cancer deaths was analyzed with Poisson regression methods. Extensive records of air samples evaluated for water-soluble total hexavalent chromium were available for the entire employment history of this cohort. Six different models of exposure-response for hexavalent chromium were evaluated by comparing deviances and inspection of cubic splines. Smoking (pack-years) imputed from cigarette use at hire was included in the model. Lifetime risks of lung cancer death from exposure to hexavalent chromium (assuming up to 45 years of exposure) were estimated using an actuarial calculation that accounts for competing causes of death. A linear relative rate model gave a good and readily interpretable fit to the data. The estimated rate ratio for 1 mg/m3-yr of cumulative exposure to hexavalent chromium (as CrO3), with a lag of five years, was RR= 2.44 (95% CI = 1.54–3.83). The excess lifetime risk of lung cancer death from exposure to hexavalent chromium at the current OSHA permissible exposure limit (PEL) (0.10 mg/m3) was estimated to be 255 per 1,000 (95% CI: 109–416). This estimate is comparable to previous estimates by U.S. EPA, California EPA, and OSHA using different occupational data. Our analysis predicts that current occupational standards for hexavalent chromium permit a lifetime excess risk of dying of lung cancer that exceeds 1 in 10, which is consistent with previous risk assessments.

Notes: The dose to human and nonhuman individuals inflicted by anthropogenic radiation is an important issue in international and domestic policy. The current paradigm for nonhuman populations asserts that if the dose to the maximally exposed individuals in a population is below a certain criterion (e.g., 〈10 mGy d−1) then the population is adequately protected. Currently, there is no consensus in the regulatory community as to the best statistical approach. Statistics, currently considered, include the maximum likelihood estimator for the 95th percentile of the sample mean and the sample maximum. Recently, the investigators have proposed the use of the maximum likelihood estimate of a very high quantile as an estimate of dose to the maximally exposed individual. In this study, we compare all of the above-mentioned statistics to an estimate based on extreme value theory. To determine and compare the bias and variance of these statistics, we use Monte Carlo simulation techniques, in a procedure similar to a parametric bootstrap. Our results show that a statistic based on extreme value theory has the least bias of those considered here, but requires reliable estimates of the population size. We recommend establishing the criterion based on what would be considered acceptable if only a small percentage of the population exceeded the limit, and hence recommend using the maximum likelihood estimator of a high quantile in the case that reliable estimates of the population size are not available.

Notes: The 1998 U.S. Environmental Protection Agency Office of Pesticide Programs (OPP) re-registration eligibility decision (RED) for phosphine fumigants has generated much interest in defining safe levels of exposure for workers and worker bystanders. This report summarizes the pertinent literature on phosphine toxicity, including animal inhalation studies and human epidemiology studies, and also describes a margin-of-exposure (MOE) analysis based on available worker exposure data. In addition, a safe occupational exposure limit is estimated using typical OPP assumptions, after determination of appropriate uncertainty factors, based on quality of data in the principal study and pharmacokinetic considerations. While a conservative 8-hour time-weighted average (TWA) of 0.1 ppm was calculated, the overall weight of evidence, from a risk-management perspective, supports a conclusion that an occupational TWA of 0.3 ppm provides adequate health protection. In addition, a 15-minute short-term exposure limit (STEL) of 3 ppm was estimated. Finally, in contrast to the MOE analysis described in the OPP's phosphine RED, the MOE analysis described herein does not indicate that fumigation workers are currently being exposed to unacceptable levels of phosphine. Collectively, these findings support the occupational exposure limits of 0.3 ppm (8-hour TWA) and 1 ppm (STEL) established in the updated applicator's manuals for phosphine-generating products, which recently received approval from OPP.

Notes: Ethylene oxide (EO) has been identified as a carcinogen in laboratory animals. Although the precise mechanism of action is not known, tumors in animals exposed to EO are presumed to result from its genotoxicity. The overall weight of evidence for carcinogenicity from a large body of epidemiological data in the published literature remains limited. There is some evidence for an association between EO exposure and lympho/hematopoietic cancer mortality. Of these cancers, the evidence provided by two large cohorts with the longest follow-up is most consistent for leukemia. Together with what is known about human leukemia and EO at the molecular level, there is a body of evidence that supports a plausible mode of action for EO as a potential leukemogen. Based on a consideration of the mode of action, the events leading from EO exposure to the development of leukemia (and therefore risk) are expected to be proportional to the square of the dose. In support of this hypothesis, a quadratic dose-response model provided the best overall fit to the epidemiology data in the range of observation. Cancer dose-response assessments based on human and animal data are presented using three different assumptions for extrapolating to low doses: (1) risk is linearly proportionate to dose; (2) there is no appreciable risk at low doses (margin-of-exposure or reference dose approach); and (3) risk below the point of departure continues to be proportionate to the square of the dose. The weight of evidence for EO supports the use of a nonlinear assessment. Therefore, exposures to concentrations below 37 μg/m3 are not likely to pose an appreciable risk of leukemia in human populations. However, if quantitative estimates of risk at low doses are desired and the mode of action for EO is considered, these risks are best quantified using the quadratic estimates of cancer potency, which are approximately 3.2- to 32-fold lower, using alternative points of departure, than the linear estimates of cancer potency for EO. An approach is described for linking the selection of an appropriate point of departure to the confidence in the proposed mode of action. Despite high confidence in the proposed mode of action, a small linear component for the dose-response relationship at low concentrations cannot be ruled out conclusively. Accordingly, a unit risk value of 4.5 × 10−8 (μg/m3)−1 was derived for EO, with a range of unit risk values of 1.4 × 10−8 to 1.4 × 10−7 (μg/m3)−1 reflecting the uncertainty associated with a theoretical linear term at low concentrations.

Notes: Comparative risk projects can provide broad policy guidance but they rarely have adequate scientific foundations to support precise risk rankings. Many extant projects report rankings anyway, with limited attention to uncertainty. Stochastic uncertainty, structural uncertainty, and ignorance are types of incertitude that afflict risk comparisons. The recently completed New Jersey Comparative Risk Project was innovative in trying to acknowledge and accommodate some historically ignored uncertainties in a substantive manner. This article examines the methods used and lessons learned from the New Jersey project. Monte Carlo techniques were used to characterize stochastic uncertainty, and sensitivity analysis helped to manage structural uncertainty. A deliberative process and a sorting technique helped manage ignorance. Key findings are that stochastic rankings can be calculated but they reveal such an alarming degree of imprecision that the rankings are no longer useful, whereas sorting techniques are helpful in spite of uncertainty. A deliberative process is helpful to counter analytical overreaching.

Notes: Recently, there has been a surge of interest in the role of feelings in framing perceptions and decisions about risk, yet no study has specifically examined the impact of feelings on perceptions/judgments about biotechnology. This exploratory study investigated current perceptions of genetically modified (GM) food to examine (1) the effects of context (making judgments about GM food at the same time as rating other current areas of concern), and (2) the effect of feelings of dread (integral affect) and background feelings of stress (negative incidental affect) on risk judgments about GM food. An established psychometric method (semantic differential task) used with a sample of 126 adults (recruited “topic-blind,” mostly from a student population) showed that, when rated in the context of other current concerns such as human cloning and Creutzfeldt-Jakob disease (CJD), there was less concern about GM food than might have been anticipated. Participants were recruited “topic-blind” in order to ensure that they were unaware that the focus of the research was on GM food specifically (and thus preventing biased recruitment to the study). Relative to 19 other current concerns GM food was “not dreaded,” not viewed as “unethical,” was judged as “controllable,” and was seen as the least “risky” of all the issues studied. GM food was viewed as a “hot topic,” a new risk, and as relatively unnatural (although it was not the highest rated concern on this scale). Ratings of risks across concerns by individuals experiencing high levels of negative incidental affect (stress) did not differ significantly from those reporting low stress.

Notes: This article examines factors that predict perceptions of risk associated with global climate change. The research focuses on the perceptions of those associated with climate change policy making in the prairie region of Canada. The data are from an online survey (n= 851) of those policy actors. The analysis integrates several dominant approaches to the study of risk perception: psychometric approaches that examine the effects of cognitive structure; demographic assessments that examine, for example, differences in perception based on gender or family status; and political approaches that suggest that one's position in the policy process may affect his or her perceived risk. Attitudes toward climate change are to a degree predicted by all of these factors, but only when indirect effects are observed. Sociodemographic characteristics have little direct effect on perceived risk, but do affect general beliefs that affect risk perceptions. Perceived risk is related more strongly to these general beliefs or world views than to more specific beliefs about the effects of climate change on weather patterns. Position within the policy process also contributes to our understanding of perceptions, with industry and governmental actors demonstrating similar attitudes, which contrast with environmental groups and university researchers.

Notes: All else being equal, the faster an invading species spreads, the more dangerous its invasion. The projection of spread rate therefore ought to be a central part of the determination of invasion risk. Originally formulated in the 1970s to describe the spatial spread of advantageous alleles, integrodifference equation (IDE) models have since been co-opted by population biologists to describe the spread of populations. More recently, they have been modified to include population structure and environmental variability. We review how IDE models are formulated, how they are parameterized, and how they can be analyzed to project spread rates and the sensitivity of those rates to changes in model parameters. For illustrative purposes, we apply these models to Cytisus scoparius, a large shrub in the legume family that is considered a noxious invasive species in eastern and western North America, Chile, Australia, and New Zealand.

Notes: This article presents a quantitative methodology for evaluating the probability of invasive pest species establishing persistent populations. The estimation of pest establishment relies on data and information describing the biology and ecology of the pest and its interactions with potential host species and the regional environment. This information is developed using a model construct borrowed from theoretical population ecology. The methodology for estimating the probability of pest establishment is part of an overall framework that explores the implications of reductions in pest invasions on subsequent establishment. The risk reduction framework integrates the engineering aspects of different technologies for reducing pest entry, the biology and ecology of pest species, the suitability of potentially susceptible hosts, and the quality of available habitats. The methodology for estimating the risk of establishment is presented using an example pest, the Asian longhorned beetle (Anoplophora glabripennis), which has been introduced into the United States via solid wood packing materials (SWPM) used in international commerce. Uncertainties inherent to the estimation of model parameters that determine the risk of establishment are defined, quantified, and propagated through the population model. Advantages and limitations of the proposed methodology are discussed along with recommendations to make the approach more useful in the management of risks posed by the establishment of pest populations.

Notes: Although estimates vary, there is a broad agreement that invasive species impose major costs on the U.S. economy, as well as posing risks to nonmarket environmental goods and services and to public health. The domestic effort to manage risks associated with invasive species is coordinated by the National Invasive Species Council (NISC), which is charged with developing a science-based process to evaluate risks associated with the introduction and spread of invasive species. Various international agreements have also elevated invasive species issues onto the international policy agenda. The World Trade Organization (WTO) Sanitary and Phytosanitary (SPS) Agreement establishes rights and obligations to adhere to the discipline of scientific risk assessment to ensure that SPS measures are applied only to the extent required to protect human, animal, and plant health, and do not constitute arbitrary or unjustifiable technical barriers to trade. Currently, however, the field of risk assessment for invasive species is in its infancy. Therefore, there is a pressing need to formulate scientifically sound methods and approaches in this emerging field, while acknowledging that the demand for situation-specific empirical evidence is likely to persistently outstrip supply. To begin addressing this need, the Society for Risk Analysis Ecological Risk Assessment Specialty Group and the Ecological Society of America Theoretical Ecology Section convened a joint workshop to provide independent scientific input into the formulation of methods and processes for risk assessment of invasive species to ensure that the analytic processes used domestically and internationally will be firmly rooted in sound scientific principles.

Notes: This article addresses the application of ecological risk assessment at the regional scale to the prediction of impacts due to invasive or nonindigenous species (NIS). The first section describes risk assessment, the decision-making process, and introduces regional risk assessment. A general conceptual model for the risk assessment of NIS is then presented based upon the regional risk assessment approach. Two diverse examples of the application of this approach are presented. The first example is based upon the dynamics of introduced plasmids into bacteria populations. The second example is the application risk assessment approach to the invasion of a coastal marine site of Cherry Point, Washington, USA by the European green crab. The lessons learned from the two examples demonstrate that assessment of the risks of invasion of NIS will have to incorporate not only the characteristics of the invasive species, but also the other stresses and impacts affecting the region of interest.

Notes: This document is a preliminary report on the role that mathematical and statistical methods might play in the defense against terrorist attacks. In no way does this replace the efforts of law enforcement agenices or intelligence activities. The hope is that mathematical techniques can make their efforts more efficient. The ideas enumerated here utilize the notion of probabilistic risk analysis, which was developed for the purpose of assessing the safety of nuclear reactors, as well as randomization and game theory. More extensive work in these directions is contemplated for the future. The author is planning workshops to evaluate the ideas presented here and to elicit additional methodologies that may prove useful in this endeavor.

Notes: Inuit populations meet a large portion of their food needs by eating country food in which pollutants are concentrated. Despite the fact that they contain pollutants, the consumption of country food has many health, social, economic, and cultural benefits. A risk determination process was set up in order to help regional health authorities of Nunavik to deal with this particular issue. Based on Nunavik health authorities' objectives to encourage the region's inhabitants to change their dietary habits, and on both the risks and the benefits of eating country food, several management options were developed. The options aimed at reducing exposure to contaminants by either substituting certain foods with others that have a lower contaminant content or by store-bought foods. This article aims at assessing the potential economic impact of these risk management options before being implemented. Relevant economic data (aggregate income and monetary outlays for the purchase of food and equipment required for food production by households) were collected and identified to serve as a backdrop for the various replacement scenarios. Results show that household budgets, and the regional economy, are not significantly affected by the replacement of contaminated foods with the purchase of store-bought meat, and even less so if the solution involves replacing contaminated foods with other types of game hunted in the region. When financial support is provided by the state, the households can even gain some monetary benefits. Results show that public health authorities' recommended changes to dietary habits among the Inuit of Nunavik would not necessarily involve economic constraints for Inuit households.

Notes: Ongoing publicity about methyl tertiary butyl ether (MTBE) suggests that this chemical is of greater concern than other contaminants commonly found in drinking water. The purpose of this article is to evaluate the available MTBE data in context with other volatile organic compounds (VOCs) that are detected in public drinking water sources in California. We find that of the 28 VOCs with a primary maximum contaminant level (MCL) in California, 21 were found in 50 or more drinking water sources from 1985 to 2002. Over the last 10 years, the most frequently detected VOCs were chloroform, tetrachloroethylene (PCE), and trichloroethylene (TCE), which were found in about 9–15% of all sampled drinking water sources. These same chemicals were found to have the highest mean detected concentrations over the last 5 years, ranging from 13 to 15 μg/L. Many VOCs were also found to routinely exceed state and federal drinking water standards, including benzene and carbon tetrachloride. By comparison, MTBE was found in approximately 1% of sampled drinking water sources for most years, and of those drinking water sources found to contain MTBE from 1998 to 2002, over 90% had detected concentrations below California's primary MCL of 13 μg/L. Relative to the other VOCs evaluated, MTBE has the lowest estimated California cancer potency value, and was found to pose one of the least cancer risks from household exposures to contaminated drinking water. These findings suggest that MTBE poses an insignificant threat to public drinking water supplies and public health in California, particularly when compared to other common drinking water contaminants.

Notes: The analysis of risk-return tradeoffs and their practical applications to portfolio analysis paved the way for Modern Portfolio Theory (MPT), which won Harry Markowitz a 1992 Nobel Prize in Economics. A typical approach in measuring a portfolio's expected return is based on the historical returns of the assets included in a portfolio. On the other hand, portfolio risk is usually measured using volatility, which is derived from the historical variance-covariance relationships among the portfolio assets. This article focuses on assessing portfolio risk, with emphasis on extreme risks. To date, volatility is a major measure of risk owing to its simplicity and validity for relatively small asset price fluctuations. Volatility is a justified measure for stable market performance, but it is weak in addressing portfolio risk under aberrant market fluctuations. Extreme market crashes such as that on October 19, 1987 (“Black Monday”) and catastrophic events such as the terrorist attack of September 11, 2001 that led to a four-day suspension of trading on the New York Stock Exchange (NYSE) are a few examples where measuring risk via volatility can lead to inaccurate predictions. Thus, there is a need for a more robust metric of risk. By invoking the principles of the extreme-risk-analysis method through the partitioned multiobjective risk method (PMRM), this article contributes to the modeling of extreme risks in portfolio performance. A measure of an extreme portfolio risk, denoted by f4, is defined as the conditional expectation for a lower-tail region of the distribution of the possible portfolio returns. This article presents a multiobjective problem formulation consisting of optimizing expected return and f4, whose solution is determined using Evolver—a software that implements a genetic algorithm. Under business-as-usual market scenarios, the results of the proposed PMRM portfolio selection model are found to be compatible with those of the volatility-based model. However, under extremely unfavorable market conditions, results indicate that f4 can be a more valid measure of risk than volatility.

Notes: The siting of nuclear waste facilities has been very difficult in all countries. Recent experience in Sweden indicates, however, that it may be possible, under certain circumstances, to gain local support for the siting of a high-level nuclear waste (HLNW) repository. The article reports on a study of attitudes and risk perceptions of people living in four municipalities in Sweden where HLNW siting was being intensely discussed at the political level, in media, and among the public. Data showed a relatively high level of consensus on acceptability of at least further investigation of the issue; in two cases local councils have since voted in favor of a go-ahead, and in one case only a very small majority defeated the issue. Models of policy attitudes showed that these were related to attitude to nuclear power, attributes of the perceived HLNW risk, and trust. Factors responsible for acceptance are discussed at several levels. One is the attitude to nuclear power, which is becoming more positive, probably because no viable alternatives are in sight. Other factors have to do with the extensive information programs conducted in these municipalities, and with the logical nature of the conclusion that they would be good candidates for hosting the national HLNW repository.

Notes: Following the attacks of September 11, 2001, the Environmental Protection Agency and other government agencies removed information from their websites that they feared could invite attacks on critical public and private infrastructure. Accordingly, the benefits and costs of environmental information disclosure programs have come under increasing scrutiny. This article describes a framework for examining these benefits and costs and illustrates the framework through brief case studies of two information disclosure programs: risk management planning and materials accounting. The article outlines what we know and still need to find out about information disclosure programs in order to appropriately balance benefits and costs.

Notes: This article reports an extension of the Carnegie Mellon risk-ranking method to incorporate ecological risks and their attributes. On the basis of earlier risk-perception studies, we identified a set of 20 relevant attributes for describing health, safety, and environmental hazards in standardized risk summary sheets. In a series of three ranking sessions, 23 laypeople ranked 10 such hazards in a fictional Midwestern U.S. county using both holistic and multiattribute ranking procedures. Results were consistent with those from previous studies involving only health and safety hazards, providing additional evidence for the validity of the method and the replicability of the resulting rankings. Holistic and multiattribute risk rankings were reasonably consistent both for individuals and for groups. Participants reported that they were satisfied with the procedures and results, and indicated their support for using the method to advise real-world risk-management decisions. Agreement among participants increased over the course of the exercise, perhaps because the materials and deliberations helped participants to correct their misconceptions and clarify their values. Overall, health and safety attributes were judged more important than environmental attributes. However, the overlap between the importance rankings of these two sets of attributes suggests that some information about environmental impacts is important to participants’ judgments in comparative risk-assessment tasks.

Notes: This article provides a brief critical examination of a 2002 report jointly issued by the World Health Organization and the World Trade Organization on WTO law and public health. The author argues that the report is in many respects misleading as to the content of WTO law, as interpreted by the Appellate Body of the WTO, its final court. In particular, the WHO/WTO report systematically understates or underestimates the margins of regulatory autonomy that WTO member states have to make regulations that protect public health.

Notes: The World Trade Organization is currently evolving its approach to incorporating scientific and technological evidence into its dispute-resolution process. In European Communities—Measures Affecting Asbestos and Asbestos-Containing Products, the Panel was faced with a large amount of complex and conflicting scientific evidence presented by the partisan experts. The Asbestos Panel's solution was to appoint independent, nonpartisan experts to help it understand and evaluate the scientific evidence. While this was far better than trying to unravel the conflicting scientific evidence on its own, two aspects of the Panel's adopted procedure merit scrutiny. First, the expert-selection process used by the Panel may not assure that the collective expertise of the appointed experts is broad enough when the dispute involves multidisciplinary scientific issues. Second, the process adopted by the Panel for consulting the appointed experts—which involved individual consultation rather than a consensus process—may leave a panel with a distorted or confused picture of the science. A consensus approach is the best means of obtaining scientific advice from appointed experts; it is most calculated to provide a clear and accurate report of the scientific information needed by a panel to make a fair and informed decision on the dispute before it. The underlying principle of world trade agreements is that it is beneficial to all of us to have free trade. Among other things, this requires an effective means of resolving disputes, and increasingly that includes disputes involving complex scientific and technological issues. This can be achieved only if the parties have confidence that their disputes will be decided in a fair and informed manner, based on the best science available. To achieve this goal, we suggest that future WTO panels depart in certain respects from the procedures utilized by the Asbestos Panel.

Notes: Twenty-four-hour recall data from the Continuing Survey of Food Intake by Individuals (CSFII) are frequently used to estimate dietary exposure for risk assessment. Food frequency questionnaires are traditional instruments of epidemiological research; however, their application in dietary exposure and risk assessment has been limited. This article presents a probabilistic method of bridging the National Health and Nutrition Examination Survey (NHANES) food frequency and the CSFII data to estimate longitudinal (usual) intake, using a case study of seafood mercury exposures for two population subgroups (females 16 to 49 years and children 1 to 5 years). Two hundred forty-nine CSFII food codes were mapped into 28 NHANES fish/shellfish categories. FDA and state/local seafood mercury data were used. A uniform distribution with minimum and maximum blood-diet ratios of 0.66 to 1.07 was assumed. A probabilistic assessment was conducted to estimate distributions of individual 30-day average daily fish/shellfish intakes, methyl mercury exposure, and blood levels. The upper percentile estimates of fish and shellfish intakes based on the 30-day daily averages were lower than those based on two- and three-day daily averages. These results support previous findings that distributions of “usual” intakes based on a small number of consumption days provide overestimates in the upper percentiles. About 10% of the females (16 to 49 years) and children (1 to 5 years) may be exposed to mercury levels above the EPA's RfD. The predicted 75th and 90th percentile blood mercury levels for the females in the 16-to-49-year group were similar to those reported by NHANES. The predicted 90th percentile blood mercury levels for children in the 1-to-5-year subgroup was similar to NHANES and the 75th percentile estimates were slightly above the NHANES.

Notes: Hormetic effects have been observed at low exposure levels based on the dose-response pattern of data from developmental toxicity studies. This indicates that there might actually be a reduced risk of exhibiting toxic effects at low exposure levels. Hormesis implies the existence of a threshold dose level and there are dose-response models that include parameters that account for the threshold. We propose a function that introduces a parameter to account for hormesis. This function is a subset of the set of all functions that could represent a hormetic dose-response relationship at low exposure levels to toxic agents. We characterize the overall dose-response relationship with a piecewise function that consists of a hormetic u-shape curve at low dose levels and a logistic curve at high dose levels. We apply our model to a data set from an experiment conducted at the National Toxicology Program (NTP). We also use the beta-binomial distribution to model the litter response data. It can be seen by observing the structure of these data that current experimental designs for developmental studies employ a limited number of dose groups. These designs may not be satisfactory when the goal is to illustrate the existence of hormesis. In particular, increasing the number of low-level doses improves the power for detecting hormetic effects. Therefore, we also provide the results of simulations that were done to characterize the power of current designs in detecting hormesis and to demonstrate how this power can be improved upon by altering these designs with the addition of only a few low exposure levels.

Notes: Regional estimates of cryptosporidiosis risks from drinking water exposure were developed and validated, accounting for AIDS status and age. We constructed a model with probability distributions and point estimates representing Cryptosporidium in tap water, tap water consumed per day (exposure characterization); dose response, illness given infection, prolonged illness given illness; and three conditional probabilities describing the likelihood of case detection by active surveillance (health effects characterization). The model predictions were combined with population data to derive expected case numbers and incidence rates per 100,000 population, by age and AIDS status, borough specific and for New York City overall in 2000 (risk characterization). They were compared with same-year surveillance data to evaluate predictive ability, assumed to represent true incidence of waterborne cryptosporidiosis. The predicted mean risks, similar to previously published estimates for this region, overpredicted observed incidence—most extensively when accounting for AIDS status. The results suggest that overprediction may be due to conservative parameters applied to both non-AIDS and AIDS populations, and that biological differences for children need to be incorporated. Interpretations are limited by the unknown accuracy of available surveillance data, in addition to variability and uncertainty of model predictions. The model appears sensitive to geographical differences in AIDS prevalence. The use of surveillance data for validation and model parameters pertinent to susceptibility are discussed.

Notes: Within the risk literature there is an ongoing debate on whether trust is vulnerable or enduring. Previous research on nuclear energy by Slovic in 1993 has shown that negative events have much greater impact on self-reported trust than do positive events. Slovic attributes this to the asymmetry principle: specifically, that trust is much easier to destroy than to create. In a questionnaire survey concerning genetically modified (GM) food in Britain (n= 396) we similarly find that negative events have a greater impact on trust than positive events. Because public opinion in Britain is skewed in the direction of opposition toward GM food, the pattern of results could either be caused by the fact that negative information is more informative than positive information (a negativity bias) or reflect the influence of people's prior attitudes toward the issue (a confirmatory bias). The results were largely in line with the confirmatory bias hypothesis: participants with clear positive or negative beliefs interpreted events in line with their existing attitude position. However, for participants with intermediate attitudes, negative items still had greater impact than the positive. This latter finding suggests that, congruent with the negativity bias hypothesis, negative information may still be more informative than positive information for undecided people. The study also identified the labeling of GM products, consulting the public, making biotechnology companies liable for any damage, and making a test available to detect GM produce as being particularly important preconditions for maintaining trust in the regulation of agricultural biotechnology.

Notes: Adverse events in hospitals, such as in surgery, anesthesia, radiology, intensive care, internal medicine, and pharmacy, are of worldwide concern and it is important, therefore, to learn from such incidents. There are currently no appropriate tools based on state-of-the art models available for the analysis of large bodies of medical incident reports. In this study, a new model was developed to facilitate medical error analysis in combination with quantitative risk assessment. This model enables detection of the organizational factors that underlie medical errors, and the expedition of decision making in terms of necessary action. Furthermore, it determines medical tasks as module practices and uses a unique coding system to describe incidents. This coding system has seven vectors for error classification: patient category, working shift, module practice, linkage chain (error type, direct threat, and indirect threat), medication, severity, and potential hazard. Such mathematical formulation permitted us to derive two parameters: error rates for module practices and weights for the aforementioned seven elements. The error rate of each module practice was calculated by dividing the annual number of incident reports of each module practice by the annual number of the corresponding module practice. The weight of a given element was calculated by the summation of incident report error rates for an element of interest. This model was applied specifically to nursing practices in six hospitals over a year; 5,339 incident reports with a total of 63,294,144 module practices conducted were analyzed. Quality assurance (QA) of our model was introduced by checking the records of quantities of practices and reproducibility of analysis of medical incident reports. For both items, QA guaranteed legitimacy of our model. Error rates for all module practices were approximately of the order 10-4 in all hospitals. Three major organizational factors were found to underlie medical errors: “violation of rules” with a weight of 826 × 10−4, “failure of labor management” with a weight of 661 × 10−4, and “defects in the standardization of nursing practices” with a weight of 495 × 10−4.

Notes: Over the past 20 years, several epidemiological studies have found an association between exposure to electromagnetic fields (EMFs) and health effects, including childhood leukemia and adult brain cancer. However, experts strongly disagree about whether this association is causal and, if so, how strong it is. In this article, we examine several alternatives to reduce EMFs from sources of the California power grid, including undergrounding distribution and transmission lines and reconfiguring or rephasing lines. The alternatives were evaluated in terms of the potential health risk reduction, cost, impacts on service reliability, property values, and many other consequences. Because of the uncertainty about an EMF-health link, the main effort was to determine the sensitivity of the decisions to the probability and seriousness of an EMF hazard. User-friendly computer models were developed to allow stakeholders to change the model assumptions and parameters to analyze the impacts of their own assumptions and estimates on the decision. The analysis clearly demonstrated that only four of the many concerns raised by the stakeholders could make a difference in the decision: health risks, costs, service reliability, and property values. Whether undergrounding, moderate alternatives for EMF reduction, or no change was the best decision depended on a few key factors, including the probability that EMF exposure is a hazard, the severity of this hazard, how the EMF reduction measures are financed, and the impacts on property values. While the analysis did not resolve the EMF issues, it showed that even in the most controversial settings, a little analysis goes a long way to clarifying the issues and to focus the debate.

Notes: The management of natural- and human-induced wildland fires is an intricate process that must balance two considerations: that of fire as a necessary natural disturbance and that of the risks that fire poses. Reconciling tradeoffs between these risks and benefits is contingent upon informed, directed, and two-way communication between wildland fire managers and stakeholders. In an effort to aid with the design of such a communication effort, this study used mental models research to determine the unique wildland fire information and decision-making needs of stakeholders living at the wildland-urban interface of a fire-prone area. While the analysis revealed many similarities in how stakeholders conceptualized the risks and benefits of wildland fire, many misconceptions and important gaps in understanding on the part of both expert and nonexpert respondents were identified.

Notes: A wide variety of tools are available, both parametric and nonparametric, for analyzing spatial data. However, it is not always clear how to translate statistical inferences into decision recommendations. This article explores the possibilities of estimating the effects of decision options using very direct manipulation of data, bypassing formal statistical analysis. We illustrate with the application that motivated this research, a study of arsenic in drinking water in nearly 5,000 wells in a small area in rural Bangladesh. We estimate the potential benefits of two possible remedial actions: (1) recommendations that people switch to nearby wells with lower arsenic levels; and (2) drilling new community wells. We use simple nonparametric clustering methods and estimate uncertainties using cross-validation.

Notes: This article presents a process for an integrated policy analysis that combines risk assessment and benefit-cost analysis. This concept, which explicitly combines the two types of related analyses, seems to contradict the long-accepted risk analysis paradigm of separating risk assessment and risk management since benefit-cost analysis is generally considered to be a part of risk management. Yet that separation has become a problem because benefit-cost analysis uses risk assessment results as a starting point and considerable debate over the last several years focused on the incompatibility of the use of upper bounds or “safe” point estimates in many risk assessments with benefit-cost analysis. The problem with these risk assessments is that they ignore probabilistic information. As advanced probabilistic techniques for risk assessment emerge and economic analysts receive distributions of risks instead of point estimates, the artificial separation between risk analysts and the economic/decision analysts complicates the overall analysis. In addition, recent developments in countervailing risk theory suggest that combining the risk and benefit-cost analyses is required to fully understand the complexity of choices and tradeoffs faced by the decisionmaker. This article also argues that the separation of analysis and management is important, but that benefit-cost analysis has been wrongly classified into the risk management category and that the analytical effort associated with understanding the economic impacts of risk reduction actions need to be part of a broader risk assessment process.

Notes: In December 2000 the EPA initiated the Voluntary Children's Chemical Evaluation Program (VCCEP) by asking manufacturers to voluntarily sponsor toxicological testing in a tiered process for 23 chemicals selected for the pilot phase. The tiered nature of the VCCEP pilot program creates the need for clearly defined criteria for determining when information is sufficient to assess the potential risks to children. This raises questions about how to determine the “adequacy” of the existing information and assess the need to undertake efforts to reduce uncertainty (through further testing). This article applies a value of information analysis approach to determine adequacy by modeling how toxicological and exposure data collected through the VCCEP may be used to inform risk management decisions. The analysis demonstrates the importance of information about the exposure level and control costs in making decisions regarding further toxicological testing. This article accounts for the cost of delaying control action and identifies the optimal testing strategy for a constrained decisionmaker who, absent applicable human data, cannot regulate without bioassay data on a specific chemical. It also quantifies the differences in optimal testing strategy for three decision criteria: maximizing societal net benefits, ensuring maximum exposure control while net benefits are positive (i.e., benefits outweigh costs), and controlling to the maximum extent technologically feasible while the lifetime risk of cancer exceeds a specific level of risk. Finally, this article shows the large differences that exist in net benefits between the three criteria for the range of exposure levels where the optimal actions differ.

Notes: Nuclear waste cleanup is a challenging and complex problem that requires both scientific analysis and dialogue among a variety of stakeholders. This article describes an effort to develop an online information system that supports this analytic-deliberative dialogue by integrating cleanup information for the Hanford Site, and making it more “transparent.” A framework for understanding and evaluating transparency guided system development. Working directly with stakeholders, we identified information needs and developed new ways to organize and present the information so that it would be more transparent to interested parties, with the ultimate aim of fostering greater participation in decision dialogues and processes. The complexity of the information needed for dialogue suggested that several types of communication devices (“information structures”) were warranted. Five information structures were developed for the pilot Decision Mapping System (). Decision maps hyperlinked decision information to maps of Hanford. Background Information provided context in a narrative format. Decision Paths organized decision process information on a timeline and provided direct hyperlinks to online documentation. The Geographic Library hyperlinked decision documents to maps. Finally, a Discussion Forum allowed users to make comments and view remarks from others. Early lessons from this work suggest that transparency is integral to long-term management, a participatory design process contributed greatly to its perceived success, and better data integration to support decision making is needed. This work has broad implications for risk communicators and risk managers because it speaks to the design of information systems to support “analytic-deliberative” decision processes (i.e., those that rely upon both risk science and public dialogue).

Notes: Fresh ground water is widely distributed in subsurface sediments below the coastal bays of the Delmarva Peninsula (Delaware, Maryland, and Virginia). These conditions were revealed by nearly 300 km of streamer resistivity surveys, utilizing a towed multichannel cable system. Zones of high resistivity displayed by inversion modeling were confirmed by vibradrilling investigations to correspond to fresh ground water occurrences. Fresh water lenses extended from a few hundred meters up to 2 km from shore. Along the western margins of coastal bays in areas associated with fine-grained surficial sediments, high-resistivity layers were widespread and were especially pronounced near tidal creeks. Fresh ground water layers were less common along the eastern barrier-bar margins of the bays, where sediments were typically sandy. Mid-bay areas in Chincoteague Bay, Maryland, did not show evidence of fresh water. Indian River Bay, Delaware, showed complex subsurface salinity relationships, including an area with possible hypersaline brines. The new streamer resistivity system paired with vibradrilling in these investigations provides a powerful approach to recovering information required for extension of hydrologic modeling of shallow coastal aquifer systems into offshore areas.

Notes: Rates of ground water recharge and discharge are not well known in the central Everglades. Here we report estimates of ground water recharge and discharge at 15 sites in the Everglades Nutrient Removal Project and in Water Conservation Area 2A (WCA-2A), along with measurements of hydraulic properties of peat at 11 sites. A simple hydrogeologic simulation was used to assess how specific factors have influenced recharge and discharge. Simulations and measurements agreed that the highest values of recharge and discharge occur within 600 m of levees, the result of ground water flow beneath levees. There was disagreement in the interior wetlands of WCA-2A (located 〉 1000 m from levees) where measurements of recharge and discharge were substantially higher than simulated fluxes. A five-year time series (1997 to 2002) of measured fluxes indicated that recharge and discharge underwent reversals in direction on weekly, monthly, and annual timescales at interior sites in WCA-2A. Ground water discharge tended to occur during average to moderately dry conditions when local surface water levels were decreasing. Recharge tended to occur during moderately wet periods or during very dry periods just as water levels began to increase following precipitation or in response to a pulse of surface water released from water-control structures by water managers. Discharge also tended to occur at sites in the wetland interior for ∼1 week preceding the arrival of the surface water pulse. We conclude that ground water recharge and discharge vary cyclically in the interior wetlands of the central Everglades, driven by the differential responses of surface water and ground water to annual, seasonal, and weekly trends in precipitation and operation of water-control structures.

Notes: Despite the central management of Israel's water resources and the highly planned strategy for a sustainable water supply, Israel has twice faced an acute water crisis during the past decade. Although the visible problem is related to a lack of additional quantities of water, the deterioration of water quality appears to be endangering the future use of available water quantities as well. A long-term policy of ground water mining (translated to salt water encroachments), and irrigation with relatively saline water and recycled waste water, among other damage, account for this deterioration. Enhanced flushing of the salt and contaminant load from the aquifers (using various techniques) is proposed as a solution to the problem.

Notes: Predicting the future performance of horizontal wells under varying pumping conditions requires estimates of basic aquifer parameters, notably transmissivity and storativity. For vertical wells, there are well-established methods for estimating these parameters, typically based on either the recovery from induced head changes in a well or from the head response in observation wells to pumping in a test well. Comparable aquifer parameter estimation methods for horizontal wells have not been presented in the ground water literature. Formation parameter estimation methods based on measurements of pressure in horizontal wells have been presented in the petroleum industry literature, but these methods have limited applicability for ground water evaluation and are based on pressure measurements in only the horizontal well borehole, rather than in observation wells. This paper presents a simple and versatile method by which pumping test procedures developed for vertical wells can be applied to horizontal well pumping tests. The method presented here uses the principle of superposition to represent the horizontal well as a series of partially penetrating vertical wells. This concept is used to estimate a distance from an observation well at which a vertical well that has the same total pumping rate as the horizontal well will produce the same drawdown as the horizontal well. This equivalent distance may then be associated with an observation well for use in pumping test algorithms and type curves developed for vertical wells. The method is shown to produce good results for confined aquifers and unconfined aquifers in the absence of delayed yield response. For unconfined aquifers, the presence of delayed yield response increases the method error.

Notes: Flow of nonvolatile nonaqueous phase liquid (NAPL) and aqueous phases that account for mobile, entrapped, and residual NAPL in variably saturated water-wet porous media is modeled and compared against results from detailed laboratory experiments. Residual saturation formation in the vadose zone is a process that is often ignored in multifluid flow simulators, which might cause an overestimation of the volume of NAPL that reaches the ground water. Mobile NAPL is defined as being continuous in the pore space and flows under a pressure gradient or gravitational body force. Entrapped NAPL is defined as being occluded by the aqueous phase, occurring as immobile ganglia surrounded by aqueous phase in the pore space and formed when NAPL is replaced by the aqueous phase. Residual NAPL is defined as immobile, nonwater entrapped NAPL that does not drain from the pore spaces and is conceptualized as being either continuous or discontinuous. Free NAPL comprises mobile and residual NAPL. The numerical model is formulated on mass conservation equations for oil and water, transported via NAPL and aqueous phases through variably saturated porous media. To account for phase transitions, a primary variable switching scheme is implemented for the oil-mass conservation equation over three phase conditions: (1) aqueous or aqueous-gas with dissolved oil, (2) aqueous or aqueous-gas with entrapped NAPL, and (3) aqueous or aqueous gas with free NAPL. Two laboratory-scale column experiments are modeled to verify the numerical model. Comparisons between the numerical simulations and experiments demonstrate the necessity to include the residual NAPL formation process in multifluid flow simulators.

Notes: Land subsidence due to subsurface fluid (water, gas, oil) withdrawal is often predicted by either finite element or finite difference numerical models based on coupled poroelastic theory, where the soil is represented as a semi-infinite medium bounded by the traction-free (ground) surface. One of the variables playing a most important role on the final outcome is the flow condition used on the traction-free boundary, which may be assumed as either permeable or impermeable. Although occasionally justified, the assumption of no-flow surface seems to be in general rather unrealistic. A permeable boundary where the fluid pressure is fixed to the external atmospheric pressure appears to be more appropriate. This paper addresses the response, in terms of land subsidence, obtained with a coupled poroelastic finite element model that simulates a distributed pumping from a horizontal aquifer confined between two relatively impervious layers, and takes either a permeable boundary surface, i.e., constant hydraulic potential, or an impermeable boundary, i.e., a zero Neumann flow condition. The analysis reveals that land subsidence is rather sensitive to the flow condition implemented on the traction-free boundary. In general, the no-flow condition leads to an overestimate of the predicted ground surface settlement, which could even be 1 order of magnitude larger than that obtained with the permeable boundary.

Notes: An experiment was conducted to determine if biodegradation of trichloroethylene (TCE) can occur in previously uncontaminated ground water in saturated fractured saprolite (highly weathered material derived from sedimentary rocks). Two undisturbed columns (0.23 m diameter by 0.25 m long) of fractured saprolite were collected from ∼2 m depth at an uncontaminated site on the Oak Ridge Reservation, Oak Ridge, Tennessee. Natural, uncontaminated ground water from the site, which was degassed and spiked with dissolved phase TCE, was continuously pumped through one column containing the natural microbial communities (the biotic column). In a second column, the microorganisms were inhibited and the dissolved phase TCE was added under aerobic conditions (dissolved oxygen conditions 〉 2 ppm). In effluent from the biotic column, reducing conditions rapidly developed and evidence of anaerobic biodegradation of TCE, by the production of cDCE, first appeared ∼31 days after addition of TCE. Reductive dechlorination of TCE occurred after iron-reducing conditions were established and about the same time that sulfate reduction began. There was no evidence of methanogenesis. Analyses using polymerase chain reaction with specific primers sets detected the bacteria Geothrix, Geobacter, and Desulfococcus-Desulfonema-Desulfosarcina in the effluent of the biotic column, but no methanogens. The presence of these bacteria is consistent with iron- and sulfate-reducing conditions. In the inhibited column, there were no indicators of TCE degradation. Natural organic matter that occurs in the saprolite and ground water at the site is the most likely primary electron donor for supporting reductive dechlorination of TCE. The relatively rapid appearance of indicators of TCE dechlorination suggests that these processes may occur even in settings where low oxygen conditions occur seasonally due to changes in the water table.

Notes: A number of methods involving indicator geostatistics were combined in a methodology for characterizing and modeling multiscale heterogeneity. The methodology circumvents sources of bias common in data from borehole logs. We applied this methodology to the complex heterogeneity within a regional system of buried valley aquifers, which occurs in the western glaciated plains of North America and includes the Spiritwood Aquifer. The region is conceptualized as having a hierarchical organization with three facies assemblage types (large-scale heterogeneity) and two facies types within each assemblage (small-scale heterogeneity). We statistically characterized the sedimentary architecture at both scales, formulated indicator correlation models from those characterizations, and used the models to simulate the architecture in a multiscale realization. We focused on the interconnectivity of units creating higher-permeability pathways. Higher-permeability pathways span the realization even though the proportion of higher-permeability facies is less than the percolation threshold. Thus, geologic structures as represented in the indicator correlation models create interconnectivity above that which would occur if the higher-permeability facies were randomly placed. This amount of interconnection among higher-permeability facies within the multiscale realization is consistent with that suggested in prior hydraulic and geochemical studies of the regional system.

Notes: We examined a large (240 km2) northern Appalachian bituminous coal basin (Irwin Syncline, Westmoreland County, Pennsylvania) comprising 27 mine complexes with nine major (〉 2.5 × 103 L/min) discharges. The synclinal basin was divided into seven subbasins based on equilibrium hydraulic relationships established during the past 25 years. Recharge rates, mine pool velocity, and residence times respond to hydraulic changes in the overburden induced by mine subsidence. The estimated maximum depth for subsidence fractures is 60 m (30 times mined thickness) with recharge rates decreasing significantly in subbasins with thicker overburden (〉 75 m). Calculated subbasin recharge rates range from 2 to 6 × 10−4 L/min/m2 and are significantly lower than the previously used rate for the basin. Residence time of ground water in the Irwin subbasins calculated using average linear velocity ranged from one to five years and were more consistent with field observations than estimates obtained using discharge and basin volume area. A positive correlation (r2= 0.80) exists between net alkalinity of the mine water-impacted discharges and residence time in the mine pools. Our results for the Irwin coal basin suggest that use of a subbasin approach incorporating overburden depth, mining methodology, and the extent of postmining inundation will lead to improved determination of ground water flow parameters in mined watersheds in northern Appalachia and elsewhere.

Notes: Flow from some springs in former glacial lakebeds of the Upper Midwest is extremely steady throughout the year and does not increase significantly after precipitation events or seasonal recharge. Analytical and simplified numerical models of spring systems were used to determine whether preferential ground water flow through high-permeability features in shallow sandstone aquifers could produce typical values of spring discharge and the unusually steady rates of spring flow. The analytical model is based on a one-dimensional solution for periodic ground water flow. Solutions to this model suggest that it is unlikely that a periodic forcing due to seasonal variations in areal recharge would propagate to springs in a setting where high-permeability features exist. The analytical model shows that the effective length of the aquifer, or the length of flowpaths to a spring, and the total transmissivity of the aquifer have the greatest potential to impact the nature of spring flow in this setting. The numerical models show that high-permeability features can influence the magnitude of spring flow and the results demonstrate that the lengths of ground water flowpaths increase when high-permeability features are explicitly modeled, thus decreasing the likelihood for temporal variations in spring flow.

Notes: This investigation was undertaken to develop an integrated method of downhole fracture characterization using a tracer. The method presented can be used to locate water-bearing fractures that intersect the well, to determine the ambient fracture flow rate and hydraulic head, and to calculate fracture transmissivity. The method was tested in two fractured crystalline bedrock wells located at the University of Connecticut in Storrs. The method entails injecting a tracer (uranine dye) into the well, while at the same time water is pumped out of the well. After steady-state conditions are reached, a borehole tracer concentration profile is developed. The dilution of the tracer is used to locate the inflowing fractures and to determine their flow rate. The fracture flow rate, plus the drawdown in the well, is then used to determine the fracture hydraulic head, transmissivity, and ambient flow rate.

Notes: A key factor in the long-term viability of aquifer storage recovery (ASR) is the extent of mineral solution interaction between two dissimilar water types and consequent impact on water quality and aquifer stability. We collected geochemical and isotopic data from three observation wells located 25, 65, and 325 m from an injection well at an experimental ASR site located in a karstic, confined carbonate aquifer in South Australia. The experiment involved five major injection cycles of a total of 2.5 × 105 m3 of storm water (total dissolved solids [TDS] ∼ 150 mg/L) into the brackish (TDS ∼2400 mg/L) aquifer. ∼60% of the mixture was pumped out during the fifth year of the experiment. The major effect on water quality within a 25 m radius of the injection well following injection of storm water was carbonate dissolution (35 ± 6 g of CaCO3 dissolved/m3 of aquifer) and sulfide mineral oxidation (50 ± 10 g as FeS2/m3 after one injection). 〈 0.005% of the total aquifer carbonate matrix was dissolved during each injection event, and ∼0.2% of the total reduced sulfur. Increasing amounts of ambient ground water was entrained into the injected mixture during each of the storage periods. High 14CDIC activities and slightly more negative δ13CDIC values measured immediately after injection events show that substantial CO2(aq) is produced by oxidation of organic matter associated with injectant. There were no detectable geochemical reactions while pumping during the recovery phase in the fifth year of the experiment.

Notes: Numerical experiments with steady-state ground water flow models show that spiraling flow lines occur in layered aquifers that have different anisotropic horizontal hydraulic conductivities in adjacent layers. Bundles of such flow lines turning in the same direction can be referred to as ground water whirls. An anisotropic layered block in a field of uniform horizontal flow results in one or more whirls with their axes in the uniform flow direction. The number of whirls depends on the number of interfaces between layers with different anisotropic properties. For flow to a well in an aquifer consisting of two anisotropic layers, with perpendicular major principal directions, whirls are found to occur in quadrants that are bounded by the principal directions of the hydraulic conductivity. The combined effect of flow to a well and a layered anisotropy implies that a single well in a system with a single anisotropic layer within an otherwise isotropic aquifer causes eight whirls. All adjacent whirls rotate in opposite directions.

Notes: Desorption is one of the most critical processes affecting the effectiveness of soil and ground water remediation. None of the currently adopted desorption models can accurately quantify desorption of low-hydrophobicity organic chemicals, and thus could potentially mislead remediation design and decision-making. A recently developed dual-equilibrium desorption (DED) model was found to be much more accurate in quantifying desorption. A screening-level transport model, DED-Transport, was developed to simulate the DED effect on behaviors of organic contaminant plumes during remediation. DED-Transport requires only simple parameters, but is applicable to many remediation scenarios. DED-Transport can be used as a decision-support tool in site remediation to more precisely predict the time required for cleanup.

Notes: Adverse impacts on the health of some fish populations, such as skewed sex distributions, have been noted in surface waters and in laboratory experiments with relatively low concentrations (above 25 ng/L) of natural estrogen (17 β-estradiol—E2). Sources of E2 to surface and ground waters can include avian, human, and mammalian waste products. The Ozark Plateau Aquifer (OPA) is a karstic basin that receives a significant portion of its water through losing reaches of rivers. Thus, there is a direct connection between surface water and ground water. The OPA was targeted for an E2 study to assess the potential for adverse health effects to aquatic organisms living in the system. Eight springs, which drain the aquifer, were sampled quarterly. The concentrations of E2 in the OPA ranged from 13 to 80 ng/L. For any one sampling event, the concentrations of E2 at the spring waters were statistically similar; however, the concentrations of E2 at all springs varied throughout the year. At Maramec Spring, one of the larger springs, the E2 concentration, was correlated with discharge. Based on the correlation between discharge and E2 concentration, aquatic organisms living in the plateau or in its discharged waters, including the threatened southern cavefish T. subterraneus, are exposed to concentration of E2 above 25 ng/L ∼60% of the time. This implies that organisms living in karst basins throughout the OPA are likely exposed to E2 concentrations that may adversely impact their reproductive success for a significant portion of each year.

Notes: In this study, we use borehole temperature data and stable isotopes to delineate the flow system and estimate the effect of urbanization in the Nagaoka area of Japan. Temperature profiles were measured four times in observation wells during the period 2000–2001 and compared with those measured in the same wells during the period 1977–1983 (Taniguchi 1986). Water was sampled in both observation and pumping wells during the same period. The temporal and spatial variability in temperature indicate clearly the effect of urban warming and heavy pumping on the ground water system. Urban warming caused higher temperatures recently as compared to the older values, and pumping caused induced recharge from the river to the ground water. The stable isotope data show the ground water flow system is divided into shallow, intermediate, and deep systems, and that land use and infiltration rate are affecting the shallow flow system.

Notes: This paper describes a series of experiments that tested the ability of the electrical resistivity tomography (ERT) method to locate correctly wet and dry fractures in a meso-scale model. The goal was to develop a method of monitoring the flow of water through a fractured rock matrix.The model was a four by six array of limestone blocks equipped with 28 stainless steel electrodes. Dry fractures were created by placing pieces of vinyl between one or more blocks. Wet fractures were created by injecting tap water into a joint between blocks. In electrical terms, the dry fractures are resistive and the wet fractures are conductive. The quantities measured by the ERT system are current and voltage around the outside edge of the model. The raw ERT data were translated to resistivity values inside the model using a three-dimensional Occam's inversion routine. This routine was one of the key components of ERT being tested.The model presented several challenges. First, the resistivity of both the blocks and the joints was highly variable. Second, the resistive targets introduced extreme changes the software could not precisely quantify. Third, the abrupt changes inherent in a fracture system were contrary to the smoothly varying changes expected by the Occam's inversion routine. Fourth, the response of the conductive fractures was small compared to the background variability.In general, ERT was able to locate correctly resistive fractures. Problems occurred, however, when the resistive fracture was near the edges of the model or when multiple fractures were close together. In particular, ERT tended to position the fracture closer to the model center than its true location. Conductive fractures yielded much smaller responses than the resistive case. A difference-inversion method was able to correctly locate these targets.

Notes: Streambed temperature mapping, hydraulic testing using minipiezometers, and geochemical analyses of interstitial water of the streambed were used to delineate the pattern of ground water discharge in a sandy streambed and to develop a flux-based conceptual model for ground water/surface water interactions. A new and simple empirical method was used to relate fluxes obtained from minipiezometer data to streambed temperatures. The relationship allowed flux to be calculated at locations where only streambed temperature measurements were made. Slug testing and potentiomanometer measurements at 34 piezometers indicated ground water discharge ranged from 0.03 to 446 L/m2/day (and possibly as high as 7060 L/m2/day) along a 60 m long by 11 to 14 m wide reach of river. Complex but similar plan-view patterns of flux were calculated for both summer and winter using hundreds of streambed temperatures measured on a 1 by 2 m grid. The reach was dominated by ground water discharge and 5% to 7% of the area accounted for ∼20% to 24% of the total discharge. 〈 12% of the total area consisted of recharge zones or no-discharge zones. A conceptual model for ground water/surface water interactions consisting of five different behaviors was developed based on the magnitude and direction of flux across the surface of the streambed. The behaviors include short-circuit discharge (e.g., high-flow springs), high discharge (e.g., preferential flowpaths), low to moderate discharge, no discharge (e.g., horizontal hyporheic or ground water flow), and recharge. Geological variations at depth played a key role in determining which type of flow behavior occurred in the streambed.

Notes: Many sites of ground water contamination rely heavily on complex numerical models of flow and transport to develop closure plans. This complexity has created a need for tools and approaches that can build confidence in model predictions and provide evidence that these predictions are sufficient for decision making. Confidence building is a long-term, iterative process and the author believes that this process should be termed model validation. Model validation is a process, not an end result. That is, the process of model validation cannot ensure acceptable prediction or quality of the model. Rather, it provides an important safeguard against faulty models or inadequately developed and tested models. If model results become the basis for decision making, then the validation process provides evidence that the model is valid for making decisions (not necessarily a true representation of reality). Validation, verification, and confirmation are concepts associated with ground water numerical models that not only do not represent established and generally accepted practices, but there is not even widespread agreement on the meaning of the terms as applied to models. This paper presents a review of model validation studies that pertain to ground water flow and transport modeling. Definitions, literature debates, previously proposed validation strategies, and conferences and symposia that focused on subsurface model validation are reviewed and discussed. The review is general and focuses on site-specific, predictive ground water models used for making decisions regarding remediation activities and site closure. The aim is to provide a reasonable starting point for hydrogeologists facing model validation for ground water systems, thus saving a significant amount of time, effort, and cost. This review is also aimed at reviving the issue of model validation in the hydrogeologic community and stimulating the thinking of researchers and practitioners to develop practical and efficient tools for evaluating and refining ground water predictive models.

Notes: Measurement and analysis of aquifer-system compaction have been used to characterize aquifer and confining unit properties when other techniques such as flow modeling have been ineffective at adequately quantifying storage properties or matching historical water levels in environments experiencing land subsidence. In the southeastern coastal plain of Virginia, high-sensitivity borehole pipe extensometers were used to measure 24.2 mm of total compaction at Franklin from 1979 through 1995 (1.5 mm/year) and 50.2 mm of total compaction at Suffolk from 1982 through 1995 (3.7 mm/year). Analysis of the extensometer data reveals that the small rates of aquifer-system compaction appear to be correlated with withdrawals of water from confined aquifers. One-dimensional vertical compaction modeling indicates measured compaction is the result of nonrecoverable hydrodynamic consolidation of the fine-grained confining units and interbeds, as well as recoverable compaction and expansion of coarse-grained aquifer units. The calibrated modeling results indicate that nonrecoverable specific storage values decrease with depth and range from 1.5 × 10−5/m for aquifer units to 1.5 × 10−4/m for confining units and interbeds. The aquifer and Potomac system recoverable specific storage values were all estimated to be 4.5 × 10−6/m, while the confining units and interbeds had values of 6.0 × 10−6/m. The calibrated vertical hydraulic conductivity values of the confining units and interbeds ranged from 6.6 × 10−4m/year to 2.0 × 10−3 m/year. These parameter values will be useful in future management and modeling of ground water in the Virginia Coastal Plain.

Notes: Ferric iron encrustations are a common problem that seriously affects the performance of wells and drains. Their formation is induced by the mixing of reduced ground water containing ferrous iron with oxic shallow ground water and exposure to air. The process of ferrous iron oxidation is a kinetically controlled reaction. The reaction rate has a quadratic dependency on pH. The precipitating oxides have an autocatalytic effect that further enhances reaction progress. This paper describes the application of kinetic models to the problem of encrustation formation. Influences of pH, residence time, and autocatalysis were modeled. The overall influence of the autocatalytic reaction path is particularly strong when initial amounts of iron oxides are present. Autocatalysis provides a good explanation on the development of well yield commonly measured in the field. Encrustation precipitation is slow at first, but speeds up after a sufficient amount of iron oxide has built up. An incomplete removal of iron oxide encrustations during rehabilitation leads to a renewed increase in catalytic efficiency and encrustation precipitation.

Notes: Prevention of acid mine drainage at surface coal mines in the Appalachian region relies to an extent on minimizing ground water contact with acid-forming materials, and maximizing ground water contact with alkalinity-yielding materials. Acid-forming materials are often selectively handled to minimize or prevent contact with ground water. Controlling ground water contact with acidic or alkaline materials depends on forecasting the level and range of fluctuation of the postmining water table within the mine backfill. Physical measurements and aquifer testing of more than 120 wells from 18 reclaimed mines in Kentucky, Ohio, Pennsylvania, and West Virginia have led to improved forecasting of the postmining ground water system. Factors that influence the ground water regime include spoil lithology and particle size, age of reclamation, spoil thickness, distance from the final highwall, and pit floor dip angle and direction. Spoil hydraulic conductivity (K) exhibits a 95% confidence interval range of six orders of magnitude about a mean K of 1.7 × 10−5 m/sec. Spoil aquifer saturated thickness is related to the overall thickness of the spoil, the lithology of the spoil, dip of the pit floor, and distance to the highwall. Saturated spoil thickness has a 95% confidence interval of 2.2 to 3.6 m about the mean of 2.9 m. The predicted saturated zone averages 19% of the total spoil thickness.