Perceived Risks of Radioactive Waste Transport Through Oregon: Results of a Statewide Survey

Transportation of hazardous materials, and particularly radioactive wastes, on public highways has become an important risk management issue. The unfavorability of public attitudes regarding hazardous and nuclear wastes signals the potential for strong public opposition to programs for transporting these materials. This paper presents the results of a survey conducted to assess public reactions to a long-term nuclear waste transport program planned to follow a route through a portion of rural Oregon. The survey assessed a number of key risk perception issues, including perceived health and safety risks of nuclear waste transport, relative risks of transport vs. storage at an existing site, trust in state officials, and satisfaction with life in communities along the transport route. The survey identified a number of attitudes and concerns that need to be understood and considered by those in charge of designing and implementing the waste-transportation program.     

Statistical Evaluation of Population Data for Calculation of Radioactive Material Transport Accident Risks

Calculation of accident dose-risk estimates with the RADTRAN code requires input data describing the population likely to be affected by the plume of radioactive material (RAM) released in a hypothetical transportation accident. In the existing model, population densities within 1/2 mile (0.8 km) of the route centerline are tabulated in three ranges (Rural, Suburban, and Urban). These population densities may be of questionable validity since the plume in the RADTRAN analysis is assumed to extend out to 120 km from the hypothetical accident site. We present a GIS-based population model which accounts for the actual distribution of population under a potential plume, and compare accident-risk estimates based on the resulting population densities with those based on the existing model. Results for individual points along a route differ greatly, but the cumulative accident risks for a sample route of a few hundred kilometers are found to be comparable, if not identical. We conclude, therefore, that for estimation of aggregate accident risks over typical routes of several hundred kilometers, the existing, simpler RADTRAN model is sufficiently detailed and accurate.     

Vehicle Emission Unit Risk Factors for Transportation Risk Assessments

When the transportation risk posed by shipments of hazardous chemical and radioactive materials is being assessed, it is necessary to evaluate the risks associated with both vehicle emissions and cargo-related risks. Diesel exhaust and fugitive dust emissions from vehicles transporting hazardous shipments lead to increased air pollution, which increases the risk of latent fatalities in the affected population along the transport route. The estimated risk from these vehicle-related sources can often be as large or larger than the estimated risk associated with the material being transported. In this paper, data from the U.S. Environmental Protection Agency's Motor Vehicle-Related Air Toxics Study are first used to develop latent cancer fatality estimates per kilometer of travel in rural and urban areas for all diesel truck classes. These unit risk factors are based on studies investigating the carcinogenic nature of diesel exhaust. With the same methodology, the current per-kilometer latent fatality risk factor used in transportation risk assessments for heavy diesel trucks in urban areas is revised and the analysis expanded to provide risk factors for rural areas and all diesel truck classes. These latter fatality estimates may include, but are not limited to, cancer fatalities and are based primarily on the most recent epidemiological data available on mortality rates associated with ambient air PM-10 concentrations.     

Quantitative Risk Analysis on the Transport of Dangerous Goods Through a Bi‐Directional Road Tunnel

A quantitative risk analysis (QRA) regarding dangerous goods vehicles (DGVs) running through road tunnels was set up. Peak hourly traffic volumes (VHP), percentage of heavy goods vehicles (HGVs), and failure of the emergency ventilation system were investigated in order to assess their impact on the risk level. The risk associated with an alternative route running completely in the open air and passing through a highly populated urban area was also evaluated. The results in terms of social risk, as F/N curves, show an increased risk level with an increase the VHP, the percentage of HGVs, and a failure of the emergency ventilation system. The risk curves of the tunnel investigated were found to lie both above and below those of the alternative route running in the open air depending on the type of dangerous goods transported. In particular, risk was found to be greater in the tunnel for two fire scenarios (no explosion). In contrast, the risk level for the exposed population was found to be greater for the alternative route in three possible accident scenarios associated with explosions and toxic releases. Therefore, one should be wary before stating that for the transport of dangerous products an itinerary running completely in the open air might be used if the latter passes through a populated area. The QRA may help decisionmakers both to implement additional safety measures and to understand whether to allow, forbid, or limit circulation of DGVs.     

A Framework for Hazardous Materials Transport Risk Assessment

In this paper, we provide a framework for quantitative risk assessment in hazardous materials transport. We first outline a basic model where population centers are approximated by points on a plane with the assumption that in the case of an incident all residents in a population center will experience the same consequences. Different versions of this model have been used by other authors in the literature. This model may be valid if the hazardous materials route goes by small population centers. Then we extend this basic model to assess risks of shipping hazardous materials through large population centers that cannot be modeled as single points on a plane. In the extended model, large population centers are treated as two-dimensional objects on the plane, which allows for a more accurate treatment of consequences than the basic model. To the extent of our knowledge the extended model is novel. We provide numerical examples for both the basic and the extended models, and finish by discussing limitations of the suggested risk assessment framework.     

Urban risks due to climate change in the Andean municipality of Pasto,Colombia: A Bayesian network approach

The current trends of climate change will increase people's exposure to urban risks related to events such as landslides, floods, forest fires, food production, health, and water availability, which are stochastic and very localized in nature. This research uses a Bayesian network (BN) approach to analyze the intensity of such urban risks for the Andean municipality of Pasto, Colombia, under climate change scenarios. The stochastic BN model is linked to correlational models and local scenarios of representative concentration trajectories (RCP) to project the possible risks to which the municipality of Pasto will be exposed in the future. The results show significant risks in crop yields, food security, water availability and disaster risks, but no significant risks on the incidence of acute diarrheal diseases (ADD) and acute respiratory infections (ARI), whereas positive outcomes are likely to occur in livestock production, influenced by population growth. The advantage of the BN approach is the possibility of updating beliefs in the probabilities of occurrence of events, especially in developing, intermediate cities with information-limited contexts.     

Farmer Knowledge and Risk Analysis: Postrelease Evaluation of Herbicide-Tolerant Canola in Western Canada

The global controversy regarding the use of genetically modified (GM) crops has proved to be a challenge for "science-based" risk assessments. Although risk analysis incorporates societal perspectives in decision making over these crops, it is largely predicated on contrasts between "expert" and "lay" perspectives. The overall objective of this study is to explore the role for farmers' knowledge, and their decade-long experience with herbicide-tolerant (HT) canola, in the risk analysis of GM crops. From 2002 to 2003, data were collected using interviews ( n = 15) and mail surveys ( n = 370) with farmers from Manitoba and across Canada. The main benefits associated with HT canola were management oriented and included easier weed control, herbicide rotation, and better weed control, whereas the main risks were more diverse and included market harm, technology use agreements (TUAs), and increased seed costs. Benefits and risks were inversely related, and the salient factor influencing risk was farmer experiences with HT canola volunteers, followed by small farm size and duration using HT canola. These HT volunteers were reported by 38% of farmers, from both internal (e.g., seedbank, farm machinery, etc.) and external (e.g., wind, seed contamination, etc.) sources, and were found to persist over time. Farmer knowledge is a reliable and rich source of information regarding the efficacy of HT crops, demonstrating that individual experiences are important to risk perception. The socioeconomic nature of most risks combined with the continuing "farm income crisis" in North America demonstrates the need for a more holistic and inclusive approach to risk assessment associated with HT crops and, indeed, with all new agricultural technology.     

Spatial Optimization of Future Urban Development with Regards to Climate Risk and Sustainability Objectives

Future development in cities needs to manage increasing populations, climate‐related risks, and sustainable development objectives such as reducing greenhouse gas emissions. Planners therefore face a challenge of multidimensional, spatial optimization in order to balance potential tradeoffs and maximize synergies between risks and other objectives. To address this, a spatial optimization framework has been developed. This uses a spatially implemented genetic algorithm to generate a set of Pareto‐optimal results that provide planners with the best set of trade‐off spatial plans for six risk and sustainability objectives: (i) minimize heat risks, (ii) minimize flooding risks, (iii) minimize transport travel costs to minimize associated emissions, (iv) maximize brownfield development, (v) minimize urban sprawl, and (vi) prevent development of greenspace. The framework is applied to Greater London (U.K.) and shown to generate spatial development strategies that are optimal for specific objectives and differ significantly from the existing development strategies. In addition, the analysis reveals tradeoffs between different risks as well as between risk and sustainability objectives. While increases in heat or flood risk can be avoided, there are no strategies that do not increase at least one of these. Tradeoffs between risk and other sustainability objectives can be more severe, for example, minimizing heat risk is only possible if future development is allowed to sprawl significantly. The results highlight the importance of spatial structure in modulating risks and other sustainability objectives. However, not all planning objectives are suited to quantified optimization and so the results should form part of an evidence base to improve the delivery of risk and sustainability management in future urban development.     

An Approach to Assessing the Impacts of Incident-Free Transportation of Radioactive Materials: II. Highway Transportation

Annual radiation doses and risks to the public living near, and traveling on, public highways, and occupational doses are calculated for highway shipments of radioactive materials under accident-free and incident-free conditions (i.e., under normal transportation conditions). The database developed by Sandia National Laboratories is used, and calculations are made using RADTRAN 4.0. This report is one of two reports estimating radiological risk associated with transportation of radioactive materials.     

Health-Based Population Forecasting: Effects of Smoking on Mortality and Fertility

A microsimulation model, allowing one to forecast short- and long-term population changes conditional on the prevalence of a risk factor in a population, is presented. In this model, population changes result from the aggregation of changes in individual event histories, which, in turn, result from mortality and infertility rates recalculated in accordance with their known relative risks in population groups exposed to a risk factor. Smoking, being the most widespread and influential preventable public health risk factor, is chosen to demonstrate the abilities of the model to forecast the population effects of different hypothetical smoking prevalences. The demographic and population health effects on 20-, 50-, and 100-year projections with the current, hypothetically doubled, and hypothetically halved the current smoking prevalence are analyzed in detail. The model predicts an increase in life expectancy (0.99 year for males and 0.64 years for females), and an increase in population size (2.2-7.5% dependent on the age group) if smoking prevalence is reduced by half. Sensitivity analyses of all findings are performed. The generalization of the model to account for multiple risk factors (e.g., the simultaneous effects of alcohol consumption, obesity, and smoking) and effects on medical expenditures are discussed.     

“短板”淘汰式评标方法及其应用研究

国内外主要的评标方法是从综合评价的角度来选择优秀的投标人,忽略了中标人的劣势可能隐含的风险;最优秀的投标人应该是不能顺利完成工程建设的风险最小;不能顺利完成工程建设的风险常常取决于投标人的"短板"。本文提出基于识别个体劣势来发现投标人"短板"的方式,并依此形成一种"短板"淘汰式评标方法。本方法主要由整体挑剔和挑剔个体两个环节构成:通过整体挑剔,按照工程的目标价值取向,客观确定各指标的权重,对投标人进行排名;通过挑剔个体,剔除"短板"短的个体。本文还模拟了大伙房水库输水工程水源地堤防工程的评标。理论和模拟表明本方法具有科学性和可操作性,并能够降低工程的履约风险。     

Should Persons with Diabetes Be Licensed to Drive Trucks?—Risk Management

How should a regulatory agency interpret a risk analysis that concludes there is a small increase in risk? The agency must decide on behalf of society whether the increased risk is large enough to justify banning the risky activity or taking some other step to lessen the risks. In a companion paper (Songer et al.), we conclude that licensing insulin using persons to drive commercial motor vehicles in interstate commerce would result in 42 additional crashes each year. Here we address risk management issues by interpreting the number of additional crashes and the relative risks of the prospective handicapped drivers. Are the number of additional crashes (42) significant? Is the increase in the annual crash risk (from 0.00785 to 0.032 for non-insulin dependent and 0.048 for insulin dependent persons) significant? Are the relative risks significant for all insulin using drivers (4.7)? For drivers with a history of severe hypoglycemic reactions (19.8)? How should society tradeoff risk increases for increases in opportunity for these handicapped persons? We review other social decisions concerning highway safety: Accepting the increasing risks of letting 16 year olds drive, allowing extremely light cars, allowing some unsafe highways, and allowing extremely unsafe driving conditions at some times of day. We conclude that the additional risks from insulin using persons are well within the current accepted range of risks. Currently, 70% of states permit insulin using persons to drive trucks within their state. Nonetheless, the social cost, due to fatalities, injuries, and property damage from allowing a person with a history of severe hypoglycemic reactions to drive is more than $19,700 per year.     

Predicting Future Excess Events in Risk Assessment

Risk characterization in a study population relies on cases of disease or death that are causally related to the exposure under study. The number of such cases, so-called "excess" cases, is not just an indicator of the impact of the risk factor in the study population, but also an important determinant of statistical power for assessing aspects of risk such as age-time trends and susceptible subgroups. In determining how large a population to study and/or how long to follow a study population to accumulate sufficient excess cases, it is necessary to predict future risk. In this study, focusing on models involving excess risk with possible effect modification, we describe a method for predicting the expected magnitude of numbers of excess cases and assess the uncertainty in those predictions. We do this by extending Bayesian APC models for rate projection to include exposure-related excess risk with possible effect modification by, e.g., age at exposure and attained age. The method is illustrated using the follow-up study of Japanese Atomic-Bomb Survivors, one of the primary bases for determining long-term health effects of radiation exposure and assessment of risk for radiation protection purposes. Using models selected by a predictive-performance measure obtained on test data reserved for cross-validation, we project excess counts due to radiation exposure and lifetime risk measures (risk of exposure-induced deaths (REID) and loss of life expectancy (LLE)) associated with cancer and noncancer disease deaths in the A-Bomb survivor cohort.     

Use of Mechanistic Models to Estimate Low-Dose Cancer Risks

The utility of mechanistic models of cancer for predicting cancer risks at low doses is examined. Based upon a general approximation to the dose-response that is valid at low doses, it is shown that at low doses the dose-response predicted by a mechanistic model is a linear combination of the dose-responses for each of the physiological parameters in the model that are affected by exposure. This demonstrates that, unless the mechanistic model provides a theoretical basis for determining the dose-responses for these parameters, the extrapolation of risks to low doses using a mechanistic model is basically "curve fitting," just as is the case when extrapolating using statistical models. This suggests that experiments to generate data for use in mechanistic models should emphasize measuring the dose-response for dose-related parameters as accurately as possible and at the lowest feasible doses.     

A GIS-Based Framework for Hazardous Materials Transport Risk Assessment

This article presents a methodology for assessment of the hazardous materials transport risk in a multicommodity, multiple origin-destination setting. The proposed risk assessment methodology was integrated with a Geographical Information System (GIS), which made large-scale implementation possible. A GIS-based model of the truck shipments of dangerous goods via the highway network of Quebec and Ontario was developed. Based on the origin and destination of each shipment, the risk associated with the routes that minimize (1) the transport distance, (2) the population exposure, (3) the expected number of people to be evacuated in case of an incident, and (4) the probability of an incident during transportation was evaluated. Using these assessments, a government agency can estimate the impact of alternative policies that could alter the carriers' route choices. A related issue is the spatial distribution of transport risk, because an unfair distribution is likely to cause public concern. Thus, an analysis of transport risk equity in the provinces of Quebec and Ontario is also provided.     

Estimation of Potential Health Effects from Acute Exposure to Hydrogen Fluoride Using a "Benchmark Dose" Approach

Communities across the United States are examining the manufacture, use, transport, and storage of hydrogen fluoride (HF) near residential areas as a consequence of a major release of HF in Texas in 1987. Reference exposure levels for routine and accidental HF emissions are calculated using existing animal and human data. The approach employs a logprobit extrapolation of concentration-response data to the 95% lower confidence limit on the toxic concentration producing a "benchmark dose" of 1% response (TC01), called a practical threshold. Species-specific and chemical-specific adjustment factors are applied to develop exposure levels applicable to the general public. Using this method, the 1-hr reference exposure level to protect the public against any irritation from a routine emission (REL-1) is 0.7 ppm and the level to protect against severe irritation from a once-in-a-lifetime (REL-2) release is 2 ppm. This approach is compared to a modified "uncertainty factor" approach.     

An Empirical Test of the Relative Validity of Expert and Lay Judgments of Risk

This article investigates how accurately experts (underwriters) and lay persons (university students) judge the risks posed by life-threatening events Only one prior study (Slovic, Fischhoff, & Lichtenstein, 1985) has previously investigated the veracity of expert versus lay judgments of the magnitude of risk. In that study, a heterogeneous grouping of 15 experts was found to judge, using marginal estimations, a variety of risks as closer to the true annual frequencies of death than convenience samples of the lay population. In this study, we use a larger, homogenous sample of experts performing an ecologically valid task. We also ask our respondents to assess frequencies and relative frequencies directly, rather than ask for a "risk" estimate--a response mode subject to possible qualitative attributions-as was done in the Slovic et al. study. Although we find that the experts outperformed lay persons on a number of measures, the differences are small, and both groups showed similar global biases in terms of: (1) overestimating the likelihood of dying from a condition (marginal probability) and of dying from a condition given that it happens to you (conditional probability), and (2) underestimating the ratios of marginal and conditional likelihoods between pairs of potentially lethal events. In spite of these scaling problems, both groups showed quite good performance in ordering the lethal events in terms of marginal and conditional likelihoods. We discuss the nature of expertise using a framework developed by Bolger and Wright (1994), and consider whether the commonsense assumption of the superiority of expert risk assessors in making magnitude judgments of risk is, in fact, sensible.     

Information Technology Risks as Seen by the Public

Risks related to information technology (IT) are becoming a focus of concern in current risk debates. The use of IT is rapidly spreading in the population, as is access to computers in general. The present article reviews the literature on IT use (especially electronic mail and various Internet applications) and the related risks. In addition, the results from a survey about IT use and risk perception, given to a random sample of the Swedish population, are reported. In general, participants were quite positive to IT and were, to some extent, aware of the related risks. However, risks of IT were mostly seen as pertinent to other people, a finding in contrast with other results on perceived technology hazards. The attitude toward the use of IT was strongly related to general attitude toward computers, and less clearly to risk perception. Only a small percentage of the respondents reported having had negative experiences with IT hazards such as Internet addiction, depression, and social isolation. When extrapolated to the general population, however, these small percentages amount to large groups in the population that have been negatively affected by IT use.     

Effect of detection methods on risk estimates of exposure to biosolids-associated human enteric viruses

This study illustrates the effect of virus detection methods on estimates of risks of infection of biosolids-associated viruses for occupational workers and residential population during a hypothetical exposure of biosolids. Five gastroenteritis-associated human enteric viruses--enteroviruses (echovirus-12, enteroviruse types 68-71), adenoviruses, rotaviruses, and noroviruses genotype--I-were considered to represent human enteric viruses for risk estimation purposes. Ingested viral doses were calculated using literature-reported total infectious virus concentrations (based on BGM and A549 cell lines) and genome copies (GCs) in Michigan dewatered and class B biosolids. Cell-line-based infectivity parameters (i.e., ratio of total infectious virus concentration to GCs) were developed for different viruses in biosolids to use GCs for calculating ingested viral dose, addressing the issue of integration of molecular methods with biosolids-based virus risk assessment. Use of virus concentrations from molecular methods (with and without using cell-line-based infectivity parameter) resulted in higher risk estimates than culture methods, indicating the effect of the virus detection method on risk estimates. Further, use of virus concentrations from A549 cell lines resulted in higher risk estimates compared to those from BGM cell lines, suggesting the need for a proper choice of cell lines in determining infectious viral dose. The Monte Carlo uncertainty analyses of estimates for risk of infection due to enteroviruses showed that enteroviruses concentration was the most important parameter influencing risk estimates, indicating the need for reducing associated uncertainty. More work is required to develop cell-line-based infectivity parameters for different virus concentration levels and sample matrix types using a cut-off-based approach.