Evaluation of the Physical Hazards Associated with Two Remedial Alternatives at a Superfund Site

This study presents an evaluation of the risks due to the physical hazards associated with two remedial alternatives for a former chemical manufacturing facility in New Jersey. Both the on-site and off-site risk of work-related fatalities during remedy implementation and the risks of accident or accident-related fatalities during the off-site transport of site-related materials were evaluated. The two remedial alternatives evaluated were on-site containment and excavation with off-site incineration. The risk of at least one fatality due to a work-related accident was estimated for on-site activities associated with each remedial alternative, and for off-site incineration. The risks of at least one accident and of one accident-related fatality were calculated with accident and fatality data from the U.S. Department of Transportation. In addition, the risk of at least one accident that might potentially affect a natural resource (e.g., river, lake, or national park) was evaluated. This evaluation indicates that the risk of a work-related fatality is over an order of magnitude higher, and the risk of an accident or accident-related fatality is over three orders of magnitude higher, for the excavation/off-site incineration remedial alternative than for the on-site containment alternative. Overall, this study indicates that the physical hazards associated with excavation and off-site incineration are much greater than those associated with on-site containment for this site. Therefore, if a choice between the two remedial alternatives were to be made based solely on physical hazards and accident risk, the on-site containment alternative would be more protective of human health and the environment than the excavation/off-site incineration alternative.     

Extending the Quantitative Assessment of Industrial Risks to Earthquake Effects

In the general framework of quantitative methods for natural‐technological (NaTech) risk analysis, a specific methodology was developed for assessing risks caused by hazardous substances released due to earthquakes. The contribution of accidental scenarios initiated by seismic events to the overall industrial risk was assessed in three case studies derived from the actual plant layout of existing oil refineries. Several specific vulnerability models for different equipment classes were compared and assessed. The effect of differing structural resistances for process equipment on the final risk results was also investigated. The main factors influencing the final risk values resulted from the models for equipment vulnerability and the assumptions for the reference damage states of the process equipment. The analysis of case studies showed that in seismic zones the additional risk deriving from damage caused by earthquakes may be up to more than one order of magnitude higher than that associated to internal failure causes. Critical equipment was determined to be mainly pressurized tanks, even though atmospheric tanks were more vulnerable to containment loss. Failure of minor process equipment having a limited hold‐up of hazardous substances (such as pumps) was shown to have limited influence on the final values of the risk increase caused by earthquakes.     

Probabilistic Analysis of Dam Accidents Worldwide: Risk Assessment for Dams of Different Purposes in OECD and Non-OECD Countries with Focus on Time Trend Analysis

This study presents probabilistic analysis of dam accidents worldwide in the period 1911–2016. The accidents are classified by the dam purpose and by the country cluster, where they occurred, distinguishing between the countries of the Organization for Economic Cooperation and Development (OECD) and nonmember countries (non-OECD without China). A Bayesian hierarchical approach is used to model distributions of frequency and severity for accidents. This approach treats accident data as a multilevel system with subsets sharing specific characteristics. To model accident probabilities for a particular dam characteristic, this approach samples data from the entire data set, borrowing the strength across data set and enabling to model distributions even for subsets with scarce data. The modelled frequencies and severities are combined in frequency-consequence curves, showing that accidents for all dam purposes are more frequent in non-OECD (without China) and their maximum consequences are larger than in OECD countries. Multipurpose dams also have higher frequencies and maximum consequences than single-purpose dams. In addition, the developed methodology explicitly models time dependence to identify trends in accident frequencies over the analyzed period. Downward trends are found for almost all dam purposes confirming that technological development and implementation of safety measures are likely to have a positive impact on dam safety. The results of the analysis provide insights for dam risk management and decision-making processes by identifying key risk factors related to country groups and dam purposes as well as changes over time.     

Containment of Polioviruses After Eradication and OPV Cessation: Characterizing Risks to Improve Management

The goal of the World Health Organization is to stop routine use of oral poliovirus vaccine shortly after interruption of wild poliovirus transmission. A key component of this goal is to minimize the risk of reintroduction by destruction of polioviruses except in an absolute minimum number of facilities that serve essential functions and implement effective containment. Effective containment begins with a complete facility risk assessment. This article focuses on characterizing the risks of exposure to polioviruses from the essential vaccine production, quality control, and international reference and research facilities that remain. We consider the potential exposure pathways that might lead to a poliovirus reintroduction, including para-occupational exposures and releases to the environment, and review the literature to provide available estimates and a qualitative assessment of containment risks. Minimizing the risk of poliovirus transmission from a poliovirus facility to increasingly susceptible communities is a crucial and ongoing effort requiring understanding and actively managing the potential exposure pathways.     

Major Accidents (Gray Swans) Likelihood Modeling Using Accident Precursors and Approximate Reasoning

Compared to the remarkable progress in risk analysis of normal accidents, the risk analysis of major accidents has not been so well‐established, partly due to the complexity of such accidents and partly due to low probabilities involved. The issue of low probabilities normally arises from the scarcity of major accidents’ relevant data since such accidents are few and far between. In this work, knowing that major accidents are frequently preceded by accident precursors, a novel precursor‐based methodology has been developed for likelihood modeling of major accidents in critical infrastructures based on a unique combination of accident precursor data, information theory, and approximate reasoning. For this purpose, we have introduced an innovative application of information analysis to identify the most informative near accident of a major accident. The observed data of the near accident were then used to establish predictive scenarios to foresee the occurrence of the major accident. We verified the methodology using offshore blowouts in the Gulf of Mexico, and then demonstrated its application to dam breaches in the United Sates.     

Evacuation Risks: A Tentative Approach for Quantification

This study tries to assess the risk of deaths and injuries from motor vehicle accidents associated with an evacuation of population groups in case of nuclear plant accidents. The risk per person–km is evaluated using: (a) data from previous evacuation: information from Soufriere evacuation (Guadeloupe Island 1976) and Mississauga (1979), added to Hans and Sell's data: no road accident occurred for a sample of 1,500,000 persons; (b) national recording system for motor vehicle accident: the rates of 2.2 10 ^-8 deaths per person–km and 32 10^-8 injuries per person–km is calculated as an average. These last rates in France overestimate the number of casualties. A reasonable hypothesis is to assume that the probability of road accident occurrence follows a Poisson distribution, as these events are independent and unfrequent, as no accident was observed in a sample of 1,500,000 persons the probability is between 0 and an upper value of 0.24 10^-8 deaths per person-km and 3.29 10^-8 injuries per person–km. The average and maximum population involved within different radii around French and U.S. Nuclear power sites are taken as a sample size in order to study the total risk of deaths and injuries in the hypothesis of an evacuation being necessary to protect the populations.     

Risk Management and Decision Rules for Light Water Reactors

A quantitative approach to risk management for accidents in light water nuclear power reactors is proposed to serve as one focus for discussion. In this proposal risk management is divided into two major tasks: the predominantly social and political task of setting the safety goals and the technical task of estimating the risks and deciding whether the safety goals have been met. The proposed safety goals include limits on the following: risk to the individual of early death or delayed cancer death; overall societal risk of early or delayed death; and the frequency of core melt accidents as well as the frequency of containment failure, given a core melt. Also included are a small element of risk aversion and an "as low as reasonably achievable" (ALARA) approach with a cost-effectviness criterion which includes both economic and health effects.     

Risk-Adjusted Mission Value: Trading Off Mission Risk for Mission Value

This article develops a decision-theoretic methodology for the risk-adjusted mission value (RAMV) for selecting between alternative missions in the presence of uncertainty in the outcomes of the missions. This methodology permits trading off mission risk for mission value, something that probabilistic risk analysis cannot do unless it explicitly incorporates both mission value and risk aversion of the project management. The methodology, in its complete implementation, is consistent with the decision theory known as expected utility theory, although it differs from conventional decision theory in that the probabilities and all but one of the utilities are not those of the decision maker. The article also introduces a new interpretation of risk aversion. The methodology is consistent with the elementary management concept concerning division of labor. An example is presented for selecting between discrete alternatives-four landing sites on Mars. A second example is presented for selecting among a set of continuous alternatives-a comet flyby distance. The methodology is developed within the context of scientific missions, but the methodology is equally applicable to any situation requiring outcome value judgments, probability judgments, and risk aversion judgments by different constituencies.     

Risk Analysis for Biological Hazards: What We Need to Know about Invasive Species

Risk analysis for biological invasions is similar to other types of natural and human hazards. For example, risk analysis for chemical spills requires the evaluation of basic information on where a spill occurs; exposure level and toxicity of the chemical agent; knowledge of the physical processes involved in its rate and direction of spread; and potential impacts to the environment, economy, and human health relative to containment costs. Unlike typical chemical spills, biological invasions can have long lag times from introduction and establishment to successful invasion, they reproduce, and they can spread rapidly by physical and biological processes. We use a risk analysis framework to suggest a general strategy for risk analysis for invasive species and invaded habitats. It requires: (1) problem formation (scoping the problem, defining assessment endpoints); (2) analysis (information on species traits, matching species traits to suitable habitats, estimating exposure, surveys of current distribution and abundance); (3) risk characterization (understanding of data completeness, estimates of the "potential" distribution and abundance; estimates of the potential rate of spread; and probable risks, impacts, and costs); and (4) risk management (containment potential, costs, and opportunity costs; legal mandates and social considerations and information science and technology needs).     

Clinical reengineering. Integrating medical and operational management

In the continuing push for cost containment in health care, many organizations have turned to cost reduction methods that fundamentally change the way care is delivered. As health care organizations continue to make financially-driven staffing changes that impact patient care, medical leadership must take on greater responsibility for operational management. Physician executives are uniquely qualified to take on leadership roles in work redesign, and must do so to ensure excellent and fiscally-responsible patient care. This article presents a proven methodology for work redesign that helps physician executives apply their clinical skills to operational management in designing new health care delivery models.     

Developing a scale for assessing risk attitudes of agricultural decision makers

This study adapts a methodology formulated in the social sciences to develop a scale for measuring an economic agent’s attitude toward risk. The scale assesses risk attitudes by eliciting farmers’ opinions towards risk management tools using a Likert procedure. The methodology validates the scale with a scientific risk attitude measure and compares the scale to the farmers’ self-assessment of their risk attitudes. The resulting scale methodology could be administered to people without the need for personal interviews. The subjects for this study were Midwestern farmers, but the methodology can be applied to any sector of the agricultural industry.     

Bayesian Data Analysis of Severe Fatal Accident Risk in the Oil Chain

We analyze the risk of severe fatal accidents causing five or more fatalities and for nine different activities covering the entire oil chain. Included are exploration and extraction, transport by different modes, refining and final end use in power plants, heating or gas stations. The risks are quantified separately for OECD and non‐OECD countries and trends are calculated. Risk is analyzed by employing a Bayesian hierarchical model yielding analytical functions for both frequency (Poisson) and severity distributions (Generalized Pareto) as well as frequency trends. This approach addresses a key problem in risk estimation—namely the scarcity of data resulting in high uncertainties in particular for the risk of extreme events, where the risk is extrapolated beyond the historically most severe accidents. Bayesian data analysis allows the pooling of information from different data sets covering, for example, the different stages of the energy chains or different modes of transportation. In addition, it also inherently delivers a measure of uncertainty. This approach provides a framework, which comprehensively covers risk throughout the oil chain, allowing the allocation of risk in sustainability assessments. It also permits the progressive addition of new data to refine the risk estimates. Frequency, severity, and trends show substantial differences between the activities, emphasizing the need for detailed risk analysis.     

Containment im Coaching

The psychodynamic concept of containment in coaching describes a process where the coach takes on, digests and returns emotional tension, unresolved conflicts und unconscious acting out of the coachee. Using two case studies the article develops the basic elements of containment in coaching. In addition to this interpersonal dimension of containment the article also highlights the structural dimension of containment — to provide sufficient space and conditions for thinking and processing emotional turmoil.     

Risk analysis of fast spreading species in a Kashmir Himalayan National Park (Dachigam) for better monitoring and management

Huge economic costs and ecological impacts of invasive alien species (IAS) in the protected areas (PAs) worldwide make their timely prediction and potential risk assessment of central importance for effective management. While the preborder weed risk assessment framework has been extensively evaluated and implemented, the postborder species risk assessment framework has not been subjected to the same degree of scrutiny. Here we used a rather more realistic modified version of the Australian Weed Risk framework (AWRM) for Dachigam National Park (DNP) in Kashmir Himalaya against 84 plant species, including 55 alien species and 29 fast spreading native species, for risk analysis. We found two very high-risk species, three high-risk species, 10 medium-risk species, 29 low-risk species, and 40 negligible-risk species in the DNP. The containment scores accordingly ranged from 14.4 to 293.5 comprising of 27 species that can be contained with very high feasibility, 23 species with high feasibility, 14 species with medium feasibility, and 12 species which cannot be contained easily thereby having low feasibility of containment (FOC) score. However, eight species which have a negligible FOC score are difficult to contain within their infestation sites. Our results demonstrate the merit of the AWRM with a caution that the necessary region-specific modifications may help in its better implementation. Overall, these results provide quite a promising tool in the hands of protected area managers to timely and effectively deal with the problem of plant invasions.     

Development of Economic Consequence Methodology for Process Risk Analysis

A comprehensive methodology for economic consequence analysis with appropriate models for risk analysis of process systems is proposed. This methodology uses loss functions to relate process deviations in a given scenario to economic losses. It consists of four steps: definition of a scenario, identification of losses, quantification of losses, and integration of losses. In this methodology, the process deviations that contribute to a given accident scenario are identified and mapped to assess potential consequences. Losses are assessed with an appropriate loss function (revised Taguchi, modified inverted normal) for each type of loss. The total loss is quantified by integrating different loss functions. The proposed methodology has been examined on two industrial case studies. Implementation of this new economic consequence methodology in quantitative risk assessment will provide better understanding and quantification of risk. This will improve design, decision making, and risk management strategies.     

Cost containment in health care: a model for management research.

Cost containment is a dominant problem in the health care field, but it has not been addressed from a comprehensive management perspective. To fill this gap, we have developed an inclusive model of the cost containment process. The model has implications for management research in several areas: cost containment baselines, incentive systems, organization structures, cost/quality trade-offs, and cost containment constraints.     

System of Systems Engineering and Risk Management of Extreme Events: Concepts and Case Study

The domain of risk analysis is expanded to consider strategic interactions among multiple participants in the management of extreme risk in a system of systems. These risks are fraught with complexity, ambiguity, and uncertainty, which pose challenges in how participants perceive, understand, and manage risk of extreme events. In the case of extreme events affecting a system of systems, cause‐and‐effect relationships among initiating events and losses may be difficult to ascertain due to interactions of multiple systems and participants (complexity). Moreover, selection of threats, hazards, and consequences on which to focus may be unclear or contentious to participants within multiple interacting systems (ambiguity). Finally, all types of risk, by definition, involve potential losses due to uncertain events (uncertainty). Therefore, risk analysis of extreme events affecting a system of systems should address complex, ambiguous, and uncertain aspects of extreme risk. To accomplish this, a system of systems engineering methodology for risk analysis is proposed as a general approach to address extreme risk in a system of systems. Our contribution is an integrative and adaptive systems methodology to analyze risk such that strategic interactions among multiple participants are considered. A practical application of the system of systems engineering methodology is demonstrated in part by a case study of a maritime infrastructure system of systems interface, namely, the Straits of Malacca and Singapore.     

Application of data mining to minimize fire-induced domino effect risks

Data mining (DM) has been applied in many advanced science and technology fields, but it has still not been used for domino effect risk management to explore minimum risk scenarios. This work investigates the feasibility of DM in minimizing the risk of fire-induced domino effects in chemical processing facilities. Based on DM, an evidential failure mode and effects analysis (E-FMEA), which could bridge chemical facilities’ operational reliability and domino effect risk, is combined with fault tree analysis (FTA) for the occurrence risk modeling of loss of containment (LOC) event of chemical facilities, which is often the triggering point of fire-induced domino effects. Industry specific data such as reliability data, inspection records, and maintenance records are of great value to model the potential occurrence criticality of LOC. The data are used to characterize the LOC risk priority number (RPN) of chemical facilities through FTA and E-FMEA, search and statistics rules are proposed to mine inspection records to assess LOC risk factors. According to the RPN scores of facilities, inherent safety strategies to minimize risk via inventory control are proposed, and their effectiveness is tested using a well-known probit model. In this way, the approach proposes a unit-specific evidence-based risk minimization strategy for fire-induced domino effects. A case study demonstrates the capability of DM in the risk minimization of fire-induced domino effects.     

The Multistage Model with a Time-Dependent Dose Pattern: Applications to Carcinogenic Risk Assessment1

A cancer risk assessment methodology based upon the Armitage–Doll multistage model of cancer is applied to animal bioassay data. The method utilizes the exact time-dependent dose pattern used in a bioassay rather than some single measure of dose such as average dose rate or cumulative dose. The methodology can be used to predict risks from arbitrary exposure patterns including, for example, intermittent exposure and short-term exposure occurring at an arbitrary age. The methodology is illustrated by applying it to a National Cancer Institute bioassay of ethylene dibromide in which dose rates were modified several times during the course of the experiment.