Induced Earthquakes from Long‐Term Gas Extraction in Groningen,the Netherlands: Statistical Analysis and Prognosis for Acceptable‐Risk Regulation

Recently, growing earthquake activity in the northeastern Netherlands has aroused considerable concern among the 600,000 provincial inhabitants. There, at 3 km deep, the rich Groningen gas field extends over 900 km² and still contains about 600 of the original 2,800 billion cubic meters (bcm). Particularly after 2001, earthquakes have increased in number, magnitude (M, on the logarithmic Richter scale), and damage to numerous buildings. The man‐made nature of extraction‐induced earthquakes challenges static notions of risk, complicates formal risk assessment, and questions familiar conceptions of acceptable risk. Here, a 26‐year set of 294 earthquakes with M ≥ 1.5 is statistically analyzed in relation to increasing cumulative gas extraction since 1963. Extrapolations from a fast‐rising trend over 2001–2013 indicate that—under “business as usual”—around 2021 some 35 earthquakes with M ≥ 1.5 might occur annually, including four with M ≥ 2.5 (ten‐fold stronger), and one with M ≥ 3.5 every 2.5 years. Given this uneasy prospect, annual gas extraction has been reduced from 54 bcm in 2013 to 24 bcm in 2017. This has significantly reduced earthquake activity, so far. However, when extraction is stabilized at 24 bcm per year for 2017–2021 (or 21.6 bcm, as judicially established in Nov. 2017), the annual number of earthquakes would gradually increase again, with an expected all‐time maximum M ≈ 4.5. Further safety management may best follow distinct stages of seismic risk generation, with moderation of gas extraction and massive (but late and slow) building reinforcement as outstanding strategies. Officially, “acceptable risk” is mainly approached by quantification of risk (e.g., of fatal building collapse) for testing against national safety standards, but actual (local) risk estimation remains problematic. Additionally important are societal cost–benefit analysis, equity considerations, and precautionary restraint. Socially and psychologically, deliberate attempts are made to improve risk communication, reduce public anxiety, and restore people's confidence in responsible experts and policymakers.     

Public Response to a Near‐Miss Nuclear Accident Scenario Varying in Causal Attributions and Outcome Uncertainty

Many studies have investigated public reactions to nuclear accidents. However, few studies focused on more common events when a serious accident could have happened but did not. This study evaluated public response (emotional, cognitive, and behavioral) over three phases of a near‐miss nuclear accident. Simulating a loss‐of‐coolant accident (LOCA) scenario, we manipulated (1) attribution for the initial cause of the incident (software failure vs. cyber terrorist attack vs. earthquake), (2) attribution for halting the incident (fail‐safe system design vs. an intervention by an individual expert vs. a chance coincidence), and (3) level of uncertainty (certain vs. uncertain) about risk of a future radiation leak after the LOCA is halted. A total of 773 respondents were sampled using a 3 × 3 × 2 between‐subjects design. Results from both MANCOVA and structural equation modeling (SEM) indicate that respondents experienced more negative affect, perceived more risk, and expressed more avoidance behavioral intention when the near‐miss event was initiated by an external attributed source (e.g., earthquake) compared to an internally attributed source (e.g., software failure). Similarly, respondents also indicated greater negative affect, perceived risk, and avoidance behavioral intentions when the future impact of the near‐miss incident on people and the environment remained uncertain. Results from SEM analyses also suggested that negative affect predicted risk perception, and both predicted avoidance behavior. Affect, risk perception, and avoidance behavior demonstrated high stability (i.e., reliability) from one phase to the next.     

Toward an Understanding of the Influence of Cultural Background and Domain Experience on the Effects of Risk‐Pricing Formats on Risk Perception

Risk‐information framing can be a powerful tool for aiding the communication of risk and improving decision making. However, little work has investigated the extent that these framing effects depend on the characteristics of the perceiver. In our study, we examine whether the effects of different risk‐pricing formats on risky choices are the same for all individuals, no matter their domain experience or cultural background, or whether there are interactions between these factors. Survey 1 revealed that three risk‐pricing formats of the same choice problem resulted in the same individuals making different risky choices (preference reversal), suggesting that risk perception was distorted by the risk‐pricing format manipulation. In Survey 2, the effects of the risk‐pricing formats were shown to differ by the participants’ cultural background (Asian vs. European) and the extent of their domain experience. The fact that there were no differences between the cultural or domain experience groups in their overall tendency to select riskier (cf. safer) choices indicates that risk behavior differences between groups are often closely linked to perceptual, rather than simply attitudinal, cognitive processes. The results demonstrate the complex, interactive cognitive processes that are used to encode risk information, involving the framing of the information and the cultural background and previous experiences of the individual. We conclude that it is important to consider the characteristics of the individual (e.g., culture, domain experience, etc.) when manipulating risk‐information framing with the aim of improving risk communication.     

Risk‐Taking and the Media

In recent years, media formats with risk‐glorifying content, such as video games that simulate illegal street racing (“bang and crash” games), films about extreme sports, and risky stunts have emerged as top sellers of the media industry. A variety of recent studies conducted by several researchers revealed that exposure to risk‐glorifying media content (e.g., video games that simulate reckless driving, smoking and drinking in movies, or depictions that glorify extreme sports) increases the likelihood that recipients will show increased levels of risk‐taking inclinations and behaviors. The present article (1) reviews the latest research on the detrimental impact of risk‐glorifying media on risk‐taking inclinations (cognitions, emotions, behaviors), (2) puts these findings in the theoretical context of recent sociocognitive models on media effects, and (3) makes suggestions to science and policymakers on how to deal with these effects in the future.     

Quantile Uncertainty and Value‐at‐Risk Model Risk

This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly important in finance, where quantile estimates (called Value‐at‐Risk) have been the cornerstone of banking risk management since the mid 1980s. A recent amendment to the Basel II Accord recommends additional market risk capital to cover all sources of “model risk” in the estimation of these quantiles. We provide a novel and elegant framework whereby quantile estimates are adjusted for model risk, relative to a benchmark which represents the state of knowledge of the authority that is responsible for model risk. A simulation experiment in which the degree of model risk is controlled illustrates how to quantify Value‐at‐Risk model risk and compute the required regulatory capital add‐on for banks. An empirical example based on real data shows how the methodology can be put into practice, using only two time series (daily Value‐at‐Risk and daily profit and loss) from a large bank. We conclude with a discussion of potential applications to nonfinancial risks.     

How Safe Is Safe Enough for Self‐Driving Vehicles?

Self‐driving vehicles (SDVs) promise to considerably reduce traffic crashes. One pressing concern facing the public, automakers, and governments is “How safe is safe enough for SDVs?” To answer this question, a new expressed‐preference approach was proposed for the first time to determine the socially acceptable risk of SDVs. In our between‐subject survey (N = 499), we determined the respondents’ risk‐acceptance rate of scenarios with varying traffic‐risk frequencies to examine the logarithmic relationships between the traffic‐risk frequency and risk‐acceptance rate. Logarithmic regression models of SDVs were compared to those of human‐driven vehicles (HDVs); the results showed that SDVs were required to be safer than HDVs. Given the same traffic‐risk‐acceptance rates for SDVs and HDVs, their associated acceptable risk frequencies of SDVs and HDVs were predicted and compared. Two risk‐acceptance criteria emerged: the tolerable risk criterion, which indicates that SDVs should be four to five times as safe as HDVs, and the broadly acceptable risk criterion, which suggests that half of the respondents hoped that the traffic risk of SDVs would be two orders of magnitude lower than the current estimated traffic risk. The approach and these results could provide insights for government regulatory authorities for establishing clear safety requirements for SDVs.     

Risk Mapping of Groundwater‐Drawdown‐Induced Land Subsidence in Heterogeneous Soils on Large Areas

Groundwater leakage into subsurface constructions can cause reduction of pore pressure and subsidence in clay deposits, even at large distances from the location of the construction. The potential cost of damage is substantial, particularly in urban areas. The large‐scale process also implies heterogeneous soil conditions that cannot be described in complete detail, which causes a need for estimating uncertainty of subsidence with probabilistic methods. In this study, the risk for subsidence is estimated by coupling two probabilistic models, a geostatistics‐based soil stratification model with a subsidence model. Statistical analyses of stratification and soil properties are inputs into the models. The results include spatially explicit probabilistic estimates of subsidence magnitude and sensitivities of included model parameters. From these, areas with significant risk for subsidence are distinguished from low‐risk areas. The efficiency and usefulness of this modeling approach as a tool for communication to stakeholders, decision support for prioritization of risk‐reducing measures, and identification of the need for further investigations and monitoring are demonstrated with a case study of a planned tunnel in Stockholm.     

Who is a Distracted Driver? Associations between Mobile Phone Use while Driving,Domain‐Specific Risk Taking,and Personality

Mobile phone use while driving (MPUWD) is an increasingly common form of distracted driving. Given its widespread prevalence, it is important for researchers to identify factors that may predict who is more likely to engage in this risky behavior. The current study investigates associations between MPUWD risk behaviors, domain‐specific risk perceptions, and broad personality dimensions. An Italian community sample (n = 804) completed a survey regarding MPUWD risk perceptions and engagement in MPUWD, in addition to the HEXACO‐PI‐R, a broad six‐factor personality inventory (honesty‐humility, emotionality, extraversion, agreeableness, conscientiousness, openness to experience), and the DOSPERT, a six‐factor domain‐specific self‐report risk‐taking measure (health/safety, recreational, social, ethical, gambling, and investment). With respect to domain‐specific risk taking, greater frequency of SMS use while driving most strongly was associated with greater risk taking for the health/safety, gambling, and ethical risk domains. Further, greater honesty‐humility and conscientiousness, two traits related to cognitive control and risk behaviors, and to a lesser extent openness to experience, were associated with less frequent MPUWD, and positively associated with MPUWD risk perceptions. With growing public safety concern surrounding MPUWD, understanding associated personality factors is not only important for identifying psychological mechanisms underlying risk behavior, but also for more effective prevention and intervention programs.     

Risk Perception in the U.K. Oil and Gas Production Industry: Are Expert Loss‐Prevention Managers' Perceptions Different From Those of Members of the Public?

This article investigates potential differences in risk perception between experts (loss-prevention managers in the U.K. oil and gas production industry) and nonexperts (managers and students). Extant research on expert versus nonexpert perceptions of risk is reviewed, followed by the present study concerning risk perceptions of seven pen-picture scenarios involving the occurrence of hazardous events in the U.K. oil and gas production industry. In contrast to many of the earlier studies of expert versus nonexpert perceptions of risk, the present analysis concludes that experts did not judge the overall riskiness of the portrayed hazardous events as less risky than the nonexperts. Nevertheless, the experts believe more strongly than our nonexperts that the risks portrayed in the scenarios pose little threat to future generations, are more precisely known, and are relatively controllable. Use of multiple regression analysis to help uncover the basis of overall riskiness assessments for expert and lay respondents was inconclusive, however. Finally, little evidence was found that nonexperts were any more heterogeneous in their risk perceptions than experts. It may be that the nature of the risks assessed in the present study may account for the general lack of clear expert versus nonexpert differences in overall perceptions of the riskiness of hazardous events in the North Sea. Earlier findings of strong expert versus nonexpert differences in risk perception assessed hazards of major public concern. It is inferred that using such extreme hazards may have resulted in an exaggerated view of differences in expert versus public (nonexpert) perception of risk.     

An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory

Land subsidence risk assessment (LSRA) is a multi‐attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor‐level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster‐Shafer (D‐S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi‐Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information—quantitative or qualitative, complete or incomplete, and precise or imprecise—to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.     

The Interplay Between Knowledge,Perceived Efficacy,and Concern About Global Warming and Climate Change: A One‐Year Longitudinal Study

If the long‐term goal of limiting warming to less than 2°C is to be achieved, rapid and sustained reductions of greenhouse gas emissions are required. These reductions will demand political leadership and widespread public support for action on global warming and climate change. Public knowledge, level of concern, and perceived personal efficacy, in positively affecting these issues are key variables in understanding public support for mitigation action. Previous research has documented some contradictory associations between knowledge, personal efficacy, and concern about global warming and climate change, but these cross‐sectional findings limit inferences about temporal stability and direction of influence. This study examines the relationships between these three variables over a one‐year period and three waves with national data from New Zealand. Results showed a positive association between the variables, and the pattern of findings was stable and consistent across the three data points. More importantly, results indicate that concern mediates the influence of knowledge on personal efficacy. Knowing more about global warming and climate change increases overall concern about the risks of these issues, and this increased concern leads to greater perceived efficacy and responsibility to help solving them. Implications for risk communication are discussed.     

Effects of Acknowledging Uncertainty about Earthquake Risk Estimates on San Francisco Bay Area Residents’ Beliefs,Attitudes, and Intentions

We test here the risk communication proposition that explicit expert acknowledgment of uncertainty in risk estimates can enhance trust and other reactions. We manipulated such a scientific uncertainty message, accompanied by probabilities (20%, 70%, implicit [“will occur”] 100%) and time periods (10 or 30 years) in major (≥magnitude 8) earthquake risk estimates to test potential effects on residents potentially affected by seismic activity on the San Andreas fault in the San Francisco Bay Area (n = 750). The uncertainty acknowledgment increased belief that these specific experts were more honest and open, and led to statistically (but not substantively) significant increases in trust in seismic experts generally only for the 20% probability (vs. certainty) and shorter versus longer time period. The acknowledgment did not change judged risk, preparedness intentions, or mitigation policy support. Probability effects independent of the explicit admission of expert uncertainty were also insignificant except for judged risk, which rose or fell slightly depending upon the measure of judged risk used. Overall, both qualitative expressions of uncertainty and quantitative probabilities had limited effects on public reaction. These results imply that both theoretical arguments for positive effects, and practitioners’ potential concerns for negative effects, of uncertainty expression may have been overblown. There may be good reasons to still acknowledge experts’ uncertainties, but those merit separate justification and their own empirical tests.     

Deliberative Disjunction: Expert and Public Understanding of Outcome Uncertainty

Many environmental and risk management decisions are made jointly by technical experts and members of the public. Frequently, their task is to select from among management alternatives whose outcomes are subject to varying degrees of uncertainty. Although it is recognized that how this uncertainty is interpreted can significantly affect decision‐making processes and choices, little research has examined similarities and differences between expert and public understandings of uncertainty. We present results from a web‐based survey that directly compares expert and lay interpretations and understandings of different expressions of uncertainty in the context of evaluating the consequences of proposed environmental management actions. Participants responded to two hypothetical but realistic scenarios involving trade‐offs between environmental and other objectives and were asked a series of questions about their comprehension of the uncertainty information, their preferred choice among the alternatives, and the associated difficulty and amount of effort. Results demonstrate that experts and laypersons tend to use presentations of numerical ranges and evaluative labels differently; interestingly, the observed differences between the two groups were not explained by differences in numeracy or concerns for the predicted environmental losses. These findings question many of the usual presumptions about how uncertainty should be presented as part of deliberative risk‐ and environmental‐management processes.     

Determinants of Seeking and Avoiding Risk‐Related Information in Times of Crisis

This research is designed to provide insight into the psychological (e.g., threat appraisal or coping appraisal) and other determinants (e.g., information quality judgments or demographics) of risk information seeking or avoidance in times of an acute risk, as part of the process of increasing public resilience through adherence to risk mitigating advice. Data were collected via telephone interviews. A specialized agency interviewed 1,000 Dutch citizens, randomly confronted with one of eight fictitious, but realistic, acute risk and emergency situations. Results indicate that information seeking in an acute situation is anticipated by a less elaborate set of predictors (age and risk perception) than information seeking in a nonacute situation (age and risk perception, as well as educational level and social norm). Although risk perception is a predictor for risk information seeking, its predictive value for acute‐risk‐related behavior, as one might have assumed based on theories such as protection motivation theory (PMT) or the extended parallel process model (EPPM), appears to be limited. Implications for risk communication are discussed.     

Does Concern‐Driven Risk Management Provide a Viable Alternative to QRA?

This article discusses a concept of concern-driven risk management, in which qualitative expert judgments about whether concerns warrant specified risk management interventions are used in preference to quantitative risk assessment (QRA) to guide risk management decisions. Where QRA emphasizes formal quantitative assessment of the probable consequences caused by the recommended actions, and comparison to the probable consequences of alternatives, including the status quo, concern-driven risk management instead emphasizes perceived urgency or severity of the situation motivating recommended interventions. In many instances, especially those involving applications of the precautionary principle, no formal quantification or comparison of probable consequences for alternative decisions is seen as being necessary (or, perhaps, possible or desirable) prior to implementation of risk management measures. Such concern-driven risk management has been recommended by critics of QRA in several areas of applied risk management. Based on case studies and psychological literature on the empirical performance of judgment-based approaches to decision making under risk and uncertainty, we conclude that, although concern-driven risk management has several important potential political and psychological advantages over QRA, it is not clear that it performs better than (or as well as) QRA in identifying risk management interventions that successfully protect human health or achieve other desired consequences. Therefore, those who advocate replacing QRA with concern-driven alternatives, such as expert judgment and consensus decision processes, should assess whether their recommended alternatives truly outperform QRA, by the criterion of producing preferred consequences, before rejecting the QRA paradigm for practical applications.     

Testing and Characterizing Properties of Nonadditive Measures Through Violations of the Sure‐Thing Principle

In expected utility theory, risk attitudes are modeled entirely in terms of utility. In the rank‐dependent theories, a new dimension is added: chance attitude, modeled in terms of nonadditive measures or nonlinear probability transformations that are independent of utility. Most empirical studies of chance attitude assume probabilities given and adopt parametric fitting for estimating the probability transformation. Only a few qualitative conditions have been proposed or tested as yet, usually quasi‐concavity or quasi‐convexity in the case of given probabilities. This paper presents a general method of studying qualitative properties of chance attitude such as optimism, pessimism, and the “inverse‐S shape” pattern, both for risk and for uncertainty. These qualitative properties can be characterized by permitting appropriate, relatively simple, violations of the sure‐thing principle. In particular, this paper solves a hitherto open problem: the preference axiomatization of convex (“pessimistic” or “uncertainty averse”) nonadditive measures under uncertainty. The axioms of this paper preserve the central feature of rank‐dependent theories, i.e. the separation of chance attitude and utility.     

Probability and Possibility‐Based Representations of Uncertainty in Fault Tree Analysis

Expert knowledge is an important source of input to risk analysis. In practice, experts might be reluctant to characterize their knowledge and the related (epistemic) uncertainty using precise probabilities. The theory of possibility allows for imprecision in probability assignments. The associated possibilistic representation of epistemic uncertainty can be combined with, and transformed into, a probabilistic representation; in this article, we show this with reference to a simple fault tree analysis. We apply an integrated (hybrid) probabilistic‐possibilistic computational framework for the joint propagation of the epistemic uncertainty on the values of the (limiting relative frequency) probabilities of the basic events of the fault tree, and we use possibility‐probability (probability‐possibility) transformations for propagating the epistemic uncertainty within purely probabilistic and possibilistic settings. The results of the different approaches (hybrid, probabilistic, and possibilistic) are compared with respect to the representation of uncertainty about the top event (limiting relative frequency) probability. Both the rationale underpinning the approaches and the computational efforts they require are critically examined. We conclude that the approaches relevant in a given setting depend on the purpose of the risk analysis, and that further research is required to make the possibilistic approaches operational in a risk analysis context.     

Modeling Risk‐Related Knowledge in Tunneling Projects

Knowledge on failure events and their associated factors, gained from past construction projects, is regarded as potentially extremely useful in risk management. However, a number of circumstances are constraining its wider use. Such knowledge is usually scarce, seldom documented, and even unavailable when it is required. Further, there exists a lack of proven methods to integrate and analyze it in a cost‐effective way. This article addresses possible options to overcome these difficulties. Focusing on limited but critical potential failure events, the article demonstrates how knowledge on a number of important potential failure events in tunnel works can be integrated. The problem of unavailable or incomplete information was addressed by gathering judgments from a group of experts. The elicited expert knowledge consisted of failure scenarios and associated probabilistic information. This information was integrated using Bayesian belief‐networks‐based models that were first customized in order to deal with the expected divergence in judgments caused by epistemic uncertainty of risks. The work described in the article shows that the developed models that integrate risk‐related knowledge provide guidance as to the use of specific remedial measures.     

Using the CAUSE Model to Understand Public Communication about Water Risks: Perspectives from Texas Groundwater District Officials on Drought and Availability

Public communication about drought and water availability risks poses challenges to a potentially disinterested public. Water management professionals, though, have a responsibility to work with the public to engage in communication about water and environmental risks. Because limited research in water management examines organizational communication practices and perceptions, insights into research and practice can be gained through investigation of current applications of these risk communication efforts. Guided by the CAUSE model, which explains common goals in communicating risk information to the public (e.g., creating Confidence, generating Awareness, enhancing Understanding, gaining Satisfaction, and motivating Enactment), semistructured interviews of professionals (N = 25) employed by Texas groundwater conservation districts were conducted. The interviews examined how CAUSE model considerations factor in to communication about drought and water availability risks. These data suggest that many work to build constituents’ confidence in their districts. Although audiences and constituents living in drought‐prone areas were reported as being engaged with water availability risks and solutions, many district officials noted constituents’ lack of perceived risk and engagement. Some managers also indicated that public understanding was a secondary concern of their primary responsibilities and that the public often seemed apathetic about technical details related to water conservation risks. Overall, results suggest complicated dynamics between officials and the public regarding information access and motivation. The article also outlines extensions of the CAUSE model and implications for improving public communication about drought and water availability risks.     

Evaluating Risk Communication: Examining Target Audience Perceptions About Four Presentation Formats for Fish Consumption Health Advisory Information

Information format can influence the extent to which target audiences understand and respond to risk-related information. This study examined four elements of risk information presentation format. Using printed materials, we examined target audience perceptions about: (a) reading level; (b) use of diagrams vs. text; (c) commanding versus cajoling tone; and (d) use of qualitative vs. quantitative information presented in a risk ladder. We used the risk communication topic of human health concerns related to eating noncommercial Great Lakes fish affected by chemical contaminants. Results from the comparisons of specific communication formats indicated that multiple formats are required to meet the needs of a significant percent of anglers for three of the four format types examined. Advisory text should be reviewed to ensure the reading level is geared to abilities of the target audience. For many audiences, a combination of qualitative and quantitative information, and a combination of diagrams and text may be most effective. For most audiences, a cajoling rather than commanding tone better provides them with the information they need to make a decision about fish consumption. Segmenting audiences regarding information needs and communication formats may help clarify which approaches to take with each audience.