An Emerging New Risk Analysis Science: Foundations and Implications

Microplastics and Co-pollutants in soil and marine environments: Sorption and desorption dynamics in unveiling invisible danger and key to ecotoxicological risk assessment

Microplastics (MPs) and their co-pollutants pose significant threats to soil and marine environments, necessitating understanding of their colonization processes to combat the plastic pandemic and protect ecosystems. MPs can act as invisible carriers, concentrating and transporting pollutants, leading to a more widespread and potentially toxic impact than the presence of either MPs or the pollutants alone. Analyzing the sorption and desorption dynamics of MPs is crucial for understanding pollutants amplification and predicting the fate and transport of pollutants in soil and marine environments. This review provides an in-depth analysis of the sorption and desorption dynamics of MPs, highlighting the importance of considering these dynamics in ecotoxicological risk assessment of MPs pollution. The review identifies limitations of current frameworks that neglect these interactions and proposes incorporating sorption and desorption data into robust frameworks to improve the ability to predict ecological risks posed by MPs and co-pollutants in soil and marine environments. However, failure to address the interplay between sorption and desorption can result in underestimation of the true impact of MPs and co-pollutants, affecting livelihoods and agro-employments, and exacerbate poverty and community disputes (SDGs 1, 2, 3, 8, 9, and 16). It can also affect food production and security (SDG 2), life below water and life on land (DSGs 14 and 15), cultural practices, and natural heritage (SDG 11.4). Hence, it is necessary to develop new approaches to ecotoxicological risk assessment that consider sorption and desorption processes in the interactions between the components in the framework to address the identified limitations.

On the interconnected nature of risk and responsibility in the research and development of new and emerging technologies

Risk analysis of new and emerging technologies requires innovative approaches that are agile, exploratory, and can accommodate broad stakeholder engagement and perspectives. Existing theories of risk governance and responsible innovation suggest that operationalizing guiding principles for engagement such as inclusion and reflection may provide a useful approach to the risk analysis of these technologies. Yet, methodologies to systematically assess how we might operationalize such guiding principles in risk analysis are limited in existing risk research. We contribute to filling this gap by demonstrating a practical methodology for examining and documenting how research and development (R&D) professionals operationalize inclusion and reflection in risk analysis and what value this provides to risk analysis in the R&D context. We use the Australian nanotechnology R&D sector as our case study, interviewing 28 experts to examine how R&D professionals have operationalized inclusion and reflection into their risk analysis practices, generating three findings. First, we describe how our research design enables the successful translation of theory into a methodology that supports an empirical assessment of the integration of these guiding principles into risk analysis practice. Second, we argue that successfully and systematically integrating inclusion and reflection in risk analysis fosters a wider understanding and identification of risk through the activation of multi-actor and multi-institutional stakeholder engagement processes. Third, we outline how this research depicts the outward-facing and introspective nature of risk analysis.

Risk literacy: Foundational issues and its connection to risk science

A new research area is developing, risk literacy. The term "risk literacy" basically refers to one's ability to understand and evaluate risk, in order to support and make appropriate decisions. In this article, we discuss how risk literacy relates to risk analysis/science with its topics of risk fundamentals (concepts), risk understanding, risk assessments, risk characterizations, risk perception, risk communication, and risk handling (covering risk management, risk governance, and policies on risk). We question how issues and research topics addressed in risk literacy relate to risk analysis/science knowledge, particularly on risk understanding. The main conclusion of the article is that risk literacy addresses an important topic-from both a theoretical and a practical societal relevancy perspective-and brings the potential for many additional developments and further insights if the topic is better integrated with risk science knowledge more broadly.

Confidence deficits and reducibility: Toward a coherent conceptualization of uncertainty level

Outside of the field of risk analysis, an important theoretical conversation on the slippery concept of uncertainty has unfolded over the last 40 years within the adjacent field of environmental risk. This literature has become increasingly standardized behind the tripartite distinction between uncertainty location, the nature of uncertainty, and uncertainty level, popularized by the "W&H framework." This article introduces risk theorists and practitioners to the conceptual literature on uncertainty with the goal of catalyzing further development and clarification of the uncertainty concept within the field of risk analysis. It presents two critiques of the W&H framework's dimension of uncertainty level-the dimension that attempts to define the characteristics separating greater uncertainties from lesser uncertainties. First, I argue the framework's conceptualization of uncertainty level lacks a clear and consistent epistemological position and fails to acknowledge or reconcile the tensions between Bayesian and frequentist perspectives present within the framework. This article reinterprets the dimension of uncertainty level from a Bayesian perspective, which understands uncertainty as a mental phenomenon arising from "confidence deficits" as opposed to the ill-defined notion of "knowledge deficits" present in the framework. And second, I elaborate the undertheorized concept of uncertainty "reducibility." These critiques inform a clarified conceptualization of uncertainty level that can be integrated with risk analysis concepts and usefully applied by modelers and decisionmakers engaged in model-based decision support.

Cases of real-life policies related to risk: How can they enhance risk analysis and risk science?

Policies on risk constitute a core topic of risk analysis and risk science, and it is common at risk conferences to present real-life cases of such policies, for example related to the handling of climate change and pandemics. Although these are of broad interest, showing how important issues in society are dealt with, it can be questioned to what extent and how these cases contribute to enhancing risk analysis and risk science. The present paper addresses this concern. It is argued that, in order to learn from the cases, they need in general to be more thoroughly followed up with discussions of concepts, principles, approaches, and methods for assessing, characterizing, communicating and handling risk. Describing a governmental policy on, for example, the handling of COVID-19 is a point of departure for interesting discussions concerning its justification and performance, in particular in relation to risk and the most updated knowledge from the risk analysis field. Such discussions are, however, often lacking. The paper points to some key obstacles and challenges for the learning process, including the difficulty of distinguishing between policies, policy analysis, and politics.

The reliability of evaporation ponds as a final basin for industrial effluent: Demonstration of an environmental risk management methodology

Recognizing and assessing environmental risk are key components of every industry management strategy. Projects need to make sure that a detailed environmental risk management strategy is applied by methodically recognizing and addressing threats from internal and external influences to comply with regulatory standards for environmental preservation and safeguarding. This study's goal is to use a novel technique to assess the impact of environmental risks related to the use of evaporation ponds as final basins for industrial effluents. It employs qualitative and statistical methodologies to identify areas where engineering and managerial safeguards' structure, functioning, and lines of defense have flaws that might result in an ecologically hazardous occurrence. Additionally, it will offer a risk evaluation based on the gravity of the impact and the likelihood that the environmental occurrence would happen by using evaporation ponds to store industrial effluents. While the environmental threat would be entirely removed, it must be capable of reducing it to ALARP. The environmental risk assessment matrix will serve as a key factor in determining whether the environmental risk level linked with an evaporation pond is acceptable, as determined by the likelihood and impacts. The result of this research allows industrial units to recognize and control potential environmental risks associated with effluents by practically implementing a new environmental risk matrix based on several environmental and ecological effects with probability factors.•This study aims to assist industrial operators, especially power plants, manage environmental risk by combining ALARP concepts with other factors to evaluate risk acceptance and tolerance levels.•The Physico-chemical characteristics of effluent collected in the evaporation pond reveal that evaporation has a deleterious impact on such industrial effluent, as evidenced by a large increase in various effluent properties, some of which exceed the limit values.•A risk evaluation found that effluent collected in the evaporation pond has a detrimental negative impact on industrial effluents. This was evidenced by a significant rise in associated activities. This could increase the expense of operating and managing evaporation ponds, which could harm the ecosystem.

Narratives of Project Risk Management: From Scientific Rationality to the Discursive Nature of Identity Work

The dominant narrative of project risk management pays homage to scientific rationality while conceptualizing risk as objective fact. Yet doubts remain regarding the extent to which the advocated quantitative techniques are used in practice. An established counternarrative advocates the importance of intuition and subjective judgment. New insights are developed by conceptualizing risk as a narrative construct used for the purposes of identity work. Project-based practitioners are seen to mobilize resources from competing narratives to meet the transient expectations of those with whom they interact. Ultimately, they tend to emphasize approaches that sustain their ascribed identities as custodians of rationality.

Risk assessment for handling hazardous substances within the European industry: Available methodologies and research streams

After the Seveso disaster occurred more than 40 years ago, there has been an increasing awareness of the potential impacts that similar accident events can occur in a wide range of process establishments, where the handling and production of hazardous substances pose a real threat to society and the environment. In these industrial sites denominated "Seveso sites," the urgent need for an effective strategy emerged markedly to handle hazardous activities and to ensure safe conditions. Since then, the main challenging research issues have focused on how to prevent such accident events and how to mitigate their consequences leading to the development of many risk assessment methodologies. In recent years, researchers and practitioners have tried to provide useful overviews of the existing risk assessment methodologies proposing several reviews. However, these reviews are not exhaustive because they are either dated or focus only on one specific topic (e.g., liquefied natural gas, domino effect, etc.). This work aims to overcome the limitations of the current reviews by providing an up-to-date and comprehensive overview of the risk assessment methodologies for handling hazardous substances within the European industry. In particular, we have focused on the current techniques for hazards and accident scenarios identification, as well as probability and consequence analyses for both onshore and offshore installations. Thus, we have identified the research streams that have characterized the activities of researchers and practitioners over the years, and we have then presented and discussed the different risk assessment methodologies available concerning the research stream that they belong to.

On Risk Probability of Prefabricated Building Hoisting Construction Based on Multiple Correlations

With growing concern about environmental pollution and occupational safety in construction industry globally, prefabricated building has become a popular building model in sustainable society. In China, management specifications of prefabricated buildings are far from mature, and safety accidents occur frequently in construction. In order to comprehensively analyze risks in hoisting construction of prefabricated buildings, this study, in view of characteristics of hoisting construction process and correlations in complex system, summarizes risk factors and classifies them according to Wuli-Shili-Renli (WSR) system. From perspective of multiple correlations, evolution mechanism of multi-system correlation and multi-risk correlation is carried out, so as to explore risk probability of hoisting construction of prefabricated buildings. At the same time, this study extends Two Additive Choquet Integral (TACI) operator and Decision-making Trial and Evaluation Laboratory (DEMATEL) in dynamic stochastic environment to construct a two-stage model for risk probability research of hoisting construction, hoping to profoundly reveal influence of risk factors and their dynamic evolution. The results show that: (1) risk probability presented a seasonal, dynamic change trend, which meant rising first, then falling, and finally keeping rising, thus regular inspection and dynamic monitoring are required in hoisting construction in these regions in the first three quarters. (2) the influence of each risk factor demonstrated dynamic changes, and risk sources that need to prevent and defuse at different time points are varied, thus targeted measures catering to different risk sources are required. (3) the degree of risk controllability is in dynamic change, but classification of cause or result in the region at the period remains the same, thus necessitating targeted response measures aimed at various risk types. (4) Individual risks like hoisting job climated break out periodically, so the law of risk occurrence should be mastered and relative precautionary measures should be taken in advance.

Precise Yet Uncertain: Broadening Understandings of Uncertainty and Policy in the BPA Controversy

Bisphenol A (BPA) is one of the most studied and most controversial chemicals used by the food packaging industry, because of its endocrine disruptive properties. Part of the controversy is due to the uncertainty that surrounds the effects of BPA on the endocrine system. Uncertainty includes data gaps, methodological hurdles, incompatibilities between toxicology and endocrinology-based approaches, and so on. In this article, we analyze how uncertainty has been conceptualized and treated. We focus on the European Food Safety Authority assessments of BPA, and study how exposure and hazard assessments have evolved over time, how uncertainty has been analyzed, and how the agency responded to controversies. Results show that in the attempt to reduce knowledge gaps, assessments have become progressively larger, including more references, evidence, and effects. There is a tendency toward greater precisions and specification of results, and toward protocolization of all processes included in the assessment (from literature review, to uncertainty assessments, and public consultation). Yet, the uncertainty has not diminished following the increase in evidence. We argue that the strategy used to reduce uncertainty within risk assessment, namely including more variables, studies, data, and methods, amplifies the uncertainty linked to indeterminacy (as more results increase the fragmentation of the knowledge base due to the open-ended nature of complex issues) and ambiguity (as complexity gives way to multiple nonequivalent interpretations of results). For this reason, it is important to consider different types of uncertainty and how these uncertainties interact with each other.

Risk Analysis in the Age of Big Data: The Promises and Pitfalls

Despite its rising popularity, the novelty and merits of big data risk analysis are still debated. This perspective article contributes to the debate by clarifying what constitutes big data in the context of risk analysis and proposing that the discussions of big data attributes (i.e., scale, speed, and structure) and big data methods should go hand in hand. Simple examples are used to illustrate the differences between big data risk analysis and traditional approaches. Finally, a distinction is made between the conceptual definition of risk and how risk is measured to clarify the contributions of big data to risk assessment, and to highlight the importance of explicitly accounting for strength of knowledge in conducting big data risk analysis.

Theoretical Matters: On the Need for Hazard and Disaster Theory Developed Through Interdisciplinary Research and Collaboration

Hazard and disaster research requires a willingness to step outside of traditional disciplinary ontological and epistemological assumptions to both accommodate and integrate different perspectives. Moreover, the complex qualities of hazards and disasters necessitate interdisciplinary approaches to inform theory development that encompasses environmental, human, and infrastructure systems at multiple scales and units of analysis. Unfortunately, truly integrative hazard and disaster theory at a scale broad enough to account for the many systems and processes involved is currently limited. In this article, we argue that robust hazard and disaster theory can only arise from interdisciplinary research and collaboration. We examine challenges to the development of interdisciplinary hazard and disaster theory, and discuss the characteristics of theory necessary for the goal-oriented nature of research aimed at reducing disaster impact.

A Risk Analysis‐Best Worst Method Based Model for Selection of the Most Appropriate Contract Strategy for Onshore Drilling Projects in the Iranian Petroleum Industry

The pre-project planning phase has a significant impact on the achievement of project objectives because during this stage, major decisions including involving contract strategies are made with a high degree of uncertainty. Studies show that the contract type can play a unique role in the achievement of project success. On the other hand, drilling projects can be considered as one of the most critical types of projects in the petroleum industry. In this research, a novel risk based best-worst method (risk-BWM) is proposed for solving the issue of selecting the best contract strategy. A three level methodology was designed; firstly, the risk breakdown structure (RBS) of drilling projects was created in four levels including one heading in level 0, eight main areas of risk in level 1, 34 sub-areas of risk in level 2, and finally, 217 risk items in level 3. Secondly and on the basis of BWM, the weights of risk factors were determined as the selection criteria and consequently the best and the worst criteria were specified. Finally, using pair-wise comparisons between six types of drilling prevalent in contracts, the most appropriate contract type was proposed. The contribution of this study is the development of a generic RBS for drilling projects and application of the risk factors for the first time for the selection of contract type using the BWM method, which has the potential of being adapted for other types of underground projects.

Globalization and global risk: How risk analysis needs to be enhanced to be effective in confronting current threats

In the last 20-30 years, technological innovation has enabled the advancement of industry at a global scale, giving rise to a truly global society, resting on an interdependent web of transnational technical, economic and social systems. These systems are exposed to scenarios of cascading outbreaks, whose impacts can ripple to very large scales through their strong interdependencies, as recently shown by the pandemic spreading of the Coronavirus. Considerable work has been conducted in recent years to develop frameworks to support the assessment, communication, management and governance of this type of risk, building on concepts like systemic risks, complexity theory, deep uncertainties, resilience engineering, adaptive management and black swans. Yet contemporary risk analysis struggles to provide authoritative societal guidance for adequately handling these types of risks, as clearly illustrated by the Coronavirus case. In this paper, we reflect on this situation. We aim to identify critical challenges in current frameworks of risk assessment and management and point to ways to strengthen these, to be better able to confront threats like the Coronavirus in the future. A set of principles and theses are established, which have the potential to support a common foundation for the many different scientific perspectives and 'schools' currently dealing with risk handling issues.

Foundational Challenges for Advancing the Field and Discipline of Risk Analysis

Risk analysis as a field and discipline is about concepts, principles, approaches, methods, and models for understanding, assessing, communicating, managing, and governing risk. The foundation of this field and discipline has been subject to continuous discussion since its origin some 40 years ago with the establishment of the Society for Risk Analysis and the Risk Analysis journal. This article provides a perspective on critical foundational challenges that this field and discipline faces today, for risk analysis to develop and have societal impact. Topics discussed include fundamental questions important for defining the risk field, discipline, and science; the multidisciplinary and interdisciplinary features of risk analysis; the interactions and dependencies with other sciences; terminology and fundamental principles; and current developments and trends, such as the use of artificial intelligence.

The Evolving Field of Risk Communication

The 40th Anniversary of the Society for Risk Analysis presents an apt time to step back and review the field of risk communication. In this review, we first evaluate recent debates over the field's current state and future directions. Our takeaway is that efforts to settle on a single, generic version of what constitutes risk communication will be less productive than an open-minded exploration of the multiple forms that comprise today's vibrant interdisciplinary field. We then review a selection of prominent cognitive, cultural, and social risk communication scholarship appearing in the published literature since 2010. Studies on trust in risk communication messengers continued to figure prominently, while new research directions emerged on the opportunities and critical challenges of enhancing transparency and using social media. Research on message attributes explored how conceptual insights particularly relating to framing, affective and emotional responses, and uncertainty might be operationalized to improve message effectiveness. Studies consistently demonstrated the importance of evaluation and how varying single attributes alone is unlikely to achieve desired results. Research on risk communication audiences advanced on risk perception and multiway engagement with notable interest in personal factors such as gender, race, age, and political orientation. We conclude by arguing that the field's interdisciplinary tradition should be further nurtured to drive the next evolutionary phase of risk communication research.

Risk Science Contributions: Three Illustrating Examples

This article aims to demonstrate that risk science is important for society, industry and all of us. Rather few people today, including scientists and managers, are familiar with what this science is about-its foundation and main features-and how it is used to gain knowledge and improve communication and decision making in real-life situations. The article seeks to meet this challenge, by presenting three examples, showing how risk science works to gain new generic, fundamental knowledge on risk concepts, principles, and methods, as well as supporting the practical tackling of actual risk problems.

Safety Regulations and the Uncertainty of Work-Related Road Accident Loss: The Triple Identity of Chinese Local Governments Under Principal-Agent Framework

This study examines how government safety regulations affect the uncertainty of work-related road accident loss (UWRAL) by considering the multi-identity of local governments in the relationship among the central government, the local governments, and enterprises. Fixed effects panel models and mediation analyses with bootstrapping were conducted to test the hypotheses using Chinese provincial panel data from 2008 to 2014. Given the complexity and nonlinear characteristics of road safety systems, a new approach based on self-organized criticality theory is proposed to measure the uncertainty of road accident loss from a complex system perspective. We find that a regional government with detailed safety work planning (SWP), high safety supervision intensity (SSI), and safety information transparency (SIT) can decrease the UWRAL. Furthermore, our findings suggest that SSI and SIT partially mediate the relationship between the SWP of regional governments and the UWRAL, with 19.7% and 23.6% indirect effects, respectively. This study also provides the government with managerial implications by linking the results of risk assessment to decision making for risk management.

An Integrated Approach for Modeling Sustainability Risks in Freight Transportation Systems

Integrating sustainability into freight transportation systems (FTSs) is a complex and challenging task due to the sheer number of inherent sustainability risks. Sustainability risks disrupt the economic, social and environmental objectives of freight operations and act as impediments in the development of sustainable freight transportation systems. The area of sustainability risk management is still unexplored and immature in the operational research domain. This study addresses these research gaps and contributes in a threefold manner. First, a total of 36 potential sustainability risks related to FTSs are identified and uniquely classified into seven categories using a rigourous approach. Second, the research proposes two prominent perspectives, namely, ontological and epistemological perspectives to understand risks and develops a novel framework for managing sustainability risks in FTSs. Third, a novel approach by integrating fuzzy evidential reasoning algorithm (FERA) with expected utility theory is developed to quantitatively model and profile sustainability risk for different risk preferences, namely, risk-averse, risk-neutral, and risk-taking scenarios. The proposed FERA is a flexible and robust approach, which transforms the experts' inputs into belief structures and aggregates them using the evidence combination rule proposed in Dempster-Shafer theory to overcome the problem of imprecise results caused by average scoring in existing models. A sensitivity analysis is conducted to demonstrate the robustness of the proposed model. Unlike conventional perception, our study suggests that most of the high priority sustainability risks are behaviorally and socially induced rather than financially driven. The results provide significant managerial implications including a focus on skills development, and on social and behavioral dimensions while managing risks in FTSs.

Advancing impact assessments of non-native species: strategies for strengthening the evidence-base

The numbers and impacts of non-native species (NNS) continue to grow. Multiple ranking protocols have been developed to identify and manage the most damaging species. However, existing protocols differ considerably in the type of impact they consider, the way evidence of impacts is included and scored, and in the way the precautionary principle is applied. These differences may lead to inconsistent impact assessments. Since these protocols are considered a main policy tool to promote mitigation efforts, such inconsistencies are undesirable, as they can affect our ability to reliably identify the most damaging NNS, and can erode public support for NNS management. Here we propose a broadly applicable framework for building a transparent NNS impact evidence base. First, we advise to separate the collection of evidence of impacts from the act of scoring the severity of these impacts. Second, we propose to map the collected evidence along a set of distinguishing criteria: where it is published, which methodological approach was used to obtain it, the relevance of the geographical area from which it originates, and the direction of the impact. This procedure produces a transparent and reproducible evidence base which can subsequently be used for different scoring protocols, and which should be made public. Finally, we argue that the precautionary principle should only be used at the risk management stage. Conditional upon the evidence presented in an impact assessment, decision-makers may use the precautionary principle for NNS management under scientific uncertainty regarding the likelihood and magnitude of NNS impacts. Our framework paves the way for an improved application of impact assessments protocols, reducing inconsistencies and ultimately enabling more effective NNS management.

Exploring the Conceptual Foundation of Continuity Management in the Context of Societal Safety

Public and private actors with critical roles for ensuring societal safety need to work proactively to reduce risks and vulnerabilities. Traditionally, risk management activities have often been performed in order to ensure continuous functioning of key societal services. Recently, however, business continuity management (BCM), and its analytical subcomponent business impact assessment (BIA), has been introduced and used more extensively by both the private and public sector in order to increase the robustness and resilience of critical infrastructures and societal functions and services. BCM was originally developed in the business sector but has received a broader use during the last decade. Yet, BCM/BIA has gained limited attention in the scientific literature-especially when it comes to clarifying and developing its conceptual basis. First, this article examines and discusses the conceptual foundation of BCM concepts, including practical challenges of applying the concepts. Based on recent conceptual developments from the field of risk management, a developed conceptualization is suggested. Second, the article discusses challenges that arise when applying BCM in the societal safety area and provides some recommendations aiming to improve the clarity and quality of applications. Third, the article provides suggestions of how to integrate the overlapping approaches of BIA and risk assessment in order to improve efficiency and effectiveness of proactive, analytic processes. We hope that the article can stimulate a critical discussion about the key concepts of BCM, their wider use in societal safety, and their connection to other concepts and activities such as risk assessment.

The Call for a Shift from Risk to Resilience: What Does it Mean?

In recent years calls have been made for a shift from risk to resilience. The basic idea is that we need to be prepared when threatening events occur, whether they are anticipated or unforeseen. This article questions the extent to which this call will have and should have implications for the risk field and science. Is the call based on a belief that this field and science should be replaced by resilience analysis and management, or is it more about priorities: Should more weight be placed on improving resilience? The article argues that the only meaningful interpretation of the call is the latter. Resilience analysis and management is today an integrated part of the risk field and science, and risk analysis in a broad sense is needed to increase relevant knowledge, develop adequate policies, and make the right decisions, balancing different concerns and using our limited resources in an effective way.

Reflections on the Use of Conceptual Research in Risk Analysis

A risk analysis science is developing, characterized by knowledge generation on concepts, principles, theories, frameworks, methods, and models, for understanding, assessing, characterizing, communicating, and managing risk (for short referred to as conceptual knowledge generation in risk analysis), as well as supporting risk knowledge generation of specific activities based on these concepts, principles, theories, frameworks, methods, and models. The scientific knowledge generation is based on different types of research methods. This article provides a discussion of some of these, the main purpose being to demonstrate the central role of conceptual knowledge generation and research in risk analysis. The importance of this type of knowledge generation and research is considered undervalued in risk analysis. Several examples are used to illustrate the discussion, including a risk governance framework and the anti-fragility concept.