Toward disaster-resilient cities: characterizing resilience of infrastructure systems with expert judgments

Thermal Degradation Characteristics of Styrene-Butadiene-Styrene Copolymer Asphalt Binder Filled with an Inorganic Flame-Retarding Agent

Asphalt binder is a complex mixture of dark brown polymers composed of hydrocarbons with generally poor fire resistance. To improve its flame retardancy when used in tunnel asphalt pavements, a new inorganic flame-retardant filler (FR) containing magnesium hydroxide, aluminum hydroxide, inorganic phosphate, and melamine salt was explored. Thereafter, limiting oxygen index (LOI) and smoke suppression tests for the flame-retarded asphalt binder (FRA) mastics mixed with FR and styrene-butadiene-styrene (SBS) copolymer asphalt binder were conducted. Thermogravimetric (TG) and differential scanning calorimetry (DSC) curves for the FRA were correspondingly generated. Based on the TG data, the reaction function g(α), apparent activation energy E_a, and pre-exponential factor A were quantitatively evaluated using kinetic analysis. In addition, a Fourier transform infrared spectrometry (FTIR) test was utilized to assess the effects of the presence of FR on the chemical composition of the asphalt binder. Dynamic shear rheometer (DSR) tests were also performed to evaluate the rheological behavior of FRA. Results show that the presence of the FR significantly reduced the LOI and improved the smoke suppression during combustion of the asphalt binder mastics. The presence of FR was found to increase the E_a and the complexity of the combustion reaction, thereby improving the flame retardancy of the asphalt binder. FTIR analysis indicated that the presence of FR did not induce any strong chemical reactions to significantly impact or alter the functional groups of the asphalt binder. Furthermore, it was also observed that the rutting parameter and critical failure temperature of FRA increased with the addition of FR due to the stiffening effect of the solid FR particles.

Disaster Risk Planning With Fuzzy Goal Programming

The uncertainty in the timing and severity of disaster events makes the long-term planning of mitigation and recovery actions both critical and extremely difficult. Planners often use expected values for hazard occurrences, leaving communities vulnerable to worse-than-usual and even so-called "black swan" events. This research models disasters in terms of their best-case, most-likely, and worst-case damage estimates. These values are then embedded in a fuzzy goal programming model to provide community planners and stakeholders with the ability to strategize for any range of events from best-case to worst-case by adjusting goal weights. Examples are given illustrating the modeling approach, and an analysis is provided to illustrate how planners might use the model as a planning tool.

A Markov Decision Process Approach for Cost-Benefit Analysis of Infrastructure Resilience Upgrades

As climate change threatens to cause increasingly frequent and severe natural disasters, decisionmakers must consider costly investments to enhance the resilience of critical infrastructures. Evaluating these potential resilience improvements using traditional cost-benefit analysis (CBA) approaches is often problematic because disasters are stochastic and can destroy even hardened infrastructure, meaning that the lifetimes of investments are themselves uncertain. In this article, we develop a novel Markov decision process (MDP) model for CBA of infrastructure resilience upgrades that offer prevention (reduce the probability of a disaster) and/or protection (mitigate the cost of a disaster) benefits. Stochastic features of the model include disaster occurrences and whether or not a disaster terminates the effective life of an earlier resilience upgrade. From our MDP model, we derive analytical expressions for the decisionmaker's willingness to pay (WTP) to enhance infrastructure resilience, and conduct a comparative static analysis to investigate how the WTP varies with the fundamental parameters of the problem. Following this theoretical portion of the article, we demonstrate the applicability of our MDP framework to real-world decision making by applying it to two case studies of electric utility infrastructure hardening. The first case study considers elevating a flood-prone substation and the second assesses upgrading transmission structures to withstand high winds. Results from these two case studies show that assumptions about the value of lost load during power outages and the distribution of customer types significantly influence the WTP for the resilience upgrades and are material to the decisions of whether or not to implement them.

Prioritization of hazards for risk and resilience management through elicitation of expert judgement

Risk assessment in communities or regions typically relies on the determination of hazard scenarios and an evaluation of their impact on local systems and structures. One of the challenges of risk assessment for infrastructure operators is how to identify the most critical scenarios that are likely to represent unacceptable risks to such assets in a given time frame. This study develops a novel approach for prioritizing hazards for the risk assessment of infrastructure. Central to the proposed methodology is an expert elicitation technique termed paired comparison which is based on a formal mathematical technique for quantifying the range and variance in the judgements of a group of stakeholders. The methodology is applied here to identify and rank natural and operational hazard scenarios that could cause serious disruption or have disastrous effects to the infrastructure in the transnational Øresund region over a period of 5 years. The application highlighted substantial divergences of views among the stakeholders on identifying a single 'most critical' natural or operational hazard scenario. Despite these differences, it was possible to flag up certain cases as critical among the natural hazard scenarios, and others among the operational hazards.

Resilience-Based Repair Strategy for Gas Network System and Water Network System in Urban City

In resilience-based frameworks, optimizing the repair strategy and approaches is important for the recovery of the function of gas network systems (GNS) and water network systems (WNS). According to the resilience quantification results of GNS and WNS for a real example urban city in China, the potential impact of utilizing different repair sequences and repair/replacement approaches was investigated. First, a Monte Carlo simulation-based method was proposed to search for the optimal repair sequence according to the skew of the recovery trajectory (SRT). Under high seismic intensity conditions, the significant difference between the repair sequence corresponding to maximum SRT and minimum SRT indicates that choosing the optimal repair sequence is important in the enhancement of repair efficiency, especially when the pipelines have experienced serious damage. We also discussed the parallel repair strategy, which is more consistent with the practice, and can greatly improve the recovery efficiency compared with the single pipeline repair strategy under large damage conditions; however, under minor damage levels, the parallel repair strategy may result in a certain degree of redundancy. Next, three different repair approaches were thoroughly compared, including the point-by-point repair approach, whole pipeline replacement, and hybrid repair approach. At the condition of high seismic intensity (e.g., macroseismic intensity IX), the resilience curves for the hybrid repair approach and the pipeline replacement approach are overall similar and take less time and economic cost than the point-by-point repair approach. However, when the seismic intensity is low, the point-by-point repair approach is most efficient and has the shortest recovery time. Therefore, the choice of repair approach should be determined by stakeholders based on the specific pipeline’s damage situation. Finally, we calculated the joint resilience curves by allocating different weight factors to GNS and WNS, to represent the proportion of water and gas supply that contributes to community resilience.

Towards a Conceptual Framework for Built Infrastructure Design in an Uncertain Climate: Challenges and Research Needs

The potential risks of climate change on the built environment involve large uncertainties. This poses an intricate problem to designers and challenges a long-standing tradition of built infrastructure design. More specifically, designers are faced with this challenging question: how to rationally account for climate change risks when designing a new asset? A framework that holistically addresses this difficult question is missing from the current literature. This study contributes to this gap by (1) proposing a conceptual framework for rationally considering the effects of climate change in the design of these assets and (2) identifying the challenges that need to be overcome to facilitate the transition, and further development, of the proposed framework into practice. First, a detailed overview of important infrastructure performance requirements that are relevant to the proposed framework is presented. The different stages of the proposed conceptual framework are then outlined. The proposed framework progresses in the following order: ranking the importance of the asset, identifying the potential climate change risks, analyzing these risks, selecting a design strategy, and finally evaluating the final design. Lastly, several challenges that impede the application of the proposed framework in practical settings are identified. The proposed conceptual framework and the identified challenges comprise a necessary steppingstone towards addressing this pressing issue and developing a more practically applicable framework for considering the risks of climate change in the design of built infrastructure assets.

Integrative Interdisciplinary Approaches to Critical Infrastructure Interdependency Analysis

There is a growing understanding that cross-sector risks faced by critical infrastructure assets in natural disasters require a collaborative foresight from multiple disciplines. However, current contributions to infrastructure interdependency analysis remain centered in discipline-specific methodologies often constrained by underlying theories and assumptions. This perspective article contributes to ongoing discussions about the uses, challenges, and opportunities provided by interdisciplinary research in critical infrastructure interdependency analysis. In doing so, several modes of integration of computational modeling with contributions from the social sciences and other disciplines are explored to advance knowledge that can improve the infrastructure system resilience under extreme events. Three basic modes of method integration are identified and discussed: (a) integrating engineering models and social science research, (b) engaging communities in participative and collaborative forms of social learning and problem solving using simulation models to facilitate synthesis, exploration, and evaluation of scenarios, and (c) developing interactive simulations where IT systems and humans act as "peers" leveraging the capacity of distributed networked platforms and human-in-the-loop architectures for improving situational awareness, real-time decision making, and response capabilities in natural disasters. Depending on the conceptualization of the issues under investigation, these broadly defined modes of integration can coalesce to address key issues in promoting interdisciplinary research by outlining potential areas of future inquiry that would be most beneficial to the critical infrastructure protection communities.

Reflecting on the challenges encountered by nurses at the great Kermanshah earthquake: a qualitative study

Background

Iran has experienced an increasing number of earthquake in the past three decades. Nurses are the largest group of healthcare providers that play an important role in responding to disasters. Based on previous studies, they experienced challenges providing care in the previous disasters. Therefore, this study aimed to explore the nursing challenges to provide care to the injured in the Kermanshah earthquake, Iran.

Methods

This is a qualitative study with conventional content analysis using Granheim and Landman approach. In this study, 16 nurses involved in providing care to the injured in the Kermanshah earthquake were selected by purposeful sampling method. Data were collected using in-depth semi-structured interviews. The criteria proposed by Guba and Lincoln were used to ensure the validity of the study.

Results

Data analysis led to the emergence of 453 primary codes, 14 subcategories, and 5 categories. The five categories were as follows: (a) organizational and managerial challenges; (b) human resources; (c) infrastructure; (d) educational preparations; (e) and ethical.

Conclusions

The results of this study showed that nurses faced several challenges in providing care to earthquake victims. Based on these findings, better educational management and planning, infrastructure reform, and establishment of a crisis nursing national team seem necessary.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12912-021-00605-3.

Hazards, Infrastructure Networks and Unspecific Resilience

The aim of this paper is to provide a framework to improve urban resilience independently of the nature of the disturbances. Recent disasters had a significant impact on critical infrastructures providing essential urban services such as energy, transportation, telecommunication, water and food supply or health care. Indeed, several natural and human-made hazards may lead to disruptions, and most critical infrastructures are networked and highly interdependent. Henceforth, resilience building remain focused on specific hazards or on improving the resilience, separately, of single infrastructures. In order to enhance urban resilience, this paper is based on learnings from three case studies that are the 2001 WTC terrorist attack, hurricanes Irma and Maria in 2017 and the 2016 Seine river flood in Paris. These events highlight disruptions to urban services, but also some resilience options. In light of both the literature and our case studies, a framework of unspecific resilience is provided for improving some resilience principles, namely omnivory, redundancy, buffering, high flux, homeostasis and flatness within electric energy, water and food supply and transportation networks. Rebuilding resilience within this framework is further discussed with respect to all kinds of disruptive events.

The Urban Observatory: A Multi-Modal Imaging Platform for the Study of Dynamics in Complex Urban Systems

We describe an “Urban Observatory” facility designed for the study of complex urban systems via persistent, synoptic, and granular imaging of dynamical processes in cities. An initial deployment of the facility has been demonstrated in New York City and consists of a suite of imaging systems—both broadband and hyperspectral—sensitive to wavelengths from the visible (∼400 nm) to the infrared (∼13 micron) operating at cadences of ∼0.01–30 Hz (characteristically ∼0.1 Hz). Much like an astronomical survey, the facility generates a large imaging catalog from which we have extracted observables (e.g., time-dependent brightnesses, spectra, temperatures, chemical species, etc.), collecting them in a parallel source catalog. We have demonstrated that, in addition to the urban science of cities as systems, these data are applicable to a myriad of domain-specific scientific inquiries related to urban functioning including energy consumption and end use, environmental impacts of cities, and patterns of life and public health. We show that an Urban Observatory facility of this type has the potential to improve both a city’s operations and the quality of life of its inhabitants.

Seismic Retrofitting Resilience-Based for Strategic RC Buildings

The resilience of communities is given by the ideal convolution of the resilience of all their single parts. Strategic buildings require high levels of performance during and after a seismic sequence. Consequently, the seismic retrofitting of old strategic buildings is a central issue in prevention and mitigation strategies. The core of the study is a resilience approach to the seismic retrofitting of existing strategic buildings. Different performance levels are considered and four different retrofitting techniques are compared according to their fragility, and their post-earthquake cost and time recovery analyses. Lastly, the retrofitting techniques are compared based on the considered resilience index, which in turn is related to the estimated reduction of the seismic losses owing to the different retrofitting techniques, but especially to the effectiveness of the intervention based on the relevant cost and recovery times. In other words, these aspects take into account the key role of a building’s characteristics, and its public and strategic role during and after an earthquake. The intervention is selected not only (as is currently done) to reduce its construction times and costs, but to limit the service interruption after earthquakes. The results of this study could be operatively used as support tools in the seismic retrofitting of strategic buildings, either individually or on a large territorial scale.

An experimental investigation of resilience decision making in repeated disasters

Given the growing prevalence of catastrophic events and health epidemics, policymakers are increasingly searching for effective strategies to encourage firms to invest in resilience rather than relying on insurance or government assistance. Too often, however, resilience research focuses on decisions made by firms and emergency planners in the context of "one-off" events. We extend this research by examining resilience decision making in the more realistic context of repeated catastrophic events. Using a population of professional managers of middle market firms and a university experimental economics subject pool, we conduct a series of controlled experiments on the decision to invest in inventories to improve firm resilience to repeated catastrophic events. While existing economic and supply chain resilience research has focused on resilience in terms of avoiding some magnitude of economic losses, existing research omits a focus on the probability of those losses. Controlled experiments can evaluate the influence of probability more effectively than observational data by better controlling for magnitude and more easily accounting for repeated events. We find that decision makers are less likely to make resilience investments when a disaster has recently occurred. We further find that advisory information alone is insufficient to motivate resilience investments by firms. It must be substantiated by a history of advisory accuracy. However, we find that this effect is heavily moderated by the type of advisory information provided; we find that firm managers are much more likely to trust precautionary advice.

A spatiotemporal analysis of urban resilience to the COVID-19 pandemic in the Yangtze River Delta

The COVID-19 pandemic has severely affected the normal socioeconomic operation of countries worldwide, causing major economic losses and deaths and posing great challenges to the sustainable development of cities that play a leading role in national socioeconomic development. The strength of urban resilience determines the speed of urban social and economic recovery. This paper constructed a comprehensive evaluation index system for urban resilience under the COVID-19 pandemic scenario considering four dimensions-economy, ecology, infrastructure, and social systems-conducted a quantitative evaluation of urban resilience in the Yangtze River Delta of China, revealed its spatiotemporal differences and change trends, and proposed targeted strategies for improving urban resilience. The results show that (1) the Yangtze River Delta urban resilience system is growing stronger every year, but there are significant differences in the level of urban resilience, its spatial distribution and regional urban resilience. (2) In the Yangtze River Delta urban agglomeration, there is less distribution of areas with a higher resilience index, while those with high and medium resilience levels are more distributed. However, the resilience of most cities is low. (3) The resilience index of eastern coastal cities is significantly higher, and the resilience of cities under the COVID-19 scenario presents obvious east-west differentiation. (4) When constructing urban resilience, the individual situation of cities should be taken into account, measures adjusted according to local conditions, reasonable lessons drawn from effective international urban resilience construction, and reasonable planning policies formulated; it is important to give play to the relationship between the whole and the parts of resilience to achieve unified and coordinated development.

Conflict Resilience of Water and Energy Supply Infrastructure: Insights from Yemen

Political instability and conflicts are contemporary problems across the Middle East. They threaten not only basic security, but also infrastructure performance. Supply infrastructure, providing basic services such as water and electricity, has been subjected to damage, capacity deterioration, and the bankruptcy of public providers. Often, in conflict countries such as Yemen, the continuity of basic supply is only possible thanks to adaptation efforts on the community and household levels. This paper examines the conflict resilience of water and energy supply infrastructure in Yemen during the armed conflict 2015–today. It contributes to resilience studies by linking knowledge on state fragility and conflicts, humanitarian aid, and infrastructure resilience. The paper presents adaptation responses of communities and public entities in the water and energy sectors in Yemen and critically evaluates these responses from the perspective of conflict resilience of infrastructure. The gained insights reaffirm the notion about the remarkable adaptive capacities of communities during conflicts and the importance of incorporating community-level adaptation responses into larger efforts to enhance the conflict resilience of infrastructure systems.

The Role of Decision Analysis in Risk Analysis: A Retrospective

In commemorating the 40th anniversary of Risk Analysis, this article takes a retrospective look at some of the ways in which decision analysis (as a "sibling field") has contributed to the development both of the journal, and of risk analysis as a field. I begin with some early foundational papers from the first decade of the journal's history. I then review a number of papers that have applied decision analysis to risk problems over the years, including applications of related methods such as influence diagrams, multicriteria decision analysis, and risk matrices. The article then reviews some recent trends, from roughly the last five years, and concludes with observations about the parallel evolution of risk analysis and decision analysis over the decades-especially with regard to the importance of representing multiple stakeholder perspectives, and the importance of behavioral realism in decision models. Overall, the extensive literature surveyed here supports the view that the incorporation of decision-analytic perspectives has improved the practice of risk analysis.

mD-Resilience: A Multi-Dimensional Approach for Resilience-Based Performance Assessment in Urban Transportation

As demonstrated for extreme events, the resilience concept is used to evaluate the ability of a transportation system to resist and recover from disturbances. Motivated by the high cumulative impact of recurrent perturbations on transportation systems, we have investigated resilience quantification as a performance assessment method for high-probability low-impact (HPLI) disturbances such as traffic congestions. Resilience-based metrics are supplementary to conventional travel-time-based indices in literature. However, resilience is commonly quantified as a scalar variable despite its multi-dimensional nature. Accordingly, by hypothesizing increased information gain in performance assessment, we have investigated a multi-dimensional approach (mD-Resilience) for resilience quantification. Examining roadways’ resilience to recurrent congestions as a contributor to sustainable mobility, we proposed to measure resilience with several attributes that characterize the degradation stage, the recovery stage, and possible recovery paths. These attributes were integrated into a performance index by using Data Envelopment Analysis (DEA) as a non-parametric method. We demonstrated the increased information gain by quantifying the performance of major freeways in Los Angeles, California using Performance Measurement System (PeMS) data. The comparison of mD-Resilience approach with the method based on area under resilience curves showed its potential in distinguishing the severity of congestions. Furthermore, we showed that mD-Resilience also characterizes performance from the lens of delay and bottleneck severities.

Integration of Critical Infrastructure and Societal Consequence Models: Impact on Swedish Power System Mitigation Decisions

Critical infrastructures provide society with services essential to its functioning, and extensive disruptions give rise to large societal consequences. Risk and vulnerability analyses of critical infrastructures generally focus narrowly on the infrastructure of interest and describe the consequences as nonsupplied commodities or the cost of unsupplied commodities; they rarely holistically consider the larger impact with respect to higher-order consequences for the society. From a societal perspective, this narrow focus may lead to severe underestimation of the negative effects of infrastructure disruptions. To explore this theory, an integrated modeling approach, combining models of critical infrastructures and economic input-output models, is proposed and applied in a case study. In the case study, a representative model of the Swedish power transmission system and a regionalized economic input-output model are utilized. This enables exploration of how a narrow infrastructure or a more holistic societal consequence perspective affects vulnerability-related mitigation decisions regarding critical infrastructures. Two decision contexts related to prioritization of different vulnerability-reducing measures are considered-identifying critical components and adding system components to increase robustness. It is concluded that higher-order societal consequences due to power supply disruptions can be up to twice as large as first-order consequences, which in turn has a significant effect on the identification of which critical components are to be protected or strengthened and a smaller effect on the ranking of improvement measures in terms of adding system components to increase system redundancy.

Towards Resilient Civil Infrastructure Asset Management: An Information Elicitation and Analytical Framework

It is rather difficult for the stakeholders to understand and implement the resilience concept and principles in the infrastructure asset management paradigm, as it demands quality data, holistic information integration and competent data analytics capabilities to identify infrastructure vulnerabilities, evaluate and predict infrastructure adaptabilities to different hazards, as well as to make damage restoration and resilience improvement strategies and plans. To meet the stakeholder’s urgent needs, this paper proposes an information elicitation and analytical framework for resilient infrastructure asset management. The framework is devised by leveraging the best practices and processes of integrated infrastructure asset management and resilience management in the literature, synergizing the common elements and critical concepts of the two paradigms, ingesting the state-of-the-art interconnected infrastructure systems resilience analytical approaches, and eliciting expert judgments to iteratively improve the derived framework. To facilitate the stakeholders in implementing the framework, two use case studies are given in this paper, depicting the detailed workflow for information integration and resilience analytics in infrastructure asset management. The derived framework is expected to provide an operational basis to the quantitative resilience management of civil infrastructure assets, which could also be used to enhance community resilience.

Does a review of urban resilience allow for the support of an evolutionary concept?

Over the last five decades, resilience has received ever greater interest from academics and practitioners and has been applied in different scientific areas, such as engineering, environmental science or medicine. In particular, resilience has become a fundamental concept in contemporary urban development, planning and management (UDPM). Despite the various reviews that have recently been made of this subject, an updated analysis of the concept is required so that commonly held views about resilience can be matched against empirical evidence while, at the same time, clarifying the use of its main formulations and connecting its embryonic development to its application in urban-centric research. This paper therefore reviews the concept of resilience (considering its primary formulations, its historical evolution and its conceptual underpinnings), establishing how it has been applied and developed in the UDPM context. Based on this review, this paper reiterates the idea of a three-dimensional framework for exploring the concept of resilience ([1] 'engineering' vs. [2] 'ecological' vs. [3] 'evolutionary resilience'). The search for urban resilience can potentially adopt an integrative approach, assuming an evolutionary perspective that can be adapted to different situations and stakeholders, thus offering a better adjusted and more dynamic urban planning and management.

Review of the Quantitative Resilience Methods in Water Distribution Networks

Water distribution networks (WDNs) are critical contributors to the social welfare, economic growth, and public health in cities. Under the uncertainties that are introduced owing to climate change, urban development, aging components, and interdependent infrastructure, the WDN performance must be evaluated using continuously innovative methods and data acquisition. Quantitative resilience assessments provide useful information for WDN operators and planners, enabling support systems that can withstand disasters, recover quickly from outages, and adapt to uncertain environments. This study reviews contemporary approaches for quantifying the resilience of WDNs. 1508 journal articles published from 1950 to 2018 are identified under systematic review guidelines. 137 references that focus on the quantitative resilience methods of WDN are classified as surrogate measures, simulation methods, network theory approaches, and fault detection and isolation approaches. This study identifies the resilience capability of the WDNs and describes the related terms of absorptive, restorative, and adaptive capabilities. It also discusses the metrics, research progresses, and limitations associated with each method. Finally, this study indicates the challenges associated with the quantification of WDNs that should be overcome for achieving improved resilience assessments in the future.

(Re)emphasizing Urban Infrastructure Resilience via Scoping Review and Content Analysis

Although the importance of urban infrastructure resilience can be inferred, its terminology remains convoluted within the literature due to a lack of systematic review from a sustainable development planning perspective. This review paper was designed to elucidate connected research themes, scientific popularity, and conceptual boundaries of the term infrastructure resilience in an urban context. Three guiding research questions were asked: What does urban infrastructure resilience really mean? What are the most common research topics connected to urban infrastructure resilience? How can humanity further improve urban infrastructure resilience from a sustainable development planning perspective? To answer these research questions, a two-step literature analysis was adopted consisting of: (i) a scoping review to select relevant publications based on a specific search query; and (ii) a content analysis to reduce and synthesize the scoping review findings further based on the three most applicable publishing outlets. The scoping review reduced articles to 535, while content analysis further condensed it to 84 across three key journals. With North America and Europe leading, the findings corroborated that eight connected subject areas establish the conceptual boundaries of urban infrastructure resilience. The eight related research topics in decreasing abundance were: (1) climate change, (2) floods, (3) disasters, (4) environmental policy, (5) ecosystems, (6) risk assessment, (7) emergency preparedness, and (8) adaptation. In conclusion, these research topics should be pursued when creating urban infrastructure resilience strategies for moving towards sustainability.

Critical Infrastructures: The Operational Environment in Cases of Severe Disruption

The functioning and resilience of modern societies have become more and more dependent on critical infrastructures. Severe disturbance to critical infrastructure is likely to reveal chaotic operational conditions, in which infrastructure service providers, emergency services, police, municipalities, and other key stakeholders must act effectively to minimize damages and restore normal operations. This paper aims to better understand this kind of operational environment resulting from, for example, a terrorist attack. It emphasizes mutual interdependencies among key stakeholders in such situations. The empirical contribution is based on observations from a workshop, in which participants representing the critical services and infrastructures in Finland discussed in thematic groups. Two scenarios guided the workshop discussions; nationwide electricity grid disruption and presumably intentionally contaminated water supply in a city. The results indicate that more attention should be paid to the interdependencies between critical infrastructures, as well as to the latent vulnerabilities hidden inside the systems. Furthermore, producing security seems to require continuous interaction and creation of meanings between extremely different actors and logics. This implies a need for changes in thinking, particularly concerning the ability to define problems across conventional administrative structures, geographical boundaries and conferred powers.

Resilience of Critical Infrastructures: Review and Analysis of Current Approaches

In crisis situations, systems, organizations, and people must react and deal with events that are inherently unpredictable before they occur: vital societal functions and thus infrastructures must be restored or adapted as quickly as possible. This capacity refers to resilience. Progress concerning its conceptualization has been made but it remains difficult to assess and apply in practice. The results of this article stem from a literature review allowing the analysis of current advances in the development of proposals to improve the management of infrastructure resilience. The article: (i) identifies different dimensions of resilience; (ii) highlights current limits of assessing and controlling resilience; and (iii) proposes several directions for future research that could go beyond the current limits of resilience management, but subject to compliance with a number of constraints. These constraints are taking into account different hazards, cascade effects, and uncertain conditions, dealing with technical, organizational, economical, and human domains, and integrating temporal and spatial aspects.

Assessment of Critical Infrastructure Resilience to Flooding Using a Response Curve Approach

Following a flood the functioning of critical infrastructure (CI), such as power and transportation networks, plays an important role in recovery and the resilience of the city. Previous research investigated resilience indicators, however, there is no method in the literature to quantify the resilience of CI to flooding specifically or to quantify the effect of measures. This new method to quantify CI resilience to flooding proposes an expected annual disruption (EADIS) metric and curve of disruption versus likelihood. The units used for the EADIS metric for disruption are in terms of people affected over time (person × days). Using flood modelling outputs, spatial infrastructure, and population data as inputs, this metric is used to benchmark CI resilience to flooding and test the improvement with resilience enhancing measures. These measures are focused on the resilience aspects robustness, redundancy and flexibility. Relative improvements in resilience were quantified for a case study area in Toronto, Canada and it was found that redundancy, flexibility, and robustness measures resulted in 44, 30, and 48% reductions in EADIS respectively. While there are limitations, results suggest that this method can effectively quantify CI resilience to flooding and quantify relative improvements with resilience enhancing measures for cities.

Holistic Infrastructure Resilience Research Requires Multiple Perspectives, Not Just Multiple Disciplines

Resilience research includes multiple definitions, concepts, perspectives, and applications across a broad range of academic disciplines. While experts, policy-makers, and practitioners assert that resilience requires holism, what is considered holistic is rarely discussed. The traditional scientific approach to holism is to engage multiple disciplines. However, this review studies an alternative approach to holism that engages multiple perspectives, as suggested by integral theory. An integral approach requires consideration of at least four irreducible domains: (1) subjective experience, (2) intersubjective culture, (3) objective behavior, and (4) interobjective systems. This way of approaching holism both engages multiple disciplines and reveals important gaps in the popular understanding of resilient infrastructure. For example, organizing the 20 most highly cited resilience research articles from all disciplines according to the Integral Map reveals that most articles in the sample set are distributed among three of the four perspectives corresponding to experience, behavior, and systems. None of the most popular articles studies resilience through the lens of culture. Thus, the importance of factors such as organizational values and group intentionality may be underappreciated in the scholarly literature.

Resilience Analysis of Countries under Disasters Based on Multisource Data

Disasters occur almost daily in the world. Because emergencies frequently have no precedent, are highly uncertain, and can be very destructive, improving a country's resilience is an efficient way to reduce risk. In this article, we collected more than 20,000 historical data points from disasters from 207 countries to enable us to calculate the severity of disasters and the danger they pose to countries. In addition, 6 primary indices (disaster, personal attribute, infrastructure, economics, education, and occupation) including 38 secondary influencing factors are considered in analyzing the resilience of countries. Using these data, we obtained the danger, expected number of deaths, and resilience of all 207 countries. We found that a country covering a large area is more likely to have a low resilience score. Through sensitivity analysis of all secondary indices, we found that population density, frequency of disasters, and GDP are the three most critical factors affecting resilience. Based on broad-spectrum resilience analysis of the different continents, Oceania and South America have the highest resilience, while Asia has the lowest. Over the past 50 years, the resilience of many countries has been improved sharply, especially in developing countries. Based on our results, we analyze the comprehensive resilience and provide some optimal suggestions to efficiently improve resilience.

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.

Analysis of Affordance, Time, and Adaptation in the Assessment of Industrial Control System Cybersecurity Risk

Industrial control systems increasingly use standard communication protocols and are increasingly connected to public networks-creating substantial cybersecurity risks, especially when used in critical infrastructures such as electricity and water distribution systems. Methods of assessing risk in such systems have recognized for some time the way in which the strategies of potential adversaries and risk managers interact in defining the risk to which such systems are exposed. But it is also important to consider the adaptations of the systems' operators and other legitimate users to risk controls, adaptations that often appear to undermine these controls, or shift the risk from one part of a system to another. Unlike the case with adversarial risk analysis, the adaptations of system users are typically orthogonal to the objective of minimizing or maximizing risk in the system. We argue that this need to analyze potential adaptations to risk controls is true for risk problems more generally, and we develop a framework for incorporating such adaptations into an assessment process. The method is based on the principle of affordances, and we show how this can be incorporated in an iterative procedure based on raising the minimum period of risk materialization above some threshold. We apply the method in a case study of a small European utility provider and discuss the observations arising from this.

Quantifying the Effects of Expert Selection and Elicitation Design on Experts' Confidence in Their Judgments About Future Energy Technologies

Expert elicitations are now frequently used to characterize uncertain future technology outcomes. However, their usefulness is limited, in part because: estimates across studies are not easily comparable; choices in survey design and expert selection may bias results; and overconfidence is a persistent problem. We provide quantitative evidence of how these choices affect experts' estimates. We standardize data from 16 elicitations, involving 169 experts, on the 2030 costs of five energy technologies: nuclear, biofuels, bioelectricity, solar, and carbon capture. We estimate determinants of experts' confidence using survey design, expert characteristics, and public R&D investment levels on which the elicited values are conditional. Our central finding is that when experts respond to elicitations in person (vs. online or mail) they ascribe lower confidence (larger uncertainty) to their estimates, but more optimistic assessments of best-case (10th percentile) outcomes. The effects of expert affiliation and country of residence vary by technology, but in general: academics and public-sector experts express lower confidence than private-sector experts; and E.U. experts are more confident than U.S. experts. Finally, extending previous technology-specific work, higher R&D spending increases experts' uncertainty rather than resolves it. We discuss ways in which these findings should be seriously considered in interpreting the results of existing elicitations and in designing new ones.

Modelling a critical infrastructure-driven spatial database for proactive disaster management: A developing country context

The understanding and institutionalisation of the seamless link between urban critical infrastructure and disaster management has greatly helped the developed world to establish effective disaster management processes. However, this link is conspicuously missing in developing countries, where disaster management has been more reactive than proactive. The consequence of this is typified in poor response time and uncoordinated ways in which disasters and emergency situations are handled. As is the case with many Nigerian cities, the challenges of urban development in the city of Abeokuta have limited the effectiveness of disaster and emergency first responders and managers. Using geospatial techniques, the study attempted to design and deploy a spatial database running a web-based information system to track the characteristics and distribution of critical infrastructure for effective use during disaster and emergencies, with the purpose of proactively improving disaster and emergency management processes in Abeokuta.Keywords: Disaster Management; Emergency; Critical Infrastructure; Geospatial Database; Developing Countries; Nigeria

Portable ultrasound in disaster triage: a focused review

Ultrasound technology has become ubiquitous in modern medicine. Its applications span the assessment of life-threatening trauma or hemodynamic conditions, to elective procedures such as image-guided peripheral nerve blocks. Sonographers have utilized ultrasound techniques in the pre-hospital setting, emergency departments, operating rooms, intensive care units, outpatient clinics, as well as during mass casualty and disaster management. Currently available ultrasound devices are more affordable, portable, and feature user-friendly interfaces, making them well suited for use in the demanding situation of a mass casualty incident (MCI) or disaster triage. We have reviewed the existing literature regarding the application of sonology in MCI and disaster scenarios, focusing on the most promising and practical ultrasound-based paradigms applicable in these settings.