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Stakeholders in multimodal freight transport encounter significant challenges due to the multitude of unknowns and inherent risks that can adversely affect operations. The subjective nature of the information complicates the identification and assessment of these risks, making them particularly challenging in the context of multimodal transport, where the potential consequences can be substantial. This research intends to provide a comprehensive understanding of the asymmetries in risks associated with multimodal freight transport by identifying and evaluating quantitative hazards. By integrating fuzzy set theory and failure mode and effects analysis (FMEA), the study offers a structured approach to statistically forecast risks, addressing imprecision in traditional risk assessments. Qualitative interviews conducted with multimodal freight transport operators in Thailand reveal critical insights, including the identification of high-priority risks such as delays from regulatory compliance, inadequate infrastructure, and inefficiencies in stakeholder communication. The findings of this study not only highlight these pressing issues but also provide actionable strategies to mitigate risks, thereby enhancing the operational resilience of multimodal freight transport systems.

High-frequency drought hazards have presented persistent challenges for environmental management and sustainable development in the South Hebei Plain, China. In this paper, the assessment of meteorological droughts in the South Hebei Plain was conducted using a multifaceted approach to ensure a comprehensive analysis. Our results demonstrated that distinct timescale cycles, ranging from centennial–semicentennial to interdecadal variations, can be identified over the past few centuries. These cycles aligned with patterns observed in the middle Yangtze basin and corresponded to regional climatic conditions. The drought cycles in the South Hebei Plain showed significant correlations with variations in the monsoon climate, sunspot activity, global changes, and human disturbances. Changes in the frequency, duration, and intensity of droughts have notably impacted hydrological variations. Extreme droughts, in particular, have heightened concerns about their effects on river systems, potentially increasing the risk of channel migration. This study enhanced our understanding of meteorological hazard patterns in the South Hebei Plain and provided valuable insights into different stages of drought management. It thus can offer lessons for improving drought preparedness and resilience and for formulating adaptive measures to mitigate future droughts and promote regional sustainability.

Greater Montreal is situated in a region with moderate seismic activity and rests on soft ground deposits from the ancient Champlain Sea, as well as more recent alluvial deposits from the Saint Lawrence River. These deposits have the potential to amplify seismic waves, as demonstrated by past strong, and recent weak, earthquakes. Studies based on the 2015 National Seismic Hazard Model (SHM5) had estimated losses to residential buildings at 2% of their value for an event with a return period of 2475 years. In 2020, the seismic hazard model was updated (SHM6), resulting in more severe hazards for eastern Canada. This paper aims to quantify the impact of these changes on losses to residential buildings in Greater Montreal. Our exposure database includes population and buildings at the scale of dissemination areas (500–1000 inhabitants). Buildings are classified by occupancy and construction type and grouped into three building code levels based on year of construction. The value of buildings is obtained from property-valuation rolls and the content value is derived from insurance data. Damage and losses are calculated using Hazus software developed for FEMA. Losses are shown to be 53% higher than the SHM5 estimates.

African Swine Fever poses a significant threat to pig production. An outbreak in Denmark would have severe economic consequences, potentially resulting in a loss between 335 million and 670 million euros. To mitigate the major risk factors, the Danish authorities and the Danish pig industry have implemented several risk-reducing measures. The small wild boar population in Danish nature has been culled, and a fence between Denmark and Germany has been constructed to stop or reduce the risk of migrating wild boar from Germany. All trucks arriving from abroad, intended for the transport of Danish pigs, are inspected, washed, and disinfected at facilities near the border before being allowed to transport pigs between herds or from herds out of Denmark. Cross-border trade of feedstuffs and potentially risky materials is continuously monitored. Based on risk assessments, feed types or bedding materials from countries with African Swine Fever that could contain parts of wild boar are banned from Danish pig herds. Certain types of fats and oils from countries with African Swine Fever can only be used after heat treatment. The import of whole kernels of corn, wheat, or barley is not considered a risk.

The application of antimicrobials in aquaculture primarily aims to prevent and treat bacterial infections in fish, but their inappropriate use may result in the emergence of zoonotic antibiotic-resistant bacteria and the subsequent transmission of resistant strains to humans via food consumption. The aquatic environment serves as a potential reservoir for resistant bacteria, providing an ideal breeding ground for development of antimicrobial resistance (AMR). The mutual inter-connection of intensive fish-farming systems with terrestrial environments, the food processing industry and human population creates pathways for the transmission of resistant bacteria, exacerbating the problem further. The aim of this study was to provide an overview of the most effective and available risk mitigation strategies to tackle AMR in aquaculture, based on the One Health (OH) concept. The stringent antimicrobial use guidelines, promoting disease control methods like enhanced farm biosecurity measures and vaccinations, alternatives to antibiotics (ABs) (prebiotics, probiotics, immunostimulants, essential oils (EOs), peptides and phage therapy), feeding practices, genetics, monitoring water quality, and improving wastewater treatment, rather than applying excessive use of antimicrobials, can effectively prevent the development of AMR and release of resistant bacteria into the environment and food. The contribution of the environment to AMR development traditionally receives less attention, and, therefore, environmental aspects should be included more prominently in OH efforts to predict, detect and prevent the risks to health. This is of particular importance for low and middle-income countries with a lack of integration of the national AMR action plans (NAPs) with the aquaculture-producing environment. Integrated control of AMR in fisheries based on the OH approach can contribute to substantial decrease in resistance, and such is the case in Asia, where in aquaculture, the percentage of antimicrobial compounds with resistance exceeding 50% (P50) decreased from 52% to 22% within the period of the previous two decades.

A company’s cyber defenses are based on a secure infrastructure and risk-aware behavior by employees. With rising cyber threats and normative training efforts showing limited impact, raising cyber risk awareness is emerging as a challenging effort. The review of the extant literature on awareness diagnosis shows interdisciplinary but mainly theoretical approaches to understanding attitudes and influencing risk behavior. We propose and test a novel methodology to combine and operationalize two tools, deep metaphor interviews and the IDEA risk communication model, to apply them for the first time in the context of behavioral cyber vulnerabilities. The results show a link between diagnosed attitudes and effective risk behavior in a real-life organizational setting, indicating the potential for an expanded diagnostic effort. We propose to develop a broader diagnostic and intervention set to improve cyber awareness and a toolkit to support the business practice of cyber risk management.

Residential energy retrofitting projects in the hot summer and cold winter (HSCW) zone of China face various risks related to project activities, which incur transaction costs (TCs), such as search, negotiation, and monitoring costs. As the leader in project implementation, the Chinese government is responsible for project planning, organisation, and coordination. However, TCs impede the government’s ability to execute risk-related project activities effectively, subsequently increasing the probability of the occurrence of risk. Drawing on transaction cost economics (TCE), this study proposes a theoretical framework to understand the barriers—such as asset specificity, uncertainty, and frequency—that prevent the government from performing project activities and mitigating risks effectively. An artificial neural network (ANN) is applied to verify the hypotheses. The results underscore experience and operational maturity in project activities, cost and time constraints, and the immature retrofitting market as significant impediments to the government’s execution of risk-related activities. Considering the varying roles of the government in reducing different risks, this study concludes by offering policy recommendations to alleviate these activity barriers and mitigate risks. By employing a TCs perspective, this study not only identifies key barriers but also deepens our understanding of risk mitigation mechanisms, providing robust policy insights tailored to the specific regional context of China, thereby enhancing both the execution and the framework of government-led retrofitting projects.

The abandonment of inland areas has become a major demographical challenge, causing a condition of local fragility in terms of spatial marginalization. To deal with this issue in Italy, a number of policy actions have been implemented over the time, namely the National Strategy for Inland Areas, established a decade ago, and more recently the Next Generation EU (NGEU) to foster local economic recovery and employment. In this context, RI.P.R.O.VA.RE., a project funded by the former Italian Ministry of the Environment and Protection of Land and Sea (MATTM), was aimed at strengthening the resilience features of communities and territories, focusing on areas within the Matese and Ufita in the Campania region and the Medio Agri in the Basilicata region (southern Italy). Besides the ability to respond to different pressure factors (e.g., of demographic and economic origin), the project also addressed issues concerning seismic and flood risks. This paper synthesizes the methods and tools provided for their analysis and mitigation as a prerequisite for regenerating inland areas. After presenting the developed methods and tools, the results obtained for the Matese study area are presented and discussed. While, on the one hand, the retrieved risk zoning maps allow individuating those municipalities requiring priority structural interventions, on the other hand, the latter are properly individuated based on the peculiar characteristics of urban fabrics.

This paper presents the cloud vendor lock-in prediction framework (CVL), which aims to address the challenges that arise from vendor lock-in in cloud computing. The framework provides a systematic approach to evaluate the extent of dependency between service providers and consumers and offers predictive risk analysis and detailed cost assessments. At the heart of the CVL framework is the Dependency Module, which enables service consumers to input weighted factors that are critical to their reliance on cloud service providers. These factors include service costs, data transfer expenses, security features, compliance adherence, scalability, and technical integrations. The research delves into the critical factors that are necessary for dependency calculation and cost analysis, providing insights into determining dependency levels and associated financial implications. Experimental results showcase dependency levels among service providers and consumers, highlighting the framework’s utility in guiding strategic decision-making processes. The CVL is a powerful tool that empowers service consumers to proactively navigate the complexities of cloud vendor lock-in. By offering valuable insights into dependency levels and financial implications, the CVL aids in risk mitigation and facilitates informed decision-making.

Portable air purifiers have been extensively used to improve indoor air quality and mitigate the transmission of airborne diseases. However, the efficacy of mitigation is strongly affected by the interactions between jet flows of processed air from the air purifiers and the background airflows driven by the ventilation system. Critical factors in this context include the position and capacity of air purifiers and the ventilation rate of the heating ventilation and air-conditioning (HVAC) system. These factors are investigated in this study via computational fluid dynamics (CFD) simulations and the infection probability for different scenarios is quantified using the latest airborne infection predictive model incorporating recent pathological and clinical data for SARS-CoV-2. The results show that the use of air purifiers can significantly reduce the concentration of particulate matter, thus contributing to a generally lower risk of airborne transmission. However, the position of air purifiers affects their overall efficacy remarkably. Comparatively, a central HVAC system is more efficient at removing airborne particles under an equivalent ventilation rate assuming it uses a mixing ventilation scheme.

This paper demonstrates how historical research is a valuable tool for identifying past geological, geomorphological and climatic hazards and therefore critical for mitigating and reducing future risk. The authors describe the potential of a scientific field that straddles that of the geologist, geographer, historian and archivist. Historical records include a range of materials and sources of information, which can be very diverse; from written documents to cartographies, and from drawings to marble tombstones. They are all useful and convey important data, on the date of the event, the size of the phenomena, sometimes on ground effects, damage or magnitude. The authors discuss how to conduct historical research by providing a list of locations and how important historical documents can be found. Works that mention geological phenomena are listed, starting with the first occasional descriptions by individuals in letters, up to very specific publications in individual fields of interest. With this introduction, the editors of the Special Issue wish to draw attention to the importance of historical documentation, which is too often ignored or considered of low priority by the scientific community, but can contain key information on events, their impacts and social and cultural adaptations.

The internet of things (IoT) and social media provide information related to disasters that could help businesses to strategically mitigate risks and optimize their supply chain during difficult times. This paper proposes a framework to show how business or supply chain enterprisers can collaborate with community and government in disaster supply chain risk management. Businesses must have an established risk mitigation plan, update it periodically and implement promptly. Community collaboration can build a resilient society, and government should play an important role in leading both financial and non-financial support during natural disasters and pandemic management. The IoT and social media are new mechanisms as a vocal point to enable government, ensuring trustworthiness of information, to provide the community with a means to express needs and feedback, and to assist business services to meet the changeable preferences under risk threats. Social media can be a collaborative effort between all the parties and helps make value added decisions efficiently in supply chain risk management.

Infant formula milk (IFM) is critical in the diet of many babies and must be of high-quality. Unfortunately, IFM has been a target of adulteration by those attempting to make illegal profits and has suffered from contamination-related issues. This study’s main objective was to identify the most critical risks affecting IFM quality in the supply chain and determine mitigation strategies to improve IFM performance measurement. We developed a model to reduce adulteration and contamination rates in the infant formula milk supply chains (IFMSCs) and maximize safety. The steps to achieve the study’s objectives included: (1) identifying the importance of IFMs for infant nutrition and their risks; (2) establishing mitigation criteria for evaluating IFMSC’s performance to maximize quality; and (3) analyzing each mitigation criterion to maximize IFM safety. Based on pairwise comparisons by professionals in the food supply chain (FSC) of decision-making, the Analytic Hierarchy Process (AHP) model was used to analyze and prioritize mitigation alternatives. According to the contamination quality risk agent, mitigation alternative (QR.M2) ranked highest. This study’s findings illustrate how vital avoiding risk is when dealing with public health, especially infants’ health, and how IFM must undergo precise testing and quality checks at every supply chain stage to ensure quality.

Increased demand for sustainable timber products has resulted in large investments in agroforestry in Australia, with plantations growing various Pinus species, selected to suit a plantation’s environment. Juvenile Pinus species have a low fire tolerance. With Australia’s history of wildfires and the likelihood of climate change exacerbating that risk, the potential for a total loss of invested capital is high unless cost-effective targeted risk minimisation is part of forest management plans. Based on the belief that the understory profiles within the juvenile plantations are a major factor determining fuel hazard risks, an accurate assessment of these profiles is required to effectively mitigate those risks. At present, assessment protocols are largely reliant on ground-based observations, which are labour-intensive, time consuming, and expensive. This research project investigates the effectiveness of using geospatial analysis of drone-derived photographic data collected in the commercial pine plantations of south-eastern Queensland as a cost-saving alternative to current fuel hazard risk assessment practices. Understory composition was determined using the supervised classification of orthomosaic images together with derivations of canopy height models (CHMs). The CHMs were subjected to marker-controlled watershed segmentation (MCWS) analysis, isolating and removing the plantation pine trees, enabling the quantification of understory fuel profiles. The method used proved highly applicable to immature forest environments with minimal canopy closure, but became less reliable for close canopied older plantations.

Graphene-based polymer composites are innovative materials which have recently found wide application in many industrial sectors thanks to the combination of their enhanced properties. The production of such materials at the nanoscale and their handling in combination with other materials introduce growing concerns regarding workers’ exposure to nano-sized materials. The present study aims to evaluate the nanomaterials emissions during the work phases required to produce an innovative graphene-based polymer coating made of a water-based polyurethane paint filled with graphene nanoplatelets (GNPs) and deposited via the spray casting technique. For this purpose, a multi-metric exposure measurement strategy was adopted in accordance with the harmonized tiered approach published by the Organization for Economic Co-operation and Development (OECD). As a result, potential GNPs release has been indicated near the operator in a restricted area not involving other workers. The ventilated hood inside the production laboratory guarantees a rapid reduction of particle number concentration levels, limiting the exposure time. Such findings allowed us to identify the work phases of the production process with a high risk of exposure by inhalation to GNPs and to define proper risk mitigation strategies.

In today’s world, financial institutions (FIs) play a pivotal role in any country’s economic growth and are vital for intermediation between the providers of investable funds, such as depositors, investors and users. FIs focus on developing effective policies for financial fraud risk mitigation however, timely prediction of financial fraud risk helps overcome it effectively and efficiently. Thus, herein, we propose a novel approach for predicting financial fraud using machine learning. We have used transaction-level features of 6,362,620 transactions from a synthetic dataset and have fed them to various machine-learning classifiers. The correlation of different features is also analysed. Furthermore, around 5000 more data samples were generated using a Conditional Generative Adversarial Network for Tabular Data (CTGAN). The evaluation of the proposed predictor showed higher accuracies which outperformed the previously existing machine-learning-based approaches. Among all 27 classifiers, XGBoost outperformed all other classifiers in terms of accuracy score with 0.999 accuracies, however, when evaluated through exhaustive repeated 10-fold cross-validation, the XGBoost still gave an average accuracy score of 0.998. The findings are particularly relevant to financial institutions and are important for regulators and policymakers who aim to develop new and effective policies for risk mitigation against financial fraud.

This paper presents a decision support tool for promoters/investors of geothermal energy projects, based on a decision tree (DT) structure. The DT aims to assist stakeholders to select public engagement strategies, alternative financing solutions and risk mitigation measures (or options) for geothermal energy projects. Public engagement is necessary for the successful development and operation of geothermal projects. Available studies (including toolkits and protocols) commonly list a set of practices for social engagement without providing information on the factors which render certain options more suitable than others. The presented tool offers a transparent framework to how relevant decisions could be managed by providing a sequence of questions that focus on social, environmental, resource risk, and financial influencing factors and to realise community engagement into geothermal projects. This work is part of the Horizon 2020 CROWDTHERMAL project, which aims at empowering the public to directly participate in the development of geothermal projects through social engagement tools and alternative financing schemes, like crowdfunding.

The application of antimicrobials in aquaculture primarily aims to prevent and treat bacterial infections in fish, but their inappropriate use may result in the emergence of zoonotic antibiotic-resistant bacteria and the subsequent transmission of resistant strains to humans via food consumption. The aquatic environment serves as a potential reservoir for resistant bacteria, providing an ideal breeding ground for development of antimicrobial resistance (AMR). The mutual inter-connection of intensive fish-farming systems with terrestrial environments, the food processing industry and human population creates pathways for the transmission of resistant bacteria, exacerbating the problem further. The aim of this study was to provide an overview of the most effective and available risk mitigation strategies to tackle AMR in aquaculture, based on the One Health (OH) concept. The stringent antimicrobial use guidelines, promoting disease control methods like enhanced farm biosecurity measures and vaccinations, alternatives to antibiotics (ABs) (prebiotics, probiotics, immunostimulants, essential oils (EOs), peptides and phage therapy), feeding practices, genetics, monitoring water quality, and improving wastewater treatment, rather than applying excessive use of antimicrobials, can effectively prevent the development of AMR and release of resistant bacteria into the environment and food. The contribution of the environment to AMR development traditionally receives less attention, and, therefore, environmental aspects should be included more prominently in OH efforts to predict, detect and prevent the risks to health. This is of particular importance for low and middle-income countries with a lack of integration of the national AMR action plans (NAPs) with the aquaculture-producing environment. Integrated control of AMR in fisheries based on the OH approach can contribute to substantial decrease in resistance, and such is the case in Asia, where in aquaculture, the percentage of antimicrobial compounds with resistance exceeding 50% (P50) decreased from 52% to 22% within the period of the previous two decades.

Quiescent faults may be capable of creating catastrophic earthquakes in locations with moderate and/or low seismic activity, such as Egypt. This study combines structural, remote sensing (RS), geophysical, and seismic activity data to examine and analyze the relationship between tectonic structures and seismotectonic activity in Egypt. In a new seismo-lineaments map of Egypt, tectonic lineaments of the Egyptian mainland were delineated and classified. The database contains 8000 lineaments that were divided into distinct geographical zones using statistical analysis and general features. Delineated lineaments were integrated with digitized geological and geophysical surface and subsurface faults and geographic information systems (GIS) processing techniques were applied to produce 4249 faults. The spatial distribution of seismic activity was determined to extract 1968 competent faults out of 4249 capable faults (i.e., greater than 10 km and suitably orientated concerning the existing stress field). Maximum expected magnitudes (Mmax) were calculated for distinct seismogenic locations in Egypt, taking into account the nature of the regional rupture. At the national scale, empirical scaling relations between fault lengths and earthquake magnitude were employed for all mapped faults in Egypt. The findings concerning the faults were highly consistent with traditional geological information. The results suggest that our technique for estimating the highest predicted magnitudes produces similar values and might be used to evaluate Egypt’s possible future seismic hazard. The results were compared to seismic databases. The similarity of our results with those reported in the catalogs lends confidence to the proposed scheme.

This paper proposes a qualitative model to overcome the limitations of conventional failure mode and effects analysis (FMEA), which does not consider risk mitigation capabilities when prioritizing risks. Failure to consider these capabilities can lead to unrealistic risk estimates, especially when the level of uncertainty is high. In the proposed model, the original applicability of conventional FMEA was retained along with the three conventional risk variables, namely, severity, occurrence, and detectability. In addition, a fourth variable was added to account for risk mitigation capabilities. A case study in the project selection of aircraft repairs was used to demonstrate the implementation of the model and its applicability. The results show that the inclusion of mitigation options leads to more realistic risk scenarios, suggesting that the original FMEA approach may lead to non-conservative risk estimates.

The current Special Issue is a digest of 13 published articles that referred to the following scientific and professional areas: construction project management and quality management in construction engineering and supervision; cost discount and the financial control of construction projects; multi-criteria feasibility studies of investment enterprises; the qualitative and quantitative research of engineering buildings by probabilistic and fuzzy sets approach; multidiscipline expertise investigations of buildings that significantly differ in structure and use.

One of the major challenges regarding energy transition is to create active support towards renewable energy installations on a local level. The CROWDTHERMAL project presents practical approaches for involving local stakeholders in different measures in order to develop acceptable solutions. Based on technical evidence and data from concrete case studies, the project shows ways how community funding can increase social acceptance towards geothermal energy installations. The presented solutions are based on alternative financial schemes studies and risk mitigation analysis in geothermal projects.

Recent earthquake events have highlighted the importance of critical infrastructure (CI) resilience, as a strong correlation was found between economic loss and severity of CI damage. CIs are characterized by a complex structure composed of sub-components that are essential for the continuous performance of the system. CI owners and governments allocate ample resources to retrofitting and upgrading CI systems and components to increase the resilience of CIs and reduce risk in case of seismic events. Governments and decision makers must manage and optimize the retrofitting efforts to meet budget and time constraints. This research presents a probabilistic methodology for CI seismic risk mitigation and management. The risk expectancy is appraised according to an FTA-based stochastic simulation. The simulation includes the development of exclusive fragility curves for the CI and an examination of the expected damage distribution as a function of earthquake intensity and fragility uncertainty of the components. Furthermore, this research proposes a novel RMIR (risk mitigation to investment ratio) indicator for the priority setting of seismic mitigation alternatives. The RMIR is a quantitative indicator that evaluates each alternative’s cost-effectiveness in terms of risk expectancy mitigation. Following the alternative’s RMIR value, it is possible to prioritize the alternatives meeting budget and time constraints. This paper presents the implementation of the proposed methodology through a case study of a generic oil pumping station. The case study includes twelve mitigation alternatives examined and evaluated according to the RMIR indicator.

Seismic mitigation of transportation systems has become a worldwide challenge, because identifying an optimal retrofit strategy entails significant computational efforts, especially for large-scale networks with numerous candidate strategies and time-consuming risk assessment processes. An efficient joint importance-based methodology is proposed in this paper to address the challenge. The proposed method selects the component set (e.g., bridges) that is most decisive to the network seismic risk based on only one set of stochastic samples but takes into account the uncertainty of multiple damage states and the interactive effect between different components. The reliability and stability of the proposed method are verified on a hypothetical transportation network under different conditions.

In the last decade, video surveillance cameras have experienced a great technological advance, making capturing and processing of digital images and videos more reliable in many fields of application. Hence, video-camera-based systems appear as one of the techniques most widely used in the world for monitoring volcanoes, providing a low cost and handy tool in emergency phases, although the processing of large data volumes from continuous acquisition still represents a challenge. To make these systems more effective in cases of emergency, each pixel of the acquired images must be assigned to class labels to categorise them and to locate and segment the observable eruptive activity. This paper is focused on the detection and segmentation of volcanic ash plumes using convolutional neural networks. Two well-established architectures, the segNet and the U-Net, have been used for the processing of in situ images to validate their usability in the field of volcanology. The dataset fed into the two CNN models was acquired from in situ visible video cameras from a ground-based network (Etna_NETVIS) located on Mount Etna (Italy) during the eruptive episode of 24th December 2018, when 560 images were captured from three different stations: CATANIA-CUAD, BRONTE, and Mt. CAGLIATO. In the preprocessing phase, data labelling for computer vision was used, adding one meaningful and informative label to provide eruptive context and the appropriate input for the training of the machine-learning neural network. Methods presented in this work offer a generalised toolset for volcano monitoring to detect, segment, and track ash plume emissions. The automatic detection of plumes helps to significantly reduce the storage of useless data, starting to register and save eruptive events at the time of unrest when a volcano leaves the rest status, and the semantic segmentation allows volcanic plumes to be tracked automatically and allows geometric parameters to be calculated.

The safety and resilience of school buildings against natural disasters is of paramount importance since schools represent a reference point for communities. Such significance is not only related to the direct consequences of collapse on a vulnerable part of the population, but also due to the importance of schools in the post-disaster recovery. This work is focused on the risk and resilience assessment of school buildings in Lisbon (Portugal) under seismic events. The results of this study, in which a subset of 32 schools are analyzed, are used to define a prioritization strategy to mitigate the seismic risk of the Lisbon City Council school building portfolio and to assess the overall resilience of the school network. Numerical modeling of the school buildings is performed in order to estimate losses in terms of the built-up area of the schools and recovery times associated with different seismic scenarios, which are probabilistically defined specifically for the sites of the buildings, accounting for the local soil conditions and associated amplification effects. Based on the obtained risk estimates, which are compared to reference values established on international guidelines and specialized literature, the Lisbon City Council and LNEC jointly defined a short- and medium-term risk mitigation plan, starting with a detailed inspection and assessment of the most vulnerable school buildings and continuing to the implementation of retrofitting measures.

Pompeii Archaeological Park is the best laboratory for the study of the seismic site effects on cultural heritage: the ancient site was destroyed and buried by the 79 AD Vesuvian eruption and, furthermore, it was also affected by the 62–63 AD strong earthquake. Large sectors of the city were reconstructed after this earthquake while other parts were still under reconstruction when the fall-out and pyroclastic density currents of the eruption buried the Roman city. In order to evaluate the distribution of the damage and reconstructions due to the earthquake, detailed mappings of the structures were carried out using multidisciplinary approaches. In addition, analyses of the topographical features, subsoil stratigraphies, and geophysical surveys, responsible for local seismic amplification (site effects), allow us to define the sectors of the ancient city where the Amplification Factors (AFs) were the main ones responsible for damage. Selected areas and examples of compromised and reconstructed buildings show that the ancient topography and subsoil features (both lithological and seismic) are the main AFs. In particular, the damages caused by the 62–63 AD earthquakes seem to be mainly due to topographical factors such as steep scarps and slopes, ridges, peaks, and terraces, as well as to the major thickness of the soft sediments (loose volcanoclastic layers, paleosols, weathered lavas, and anthropogenic infillings) located over the well-lithified lavas. It is not uncommon to also have the combination of these two factors. For the first time, this multidisciplinary approach allows us to draw a seismic microzonation map for one of the most important archaeological sites of the world.

Flood risk in Italy is a key aspect for the administrative authorities, from the national to the local level. This is especially true in Northern Italy, where the Po River, the most important river of the peninsula, and its river basin are located. In North-Western Italy, the Po Basin is described by numerous sub-basins, among which is the Tanaro River basin: here, in the last decades, floods have produced significant damage, causing an increased concern to local and regional administrations. The main goal of this study was to identify suitable sites for the construction of dams, having the function of retention basins, aiming to mitigate the flood risk in the Upper Tanaro Valley. First, using a qualitative approach, suitable sites were identified using available public data provided by regional administrations and field data obtained from geomorphological surveys, later elaborated in a Geographic Information System (GIS) environment. Several models were then produced using conventional methods to evaluate the hydrological characteristics of the study area and to assess the efficiency of each site in terms of flood water flow rate reduction: the performance was evaluated at control sections chosen in urban areas along the Upper Tanaro Valley. The results show that it is possible to find suitable locations for risk mitigation structures. These models also allowed for a rapid cost-effectiveness evaluation, which led to the definition of the best-performing site. The Upper Tanaro Valley case study here analyzed contributes to proving the importance of an integrated approach based on geomorphological, geo-hydrological, and hydraulic evaluations when dealing with the choice of a flood risk mitigation strategy.

In recent years it has become possible to collect GPS data from drivers and to incorporate these data into automobile insurance pricing for the driver. These data are continuously collected and processed nightly into metadata consisting of mileage and time summaries of each discrete trip taken, and a set of behavioral scores describing attributes of the trip (e.g, driver fatigue or driver distraction), so we examine whether it can be used to identify periods of increased risk by successfully classifying trips that occur immediately before a trip in which there was an incident leading to a claim for that driver. Identification of periods of increased risk for a driver is valuable because it creates an opportunity for intervention and, potentially, avoidance of a claim. We examine metadata for each trip a driver takes and train a classifier to predict whether the following trip is one in which a claim occurs for that driver. By achieving an area under the receiver–operator characteristic above 0.6, we show that it is possible to predict claims in advance. Additionally, we compare the predictive power, as measured by the area under the receiver–operator characteristic of XGBoost classifiers trained to predict whether a driver will have a claim using exposure features such as driven miles, and those trained using behavioral features such as a computed speed score.

The safety inspection capability of construction sites before typhoons could be improved using a UAV, which has a rapid identification capability. However, the main safety inspection items need construction experience and technical safety specifications. This study aimed to obtain the influencing factors of typhoon and their weight proportion through the knowledge of disaster theory and the analytic hierarchy process (AHP). The effectiveness of this method was verified by collecting and analyzing the field data at the construction site. A set of construction site early warning flows and disaster prevention and mitigation measures for typhoons are proposed. The results show that UAVs can be used as a tool in this scenario, helping to improve disaster prevention and enhancing the capability of construction site management to evaluate typhoon risk. The research provides a much-needed common ground for collecting and analyzing advances in UAVs and immersive technologies, as well as their influence on building projects. Furthermore, this article provides a new horizon for beginner researchers working on digitalized construction research.

The application of microgrids in critical infrastructures has grown considerably due to the power supply reliability and resilience, and the island operation possibility of providing independence from the main grid. However, the necessity of intense information exchange between the devices that compose the microgrid to their proper operation, and the communication infrastructure required to realize that, makes the system vulnerable to cybersecurity threats. In this context, the case study presented in this paper raises two important subjects of discussion in the Brazilian electrical sector context, which are microgrids and cybersecurity in critical infrastructures of the electrical sector. Therefore, this paper presents the practical challenges related to these two subjects by reporting the development, implementation, and commissioning of a new microgrid controller, and the solutions found to accelerate the development by reducing costs, mitigating risks, and optimizing the commissioning time.

With the rapid development of urbanization around the world, the sea-level-rise problem is gaining more and more attention in the 21st century. Sea-level rise is the result of a combination of climate-related factors, structural factors and human activities. Recent studies related to the contributions of these factors to sea-level rise are reviewed and analyzed in this paper. The results suggest that the melting of glaciers and ice sheets have contributed the most to sea-level rise and will continue to be the dominant factor in sea-level rise for the following decades. As sea-level rise becomes an increasingly serious problem, geological disasters related to sea-level rise are also gaining more attention. To better understand the effect of sea-level rise on geological disasters, relevant issues including storm surges, seawater intrusion, the loss of coastal wetland, seismicity, seismic liquefaction and submarine mass failure are further reviewed and highlighted. In response to the risks of those disasters caused by sea-level rise, some disaster mitigation measures are proposed, and in the end, the quantitative disaster assessment concept based on resilience is introduced to the coastal urban system, to assess its ability to resist and recover from geological disasters due to the sea-level rise.

Italy is one of the European countries most affected by landslides. In order to mitigate the risk, the analysis of such phenomena should involve a broad spectrum of studies to understand the geological and geomorphological properties of the unstable areas, the geometric features of the landslides and the causes of their trigger, the evolution over time, and the works of risk mitigation taken as well as their effectiveness over time. This article is concerned with multidisciplinary investigations on a historical earth flow occurred in Montemurro (Basilicata, Southern Italy) in 1907. We analyse unpublished archive sources strictly coupled with new geological and geomorphological surveys. Furthermore, to gain information on the geometrical features of the landslide body, geophysical prospections (ERT) is used alongside the field surveys. Lastly, to gain insight on the landslide triggering factors, we employed historical–climatological analysis: in particular, we made use of the monthly simple daily intensity index (SDII) to evaluate extreme events and the standardised precipitation index (SPI) to consider previous wetness conditions. The earth flow was triggered on 26 February 1907 and the main movement lasted about one week, involving several buildings, including those of cultural interest. Historical documentary investigations and historical climatological analysis both indicate that the earth flow was triggered by a preceding heavy rain period, which independent historical sources suggest also caused the activation of landslides over a wider area around Montemurro. Currently, the earth flow is NE–SW oriented, extends for a length of ~1.1 km, and has an average width of ~220 m. The landslide is in a dormant activity phase. From a methodological point of view, the research stresses the importance of integrated approaches to investigate natural hazards, particularly by the use of historical data. This research may be of interest to academics, practitioners, and policymakers for both the methodological approach followed and results gained, useful in view of both risk mitigation and territorial planning of landslide-prone areas.

Parcel-level risk (PLR) describes how wildfire risk varies from home to home based on characteristics that relate to likely fire behavior, the susceptibility of homes to fire, and the ability of firefighters to safely access properties. Here, we describe the WiRē Rapid Assessment (RA), a parcel-level rapid wildfire risk assessment tool designed to evaluate PLR with a small set of measures for all homes in a community. We investigate the relationship between 2019 WiRē RA data collected in the Columbine Lake community in Grand County, Colorado, and whether assessed homes were destroyed in the 2020 East Troublesome Fire. We find that the overall parcel-level risk scores, as well as many individual attributes, relate to the chance that a home was destroyed. We also find strong evidence of risk spillovers across neighboring properties. The results demonstrate that even coarsely measured RA data capture meaningful differences in wildfire risk across a community. The findings also demonstrate the importance of accounting for multiple aspects of PLR, including both hazards and susceptibility, when assessing the risk of wildfire to homes and communities. Finally, the results underscore that relatively small actions by residents before a fire can influence wildfire outcomes.

In the last century, floods have been more frequently hitting population and human activity, especially in the sub-Saharan context. The aim of this study is to propose suitable flood mitigation measures for the downstream part of the Rio Muaguide, which flows in northern Mozambique. In this terminal part of the river, the bed has been buried by sediment in many reaches; due to the reduction of the section conveyance, wide areas are inundated during the rainy season with negative consequences for several villages relying on subsistence agriculture. The design of any measure requires quantitative determinations but, as many less developed countries, Mozambique is affected by data scarcity. Therefore, in this study global and freely available data have been used to perform hydrologic and two-dimensional hydro-dynamic modelling, finally producing a flood hazard map. Particular care has been put into a critical analysis of several data sources, in terms of their suitability for the purposes of the work. Based on the modelling results and on field evidence, an intervention has been proposed with a double functionality of mitigating the effects of periodic floods and storing water to be used by the agricultural community during drier seasons. The proposed intervention combines restoring a sedimentation-less shape of the river sections and exploiting a natural basin as a storage basin. The methods applied and the intervention proposed for the Rio Muaguide are prototypal for several analogous streams in the coastal portion of Mozambique.

Conservation Agriculture (CA) is promoted by research and development (R&D) agencies to sustainably intensify agricultural systems with the goals of improving food security and livelihoods and adapting food systems to global climate change. Despite the many benefits of CA, there are few farmers around the world that have simultaneously implemented all facets of the strategy. In part, this reflects the challenges in applying, adapting, and understanding this complex and multi-dimensional agricultural innovation in the context of diverse farming systems. In this paper, we applied an integrated framework that combines bioeconomic simulation, risk analysis, adoption theory, and impact assessment to investigate how various combinations of CA components (no-tillage, soil cover, crop diversification, plus growing a new crop or variety) performed over a 10-year period in representative farms in a central Mexican case study. We found significant differences in profit, net value, downside risk, and risk-aversion cost between double-component scenarios (and improved CA to a lesser extent) and all other scenarios, which suggested that disaggregating CA into smaller component packages could increase farmer adoption in risky contexts. Our findings provided valuable insights on CA feasibility and could help establish policy and reporting metrics. The study highlighted the need for employing a range of research tools to understand the relative value of agricultural innovations and to identify and reduce trade-offs and uncertainty in farming systems.

This paper discusses the relations between the impacts of volcanic eruptions at multiple-scales and the related-issues of disaster-risk reduction (DRR). The review is structured around local and global impacts of volcanic eruptions, which have not been widely discussed in the literature, in terms of DRR issues. We classify the impacts at local scale on four different geographical features: impacts on the drainage system, on the structural morphology, on the water bodies, and the impact on societies and the environment. It has been demonstrated that information on local impacts can be integrated into four phases of the DRR, i.e., monitoring, mapping, emergency, and recovery. In contrast, information on the global impacts (e.g., global disruption on climate and air traffic) only fits the first DRR phase. We have emphasized the fact that global impacts are almost forgotten in the DRR programs. For this review, we have extracted case studies from Indonesia, and compared them to those of other regions, because Indonesia is home to >130 volcanoes and experienced several latest volcanic eruptions with VEI > 5.

Mining companies are responsible for the impacts that result from their mining activities even after the mining period has ended. At the same time, at the European and international levels, there is a lack of a detailed operational methodology comprising environmental risks during and after closure of underground coal mines. The environmental risk aspects that need to be considered when planning the closure of an underground coal mine and post closure in the broader environmental context are the following: modification of water flow scheme, surface instability, mine gas emission on the surface, and water and soil pollution. In this study, we focus on assessing groundwater risk in the context of an underground coal mine closure and evaluating the selected risk mitigation strategies in terms of performance and cost. The results from this study could be used for developing a final closure groundwater assessment plan by selecting the most feasible treatment alternatives for different environmental impacts, together with the transitional monitoring that could guarantee a hazard level in compliance with land reuse and the use of natural resources. Finally, the cost-efficient monitoring and treatment programs are used to estimate the financial provisions needed to mitigate groundwater risks during underground coal mine closure contexts.

Fires are among the most frequently recurring hazards affecting museums and cultural heritage sites. The fires of the National Museum of Brazil in 2018 and of Notre Dame de Paris in 2019 showed that the consequences of such events can be heavy and lead to irreversible heritage losses. In Kosovo, few studies were made about the risks that can affect cultural heritage sites. A project led by the NGO Kosovo Foundation for Cultural Heritage without Borders (CHwB Kosova) in 2018 explored the most prevalent risks for the cultural heritage sites of the country and highlighted fire as a predominant risk in Kosovo. In order to better understand it, vulnerability assessments were conducted in several museums in Kosovo. Data were collected through field visits in the different museums, in which interviews with staff members as well as observations were conducted. The aim of this paper is to present the main results of the fire vulnerability assessments conducted in Kosovo’s museums in 2018. An important aspect of this project is the approach to collect information in data-scarce environments. It is believed that the questionnaires used to lead interviews with museums’ staff members could help other practitioners to collect data in such contexts and evaluate more easily the risk of fire for the museums and their collections. In the context of Kosovo, one of the main findings is the identification and prioritisation of measures to ensure better protection of Kosovar museums. Structural mitigation measures such as alarm and fire suppression systems are not the only elements necessary to improve the resilience of Kosovar museums to fire. Indeed, the promotion of risk awareness, the training of staff members and the realisation of crisis simulation exercises are just as important in order to prevent and detect a fire, and above all, to respond quickly and accurately if a fire occurs.

Understanding African swine fever virus (ASFV) transmission is essential for strategies to minimize virus spread during an outbreak. ASFV can survive for extended time periods in animal products, carcasses, and the environment. While the ASFV genome was found in environments around infected farms, data on the virus survival in soil are scarce. We investigated different soil matrices spiked with ASFV-positive blood from infected wild boar to see if ASFV can remain infectious in the soil beneath infected carcasses. As expected, ASFV genome detection was possible over the entire sampling period. Soil pH, structure, and ambient temperature played a role in the stability of infectious ASFV. Infectious ASFV was demonstrated in specimens originating from sterile sand for at least three weeks, from beach sand for up to two weeks, from yard soil for one week, and from swamp soil for three days. The virus was not recovered from two acidic forest soils. All risk mitigation experiments with citric acid or calcium hydroxide resulted in complete inactivation. In conclusion, the stability of infectious ASFV is very low in acidic forest soils but rather high in sandy soils. However, given the high variability, treatment of carcass collection points with disinfectants should be considered.

Widespread production and use of engineered nanomaterials in industrial and research settings raise concerns about their health impact in the workplace. In the last years, graphene-based nanomaterials have gained particular interest in many application fields. Among them, graphene nanoplatelets (GNPs) showed superior electrical, optical and thermal properties, low-cost and availability. Few and conflicting results have been reported about toxicity and potential effects on workers’ health, during the production and handling of these nanostructures. Due to this lack of knowledge, systematic approaches are needed to assess risks and quantify workers’ exposure to GNPs. This work applies a multi-metric approach to assess workers’ exposure during the production of GNPs, based on the Organization for Economic Cooperation and Development (OECD) methodology by integrating real-time measurements and personal sampling. In particular, we analyzed the particle number concentration, the average diameter and the lung deposited surface area of airborne nanoparticles during the production process conducted by thermal exfoliation in two different ways, compared to the background. These results have been integrated by electron microscopic and spectroscopic analysis on the filters sampled by personal impactors. The study identifies the process phases potentially at risk for workers and reports quantitative information about the parameters that may influence the exposure in order to propose recommendations for a safer design of GNPs production process.

Rockfalls evolve rapidly and unpredictably in mountain environments and can cause considerable losses to human societies, structures, economical activities, and also natural and historical heritage. Rockfall risk analyses are complex and multi-scale processes involving several disciplines and techniques. This complexity is due to the main features of rockfall phenomena, which are extremely variable over space and time. Today, a considerable number of methods exists for protecting land, as well as assessing and managing the risk level. These methodologies are often very different from each other, depending on the data required, the purposes of the analysis, and the reference scale adopted, i.e., the analysis level of detail. Nevertheless, several questions still remain open with reference to each phase of the hazard and risk process. This paper is devoted to a general overview of existing risk estimation methodologies and a critical analysis of some open questions with the aim of highlighting possible further research topics. A typical risk assessment framework is exemplified by analyzing a real case study. Each step of the process is treated at both the detailed and the large scale in order to highlight the main characteristics of each level of detail.

Small Island Developing States (SIDS) of the Pacific over the last decade have established some of the most ambitious renewable energy targets in the world. The promotion of renewable energy has been motivated by a desire to lessen dependence on fossil fuels, given the adverse economic impacts of high oil prices on these countries. Efforts to attract development assistance and to strengthen the position of Pacific SIDS in climate change negotiations have likely also played a role. This paper explores the development of renewable energy resources in the Pacific through a public policy lens. The ambitious renewable energy targets established by Pacific SIDS are argued to be appropriate in some cases, but in other cases are criticised on economic grounds. A potential trade-off is identified between the risk mitigation benefits and poverty alleviation benefits of different renewable technology investments, with questions raised about whether support for the former rather than the latter by development partners is appropriate. A number of institutional and financial challenges to the development of renewable energy resources in Pacific SIDS are also discussed.

Within EU marketing authorization procedures of human and veterinary medicinal products (HMP and VMP), an environmental risk assessment (ERA) has to be performed. In the event that an unacceptable environmental risk is identified, risk mitigation measures (RMM) shall be applied in order to reduce environmental exposure to the pharmaceutical. Within the authorization procedures of HMP, no RMM have been applied so far, except for specific precautions for the disposal of the unused medicinal product or waste materials. For VMP, a limited number of RMM do exist. The aim of this study was to develop consistent and efficient RMM. Therefore, existing RMM were compiled from a summary of product characteristics of authorized pharmaceuticals, and new RMM were developed and evaluated. Based on the results, appropriate RMM were applied within the authorization procedures of medicinal products. For HMP, except for the existing precautions for disposal, no further reasonable measures could be developed. For VMP, two specific precautions for disposal and 17 specific precautions for use in animals were proposed as RMM.

This paper discusses the application of resilience engineering principles by shipborne navigation systems. As a technological system, the ship navigation system comprises all the communication and navigation equipment required to operate a ship. If examined as a socio-technological system, one has to additionally consider the use of the ship navigation system by the bridge teams in order to perform the nautical profession in terms of safe and efficient ship navigation, taking into account environmental information received by communication. The first part of this work discusses the theoretical background of resilience engineering and situation awareness. Case studies are used to illustrate under which conditions the application of resilience principles may result in an improvement of the operational reliability. With the help of simulations, it is shown that a sub-optimal implementation and utilization of resilience principles may decrease the robustness of the technical ship navigation system, as well as the reliability and adaptability of the ship navigation system in use. The examples illustrate once again that monitoring is one of the four cornerstones of resilience: anticipating, monitoring, learning, and responding. This is due to the effectiveness of most resilience principles depending on the availability and trustworthiness of situational information in relation to system status and environmental conditions, irrespective of whether the generation and use of the situational information is machine-made or human-made. Therefore, the establishment of situation awareness is an essential accompanying functionality to be considered in design, operation, and use of resilient systems.

Hazardous materials (HAZMAT) are important for daily production in cities, which usually have a high population. To avoid the threat to public safety and security, the routes for HAZMAT transportation should be planned legitimately by mitigating the maximum risk to population centers. For the objective of min-max local risk in urban areas, this study has newly proposed an optimization model where the service of a link for HAZMAT transportation was taken as the key decision variable. Correspondingly, the symmetric problem of min-max optimization takes significant meanings. Moreover, in consideration of the work load of solving the model under a lot of decision variables, a heuristic algorithm was developed to obtain an optimal solution. Thereafter, a case study was made to test the proposed model and algorithm, and the results were compared with those generated by deterministic solving approaches. In addition, this research is able to be an effective reference for authorities on the management of HAZMAT transportation in urban areas.

The deployment of small unmanned aircraft systems (UAS) to collect routine in situ vertical profiles of the thermodynamic and kinematic state of the atmosphere in conjunction with other weather observations could significantly improve weather forecasting skill and resolution. High-resolution vertical measurements of pressure, temperature, humidity, wind speed and wind direction are critical to the understanding of atmospheric boundary layer processes integral to air−surface (land, ocean and sea ice) exchanges of energy, momentum, and moisture; how these are affected by climate variability; and how they impact weather forecasts and air quality simulations. We explore the potential value of collecting coordinated atmospheric profiles at fixed surface observing sites at designated times using instrumented UAS. We refer to such a network of autonomous weather UAS designed for atmospheric profiling and capable of operating in most weather conditions as a 3D Mesonet. We outline some of the fundamental and high-impact science questions and sampling needs driving the development of the 3D Mesonet and offer an overview of the general concept of operations. Preliminary measurements from profiling UAS are presented and we discuss how measurements from an operational network could be realized to better characterize the atmospheric boundary layer, improve weather forecasts, and help to identify threats of severe weather.

This paper focuses on the influence of detailed engineering maturities on offshore engineering, procurement, and construction (EPC) project procurement and construction cost performance. The authors propose a detailed engineering completion rating index system (DECRIS) to estimate the engineering maturities, from contract award to beginning of construction or steel cutting. The DECRIS is supplemented in this study with an artificial neural network methodology (ANN) to forecast procurement and construction cost performances. The study shows that R2 and mean error values using ANN functions are 20.2% higher and 19.7% lower, respectively, than cost performance estimations using linear regressions. The DECRIS cutoff score at each gate and DECRIS forecasting performance of total cost impact were validated through the results of fifteen historical offshore EPC South Korean mega-projects, which contain over 300 procurement cost performance data points in total. Finally, based on the DECRIS and ANN findings and a trade-off optimization using a Monte-Carlo simulation with a genetic algorithm, the authors propose a cost mitigation plan for potential project risks based on optimizing the engineering resources. This research aids both owners and EPC contractors to mitigate cost overrun risks, which could be continuously monitored at the key engineering gates, and engineering resources could be adjusted per optimization results.

This retrospective analysis aimed to assess and compare the short-term perioperative outcomes and morbidity of hybrid and full-Robotic-Assisted Minimally Invasive Esophagectomy (RAMIE) surgical techniques. A total of 168 robotic-assisted Ivor Lewis esophagectomy procedures performed at Muenster University Hospital were included in the study, with 63 cases in the hybrid group and 105 cases in the full-robotic group. Demographic factors, comorbidities, and tumor stages showed no significant differences between the two groups. However, the full-RAMIE technique demonstrated superiority in terms of overall operative time, postoperative pain levels, and patient morphine consumption. Additionally, the full-RAMIE group exhibited better perioperative outcomes, with significantly shorter ICU stays and fewer occurrences of pneumonias and severe complications. While there was a trend favoring the full-RAMIE technique in terms of severe postoperative complications and anastomotic insufficiencies, further research is required to establish it as the gold standard surgical technique for Ivor Lewis esophagectomy.

Genebanks are crucial for safeguarding global crop diversity but are themselves exposed to several risks. However, a scientific basis for identifying, assessing, and managing risks is still lacking. Addressing these research gaps, this study provides risk analysis for three key risk groups: natural hazards, political risks, and financial risks, carried out on a sample of 80 important national and international genebanks, comprising at least 4.78 million accessions or roughly 65% of the reported total of ex situ conserved accessions worldwide. The assessment tool of Munich Re "Natural Hazards Edition" allowed a location-specific comparison of the natural hazard exposure. Results showed that genebanks in the Asia-Pacific region are most exposed to natural hazards, while institutions in African and some Asian countries are rather vulnerable to political risks. Financing is a major problem for national genebanks in developing countries, whereas the Global Crop Diversity Trust achieved considerable financial security for international genebanks. Large differences in the risk exposure of genebanks exist, making a location- and institution-specific risk assessment indispensable. Moreover, there is significant room for improvement with respect to quality and risk management at genebanks. Transferring risks of genebanks to third parties is underdeveloped and should be used more widely.