Carmine Galasso’s research while affiliated with University College London and other places

In the aftermath of an earthquake, the number of residents whose housing was destroyed is often used to approximate the number of people displaced (i.e., rendered homeless) after the event. While this metric can provide rapid situational awareness regarding potential long-term housing needs, more recent research highlights the importance of additional factors beyond housing damage within the scope of household displacement and return (e.g., utility disruption, tenure, place attachment). This study benchmarks population displacement estimates using this simplified conventional approach (i.e., only considering housing destruction) through three scenario models for recent earthquakes in Haiti, Japan, and Nepal. These model predictions are compared with officially reported values and alternate mobile location data-based estimates from the literature. The results highlight the promise of scenario models to realistically estimate population displacement and potential long-term housing needs after earthquakes, but also highlight a large range of uncertainty in the predicted values. Furthermore, purely basing displacement estimates on housing damage offers no view on how the displaced population counts vary with time as compared to more comprehensive models that include other factors influencing population return or alternative approaches, such as using mobile location data.

Environmental impact assessments in the construction sector often overlook the significant effects of natural hazards, in particular earthquakes. These destructive events pose severe sustainability challenges as they frequently require large-scale repairs and replacement for damaged buildings, demanding the production and use of substantial quantities of building materials. Here, we unveil the environmental toll of earthquakes in Europe, presenting essential environmental data on the continent’s building stock. We further generate novel seismic risk maps that quantify the embodied carbon resulting from seismic-damage repair and reconstruction of residential, commercial, and industrial buildings, considering all plausible earthquake scenarios across the region. To this end, we first develop a comprehensive database of material quantities and embodied carbon factors for a broad range of construction materials and building components. This database serves as a crucial input for a continent-wide probabilistic seismic risk model, which estimates the potential environmental impacts of future earthquakes by analysing over 3 million realistic damage scenarios, each with its own probability of occurrence. Our findings reveal that Europe’s earthquake-exposed building stock embodies nearly 13.4 billion tons of carbon dioxide equivalent (CO 2 e), with seismic damage alone generating more than 6.4 million tons of CO 2 e annually; comparable to the emissions of 32,000 one-way flights from Paris to New York carrying 200 passengers. Our models not only establish critical benchmarks for the carbon footprint of the European construction sector, but also offer a versatile tool for assessing the impacts of other natural hazards, driving sustainable disaster risk mitigation and fostering more resilient, eco-friendly built environments.

The frequent occurrences of bridge fires and the substantial disruptions and direct/indirect economic losses resulting from these events highlight the immediate need for effective fire-safety-oriented design of new bridges and retrofit approaches for vulnerable existing bridges. In this Perspective, we discuss why a holistic engineering approach integrating innovative fire analysis methods and structural design/retrofit strategies into multi-hazard and future-oriented risk modeling frameworks represents the way forward to more sustainable and resilient infrastructure in an uncertain and rapidly changing built environment.

Effective disaster-risk management requires holistic risk-modelling approaches, which: (1) capture the effects of multiple (natural) hazards on the system/community of interest; and (2) account for social vulnerability factors that influence how different sectors within the community experience, respond to and cope with these effects. We propose a straightforward multi-risk index that integrates both of these crucial considerations. The index represents a combination of indicators for individual risks of interest. It appropriately accounts for uncertainties in the underlying dimensions of risk, relying on probabilistic distributions of hazard, physical and social vulnerability, and population exposure information. Furthermore, these dimensions are weighted in the index calculation to explicitly reflect variable stakeholder priorities on associated matters (e.g., policymaking). We demonstrate the index for earthquake and flood risk across the entire country of Italy (at the resolution of municipalities), using easily accessible open data. The proposed index identifies hotspots across the country that should be prioritised for disaster risk reduction actions. Sensitivity analyses of the applied weights reveal how these hotspots can change as a function of stakeholder preferences and/or variations in the emphasis placed on different types of hazards, ultimately underlining the importance of accounting for accurate stakeholder feedback and adopting a multi-layered view of risk in disaster-related decision making. A prominent advantage of the proposed index is that it is relatively simple and could be easily adopted for practical multi-risk decision support across any other national or transnational context of interest.

Due to the recent damage and collapse of several bridges in Italy, reliable quantification of their vulnerability is paramount for planning various risk mitigation and resilience-enhancing strategies. This paper specifically fo-cuses on the seismic vulnerability and loss assessment of existing reinforced concrete (RC) deck-stiffened arch bridges. The study considers a bridge typology known as the "Maillart-type" arch bridge, a common structural typology in the 1950s and characterised by a particularly stiff deck and a slender vault, i.e., a high deck-to-arch flexural stiffness ratio. Such bridges were typically designed considering only gravity loads and usually without ductile structural detailing and consideration of capacity-design principles. Historical documents and original design blueprints are used to simulate the design of an archetype bridge representative of the Italian "Maillart-type" arch bridge population. Then, nonlinear cloud-based time-history analysis is performed to investigate the seismic response of the considered archetype under varying ground-motion intensities and derive fragility and vulnerability relationships. Specifically, three different models are considered: one that adopts a conservative approach where damage is determined by the shear failure of the shortest pillar, another that provides a more detailed representation of structural damage progression, and a third that assumes retrofitting of the shortest pillar. The vulnerability relationships are combined with site-specific seismic hazard curves for case-study locations to estimate expected annual losses. The results represent a first step in assessing the seismic vulnerability of "Maillart-type" arch bridges to plan seismic risk mitigation interventions for such a bridge typology.

When dealing with probabilistic seismic-risk assessments explicitly accounting for seismicity clustering and resulting damage accumulation, damage analysis must adopt state-dependent fragility relationships. Building-level, state-dependent fragilities represent the probability of reaching or exceeding a damage state (DS) threshold conditional to an initial DS due to previous seismic events (e.g., a mainshock) and the intensity of a second ground motion. Advanced methodologies for state-dependent fragility estimation have been proposed, typically relying on sequential non-linear dynamic analyses of Multi-Degree-of-Freedom (MDoF) numerical models. However, for many practical applications, lower-refinement methods may be preferred by various end-users/stakeholders, despite accepting higher uncertainties and/or some bias in the results. Research efforts are still needed to develop simplified approaches for damage-dependent fragility analysis and evaluate their accuracy compared to more refined methods. This paper contributes to this aim by investigating the trade-off between the refinement level of analysis and the result accuracy, considering alternative methodologies for state-dependent fragility estimation. This is done by analysing an archetype reinforced concrete frame structure with different seismic response analysis methods: i) non-linear static analysis, coupled with a spectrum-based approach (low-refinement level); ii) sequential non-linear dynamic analysis of equivalent inelastic Single-Degree-of-Freedom (SDoF) systems (medium-refinement level); iii) sequential non-linear dynamic analysis of advanced MDoF numerical models (high-refinement level). In line with the state-of-the-art procedures in the literature, fragility estimation is performed, whenever possible, considering energy-based approaches to effectively capture damage accumulation during ground-motion sequences. The results highlight that simplified methodologies enable a relatively accurate fragility estimation compared to the more refined approaches. Based on the characterised relative error, results from this study may facilitate calibrating suitable correction factors for adopting simplified methods in practice.

In the context of natural hazard risk quantification and modeling of hazard interactions, some literature separates “Level I” (or occurrence) interactions from “Level II” (or consequence) interactions. The Level I interactions occur inherently due to the nature of the hazards, independently of the presence of physical assets. In such cases, one hazard event triggers or modifies the occurrence of another (e.g., flooding due to heavy rain, liquefaction and landslides triggered by an earthquake), thus creating a dependency between the features characterizing such hazard events. They differ from Level II interactions, which instead occur through impacts/consequences on physical assets/components and systems (e.g., accumulation of physical damage or social impacts due to earthquake sequences, landslides due to the earthquake-induced collapse of a retaining structure). Multi-hazard life cycle consequence (LCCon) analysis aims to quantify the consequences (e.g., repair costs, downtime, casualty rates) throughout a system’s service life and should account for both Level I and II interactions. The available literature generally considers Level I interactions – the focus of this study – mainly defining relevant taxonomies, often qualitatively, without providing a computational framework to simulate a sequence of hazard events incorporating the identified interrelations among them. This paper addresses this gap, proposing modeling approaches associated with different types of Level I interactions. It describes a simulation-based method for generating multi-hazard event sets (i.e., a sequence of hazard events and associated features throughout the system’s life cycle) based on the theory of competing Poisson processes. The proposed approach incorporates the different types of interactions in a sequential Monte Carlo sampling method. The method outputs multi-hazard event sets that can be integrated into LCCon frameworks to quantify interacting hazard consequences. An application incorporating several hazard interactions is presented to illustrate the potential of the proposed method.

Risk-based design and assessment methods are gaining popularity in performance-based structural fire engineering. These methods usually start by defining a set of hazard scenarios to use as analysis inputs. This approach, proven highly effective for other hazard types such as earthquakes, may not be optimal for fire safety design. Indeed, the strong coupling between the fire phenomenon and structural features enables an ad-hoc design variable selection (and/or optimisation) to reduce fire intensity, making fire scenarios additional design outputs. In addition, such a coupling effect implies that fire scenarios maximising consequences are structure specific. Building on these considerations, this paper discusses the limitations that arise at different analysis steps (i.e., fire-scenario and intensity treatment, identifying fire intensity measures, probabilistic fire hazard analysis, developing fire fragility models, and risk calculation) when using conventional risk-based approaches for design purposes. Furthermore, it compares such approaches with a fire safety design methodology (the Consequence-oriented Fire intensity Optimisation, CFO, approach) that addresses the identified limitations. The potential benefits of integrating the two approaches are also discussed. Finally, the fire design of a simplified steel-girder bridge is introduced as an illustrative example, comparing the consequence metrics and design updating strategies resulting from the two approaches.