Vulnerability assessment and categorization against heat waves for the Bilbao historic area

Sustainable Cities and Society 98 (2023) 104805 Available online 19 July 2023 2210-6707/© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/). Vulnerability assessment and categorization against heat waves for the Bilbao historic area Laura Quesada-Ganuza a , * , Leire Garmendia a , Irantzu Alvarez b , Eduardo Roji a a Department of Mechanical Engineering, Faculty of Engineering in Bilbao, University of the Basque Country UPV/EHU, Plaza Torres Quevedo 1, 48013 Bilbao, Spain b Department of Graphic Design and Engineering Projects, Faculty of Engineering in Bilbao, University of the Basque Country UPV/EHU, Plaza Ingeniero Torres Quevedo s/n, Building II, Bilbao 48013, Spain ARTICLE INFO Keywords: Climate hazards Multi-criteria decision analysis GIS mapping Cultural heritage preservation Urban planning Comprehensive risk assessment ABSTRACT Climate change is threatening urban cultural heritage’s preservation and survival. To improve the resilience of urban systems, planning decision-making processes must consider the risks that climate change poses to heritage. Nevertheless, despite the extensive body of research on climate-related hazards, there remains a significant knowledge deficiency related to the assessment of risks that considers heat waves and historic urban sites. This study’s primary objective is to use Geographic Information Systems (GIS) data to analyse how historic urban locations and heat waves interact, as both urban systems and heritage areas. Socioeconomic, cultural, governmental, and physical aspects of the system are considered for a holistic approach. Key performance indicators, criteria, and requirements pertaining to key vulnerabilities of historic urban areas are identified to undertake a vulnerability assessment methodology, and appraised using the MIVES methodology, a Multi Criteria Decision Making Methodology (MCDM), to achieve this goal. Additionally, a reduced and dataconstrained evaluation is provided through a categorization, for both buildings and public spaces. The categorization process and complete methodology are discussed along with the results of its application to a GIS-based model in Bilbao’s historic district (Basque Country, Spain). This study seeks to be reproducible and be a tool for future global studies. 1. Introduction According to the Intergovernmental Panel on Climate Change (IPCC), the world’s temperature will rise by at least 1.5 ◦C during the next 20 years (IPCC, 2022). Since global warming and climate change are unavoidable, metropolitan regions and their surroundings typically experience the greatest temperatures (IPCC, 2022). This temperature rise poses a serious threat to urban areas, which is exacerbated by other environmental disasters like sea level rise, more frequent and severe heat waves, frequent and excessive precipitation, and resulting floods. The IPCC also notes that the destruction of legacy will result in the loss of traditional customs, a general sense of place, and damage to the physical infrastructure of communities (IPCC, 2014). Therefore, this highlights the need for and the importance of risk assessment methods for the prioritization of adaptation strategies and development towards more resilient cities, with historic areas as a focus. (Quesada-Ganuza et al., 2021). As historic areas represent the sense of place and the identity of cities, being vessels for their tangible and intangible history, they deal with challenges that deserve special attention. Hence, risk and vulnerability assessment and their role on disaster mitigation and adaptation plans should be integrated in urban planning and conservation plans to confront the future challenges that climate change presents, and ensure a sustainable development of cities as well as a resilient built environment. Currently, the existence of vast databases ensures the feasibility of vulnerability and risk analysis and enables planners for evidence-based decision making that will enhance holistic management and conservation strategies. In recent years, significant efforts have been made to estimate the vulnerability of cultural heritage and historic centres to climate change impacts, including the specific threat of heat waves. Organizations such as UNESCO and ICOMOS have played instrumental roles in addressing this critical issue. UNESCO, as a global leader in heritage preservation, has recognized the need to understand and mitigate the vulnerabilities of cultural heritage sites to climate change. Through various research endeavours, reports, and policy documents, UNESCO has shed light on the multifaceted impacts of climate change on World Heritage Sites * Corresponding author. E-mail address: [email protected] (L. Quesada-Ganuza). Contents lists available at ScienceDirect Sustainable Cities and Society journal homepage: www.elsevier.com/locate/scs https://doi.org/10.1016/j.scs.2023.104805 Received 24 March 2023; Received in revised form 7 June 2023; Accepted 14 July 2023 Sustainable Cities and Society 98 (2023) 104805 2 (Markham et al., 2016; UNESCO, 2008). While there is a lack of specific studies focused solely on estimating vulnerability to heat waves, UNESCO’s comprehensive initiatives provide valuable insights into the broader vulnerability of cultural heritage and historic centers to climate-related risks, encompassing aspects such as physical, social, economic, and environmental dimensions, at both local and global scales (UNESCO, 2008). Similarly, ICOMOS, the International Council on Monuments and Sites, has been actively involved in addressing the challenges posed by climate change to cultural heritage. Through its dedicated Climate Change and Heritage Working Group, ICOMOS has spearheaded efforts to comprehend and mitigate the vulnerabilities of cultural heritage sites to climate-related hazards, aligning with the broader objective of assessing and managing the risks faced by cultural heritage and historic centres in the context of climate change (Dastgerdi et al., 2019). Their work emphasizes the importance of integrating climate resilience strategies and adaptive measures into heritage conservation practices, ensuring the preservation and resilience of these irreplaceable cultural assets in the face of increasing climate uncertainties. In comparison to the broader initiatives undertaken by UNESCO and ICOMOS, the study presented in this paper contributes to the knowledge by specifically focusing on the vulnerability assessment of historic urban areas to heat waves. By considering the unique characteristics and complexities of historic buildings and their urban environments to this specific hazard, this study offers valuable insights into the specific challenges and risks faced by these areas, complementing the broader understanding provided by the mentioned initiatives.Heritage must be considered a cultural capital of the communities when analysing the risk of a changing climate and its resulting extreme hazards, as it is essential to build a sustainable link between citizens and their environment and to enhance a feeling of place and belonging (Brabec & Chilton, 2015). Cultural legacy is the connection to the past that allows us to live in the present. It also shapes our identity and our relationship to the environment and the places we live (Harrison, 2010). As a result, cultural heritage is a crucial resource for both sustainable development and the creation and application of effective solutions to mitigate the impacts of climate change. One of the main hazards that impact on historic urban areas are heat waves, furthermore the intensity and probability of extreme heat waves have been increasing worldwide due to climate change (IPCC, 2022; Meehl & Tebaldi, 2004). Heat waves are a concerning hazard for urban population since the risk from them will worsen for cities and infrastructure (IPCC, 2022), with a minimum of half of the world’s population, considering the best case RCP 2.6 scenario, exposed to extreme periods of heat and humidity this century (Zhao et al., 2021). In spite of the high level of concern regarding climate change impacts on heritage; and the abundance of literature addressing the need for research in the area (Brabec & Chilton, 2015; Quesada-Ganuza et al., 2021; Sesana et al., 2021), methodologies for the understanding of the impacts of climate change on cultural heritage and historic areas with a holistic approach (considering all aspects of intangible and tangible heritage within the urban system) are a noticeable gap in knowledge (Quesada-Ganuza et al., 2021). Although they are some examples of methodologies that consider the more traditional threats, as earthquakes and floods (Alessandra Gandini et al., 2021), there has not been a risk assessment approach to the impact of heat waves and the urban heat island phenomenon on cultural heritage (Quesada-Ganuza et al., 2021). In response to this critical gap, our study addresses the need for a comprehensive risk assessment methodology that specifically focuses on the vulnerability of historic areas to heat waves. Building upon our previous work and systematic literature review on risk assessment methodologies in historic areas (Quesada-Ganuza et al., 2021), which addressed the gap regarding heat waves, we integrated findings from studies that examine various aspects influencing vulnerability to heat waves in urban areas (Elbondira et al., 2021; Ma et al., 2023; Min et al., 2019; Ravankhah et al., 2019; Santamouris et al., 2015; Zhang et al., 2022). This comprehensive review informed the selection of indicators and criteria in our methodology, ensuring a holistic approach that considers the multifaceted nature of vulnerability in historic areas. By combining these two lines of enquiry, we contribute to advancing knowledge in the field and provide a practical tool for decision-makers and stakeholders involved in heritage conservation and urban planning. By incorporating the impacts of heat waves and the urban heat island effect into our methodology, we contribute to advancing knowledge in the field and provide practical tools for decision-makers and stakeholders involved in heritage conservation and urban planning. There is no single criteria for what constitutes a heat wave because thresholds differ by geography and climate. According to the World Meteorological Organization (WMO) guidance on heat-health warning (WMO-No.1142) (UNEP & WMO, 2007; World Meteorological Organization, 2018), a heat wave is defined as a stretch of unusually hot and dry or hot and humid weather that lasts at least two to three days and has a noticeable effect on human activities. Such extreme events brought on by unusually hot persistent temperatures have significant effects on ecosystems, the economy, and human mortality (IPCC, 2022; Meehl & Tebaldi, 2004). Heat waves amplify the urban heat island effect (Santamouris, 2019), and combined with the increase on urban population and growth of the built environment, it will potentially affect half of the population in the future (Huang et al., 2019; Zhao et al., 2018). The urban heat island effect indicates how the morphology of an urban region influences heat as shade and ventilation, the technical and physical-chemical properties of urban features, and materials, as well as the typology and design of green spaces, affect its severity (Li & Bou-- Zeid, 2013; Oke et al., 2017). Wind movement, energy absorption, and surfaces’ capacity to reflect long wave radiation back into space are all influenced by the layout and materials of cities (Gartland, 2010; Oke et al., 2017). The purpose of this paper is to assess the vulnerability of historic urban areas to heat waves using the MIVES methodology via a GIS model, with the addition of a categorization propose to facilitate largescale analysis. MIVES is a multicriteria analysis framework that combines Multi Criteria Decision Making Methodology (MCDM) with MultiAttribute Utility Theory (MAUT) incorporating the value function (VF) concept and assigning weights by the means of the Analytic Hierarchy Process (AHP) (Pujadas et al., 2017). For the purpose of a holistic assessment, the historic urban area is considered with a multiscale approach, assessing both the buildings and the urban spaces. Hence, this manuscript presents three sections. The first one approaches the basis and scope of the research, introducing the MIVES methodology used in the study, as well as the modeling and data management strategy using GIS. The second section contains the main research, the proposed categorization and its application for vulnerability assessment in the historic urban area of Bilbao. The final and third section compares the results of the categorization tool in the Bilbao case study with the vulnerability assessment carried out without the use of a categorization approach. 2. MIVES and data management When it comes to decision-making and the prioritization of solutions, several MCDM have been developed over the last decades (Kabir et al., 2014), in search for a systematic framework that is able to reflect the multidimensional nature of the reality. In a multi-criteria method, the problem is disassembled into its component parts in order to analyse each one (Pujadas et al., 2017). For the development of this study, the MIVES methodology was chosen. 2.1. MIVES methodology In order to evaluate sustainability in construction, a multi-criteria methodology called MIVES was created (Aguado et al., 2012; Pons & Aguado, 2012; San-Jos´ e Lombera & Cuadrado Rojo, 2010; San-Jos´ e Lombera & Garrucho Aprea, 2010). The Analytic Hierarchy Process L. Quesada-Ganuza et al. Sustainable Cities and Society 98 (2023) 104805 3 (AHP) is used to assign weights in this system, which was jointly created by the University of the Basque Country (UPV/EHU), the Polytechnic University of Catalonia (UPC) and Tecnalia, combines, MCDM with the VF notion. MIVES is used to homogenise several variable types measured with various units. It considers and relatively compares both quantitative and qualitative variables by transforming them to a comparable unit. Therefore, it provides a framework in which environmental, social, economic, and technical indicators can be taken into consideration and Fig. 1. Evaluation of alternatives in MIVES (taken from Vi˜ nolas Prat et al. 2009). Fig. 2. Different value functions (adapted from San-Jos´ e Lombera and Cuadrado Rojo 2010). L. Quesada-Ganuza et al. Sustainable Cities and Society 98 (2023) 104805 4 compared integrating them into a single index. The choice (to be made) is initially defined. The problem to be solved is identified and defined during this stage. Following the definition of the decision tree and development of the requirements, the criteria (subcriteria) and indicators are selected based on the nature and circumstances of the project. Following that, the alternatives (potential solutions) to the given problem are defined; the quantity of alternatives will depend on the nature of the problem. It is of great importance to point out that, unlike other tools that assess or prioritize alternatives (for example AHP), the assignment of these alternatives can be developed before or after the definition of the model (decision tree), which is a differentiating factor with respect to other evaluation approaches. Finally, with the requirements, criteria and indicators and their weights already defined, the values for each of their alternatives are obtained using value functions, to carry out the their evaluation and make the best decision. The assessment is carried out for the three levels of the decision making tree: indicators, criteria and requirements (Fig. 1). The objective of VF is to compare the evaluation of the indicators using different measurement units. The VF’s ability to convert a variable or attribute’s quantification into a dimensionless variable between 0 and 1 makes it possible to weight the various assessments of each of the indicators. A value function is suggested for each indicator for the evaluation stage. For each indication, this value function, which ranges from 0 to 1 on the ordinate axis, shows the situation of zero valuation or the highest valuation (saturation). On the abscissa axis is the indicator variable, which, in the case of being an attribute, can be converted into a variable (Fig. 2). Five parameters that make up the value function can be adjusted to produce a wide range of shapes: straight, S-shaped, concave, or convex (Fig. 2). 2.2. Multiscale data model and data management A multiscale data model for the management of information is necessary as part of the methodological approach to support the process of decision making and provide proper visualization of the results. A data model with both geometric and semantic data is necessary. This model will gather the information necessary for both the categorization process and the full MIVES vulnerability assessment process, both limited bay data availability and the characteristics of each case study, but aiming for replicability (Fig. 3). The objective of the data models is, therefore, to provide representative information of vulnerability within the historic area to support the prioritization of adaptive and preventative interventions and strategies. GIS, particularly with the use of QGIS, was chosen as the tool for creating the models. GIS is a category of database that combines software tools for gathering, processing, and displaying data with spatial information. As a tool, it provides the opportunity to work with geometric and semantic information at different levels that can be easily integrated with satellite data, as well as provide interoperability with the geographic data bases of different regions. 3. Decision-making process Characterizing the probable effects of heat waves and the urban heat island on the components that make up the historic urban area led to the needs, criteria, and indicators that make up the decision tree. Determining the impact chain using the AR5 framework would therefore be the first step. The AR5 framework’s vulnerability notion is crucial for characterising risk, and its evaluation entails traits and procedures that can be assessed in various ways depending on the discipline (Adger, 2006; Brooks, 2003). As a result, according to the AR5 definition, vulnerability is the tendency or propensity of an element exposed to extreme events (such as climate change events) to be negatively impacted, and this vulnerability along with hazard and exposure will define the risk. According to the IPCC, vulnerability includes sensitivity to the risk and an inability to adapt to climate change’s negative effects (IPCC, 2014). While the concept of sensitivity is pretty simple, the definition of coping capacity varies depending on the system that is Fig. 3. Generation of the GIS models for the implementation and visualization of the methodology. L. Quesada-Ganuza et al. Sustainable Cities and Society 98 (2023) 104805 5 being evaluated. In the AR5, coping capacity is “the ability of people, institutions, organizations, and systems, using available skills, values, beliefs, resources, and opportunities, to address, manage, and overcome adverse conditions in the short to medium term”. It is important to note that coping capacity should not be confused with adaptive capacity, which pertains to the medium and long-term capacity to adapt and adjust to changing conditions, and it is not considered as part of vulnerability assessment. However, adaptive capacity plays a crucial role in overall resilience, as it contributes to a system’s ability to absorb and recover from shocks and stresses. Following this approach, the impact chain results as shown in Fig. 4 and the requirements divided into hazard, exposure and vulnerability. The main receptor for this assessment will be the buildings and the public spaces, in a twofold approach, considering their physical, cultural, socio-economic and environmental characteristics when assessing their vulnerability to heat waves. This means that even if the main receptors are the buildings/ urban spaces themselves, not only their physical degradation from heat wave conditions will be considered but also the thermal comfort will be a main consideration. Necessary for a holistic perspective, thermal comfort is relevant for the impact it has on the users along with the effect on the use and, therefore, on the socio-economic, environmental and cultural aspects of both buildings and urban spaces. In conclusion, the decision-making process provides a data model for historic urban areas that considers vulnerability following the latest approaches to climate change, and structures the information to provide an accessible and replicable framework for decision-making and the prioritization of interventions. The methodology presented in this study focuses on the evolution and definition of vulnerability indicators and contextualizes it to historic areas and urban heritage. The modeling strategy is proposed in two ways: one, through the categorization method, and two, through the full modeling including individual data for every element. The categorization aims to generate a number of sample buildings and open spaces that accurately represent the historic area. This method provides a complete assessment with limited data, reducing analysis time and resources. Hence, the categories are generated using only the information or indicators that better characterise the elements under assessment. Afterwards, the selected indicators are fed with the sample elements and the results extrapolated to all the elements within the category. The vulnerability assessment includes 11 indicators in the case of the buildings and 8 for the public spaces, which are assessed by VFs to obtain dimensionless values from 0 to 1. Weights are then assigned through the AHP by stablishing the relative importance, through pairwise comparison of the different levels of the decision tree. The analysis requirements force us to use a multi-criteria methodology and MIVES’ capacity to measure information of a different nature in the same language make it suitable for our objective. In addition, it also allows using the categorization and is a friendly tool due to its treeshaped display and the clarity with which the information and evaluation are displayed. When using the classification approach, data will be gathered to determine the sample level’s susceptibility. The next stage is to compute vulnerability for each sample building and public area, representing each category, and extrapolate that value to the elements falling under that category. Resulting on the vulnerability of the historic area. The vulnerability will be specific for each element resulting on maps picturing the vulnerability index level. As a second step, the full vulnerability assessment will be implemented, without a categorization process, using the full indicators list and the data collected for every single element, both buildings and open spaces, and the results compared for both methods. Following the MIVES approach set before in this study, the definition of the problem and decision to be taken is the first step. The scope for this methodology is to identify, objectively, buildings and public spaces as elements of the historic urban area, that are more vulnerable to heat waves and the urban heat island effect. This concludes with a decisionmaking tree formed by the sensitiveness and coping capacity of the elements as the two main requirements, followed by the criteria that considers the different systems for the holistic approach, and the individual indicators, following the impact chain on Fig. 4. 3.1. Vulnerability of buildings The sensitiveness requirement assesses the degree to which a building is affected by a heat wave event. As depending on the characteristics of the building its response to the impact will vary. Several aspects are considered to measure its sensitivity with a holistic perspective. Therefore, the following criteria are defined considering the characteristics of the buildings: environmental, social, physical, economic and cultural value. The environmental sensitivity of the building refers to the characteristics of the immediate surrounding of the building that affect its thermal behaviour, and, therefore, the thermal comfort inside. In this case, the solar radiation of the envelope and the acoustic pollution that surrounds the building where chosen as the indicators. The solar radiation heats the envelope of the building, affecting the thermal comfort inside. The acoustic pollution surrounding the building is proven to reduce the willingness of the inhabitants to open the windows, and therefore, the ability to ventilate the interior of the building during the hours of less heat (Nú˜ nez Peir´ o et al., 2020). The social sensitivity criteria indicates the characteristics of the inhabitants that makes them more sensitive to heat waves. For this, three Fig. 4. Relationship between the suggested impact chain for historic urban areas and the IPCC AR5 methodology for risk assessment (Quesada-Ganuza et al., 2022). L. Quesada-Ganuza et al. Sustainable Cities and Society 98 (2023) 104805 6 indicators have been defined, the density of the population residing within the building, the amount of vulnerable population than can suffer adverse consequences from reduced thermal comfort (depending on the age group they belong to and the associated vulnerability level), and the existence and amount of insulation in the envelope of the building. For the physical sensitivity criteria that considers the degradation of the building from heat wave conditions, two indicators are defined: date of construction and state of conservation. The date of construction Table 1 Summary of the values for each alternative of indicators regarding the vulnerability of public space. Fig. 5. VF for relevance of the public space. L. Quesada-Ganuza et al. Sustainable Cities and Society 98 (2023) 104805 7 provides the historical typology and, consequently, is linked to materials degradation due to temperature and humidity extremes. The economic and cultural value criteria are composed of one indicator each. Economic sensitivity will be measured by the primary use of the building, considering the effect that reduced thermal comfort inside can have on it, affecting its normal use. For cultural value, the link of the building to historical events or traditions will be considered. As for the coping capacity requirement, it refers to the ability of the system, in this case the building, to face the possible impact of the extreme event in a very short period. In this case, it is composed of two criterion, each of them considering one indicator. The first one is accessibility of the buildings, with the indicator being the presence of an elevator. This considers the possibility of evacuating potential victims of heat strokes or similar health problems caused by heat wave conditions. In the case of the second criteria, cultural value, it considers protection level as an indicator. Protection level of buildings in historic areas limit the interventions and the possible solutions that can be implemented to mitigate the impact of heat waves on buildings and their inhabitants. Fig. 6. Final decision tree for buildings with weights. Fig. 7. Final decision tree for public spaces with weights. L. Quesada-Ganuza et al. Sustainable Cities and Society 98 (2023) 104805 8 3.2. Vulnerability of public space The sensitiveness of public spaces, such as streets or squares, to heat waves conditions vary depending on their physical, environmental and socio-cultural characteristics. This characteristics affect the thermal comfort within this spaces and the people using them. Hence, the sensitiveness of public spaces is composed of three criteria, physical, environmental and socio-cultural. Albedo, the Normalized Difference Vegetation Index (NDVI), and the Sky View Factor (SVF) are among the indicators that describe the space’s physical features. Albedo, which ranges from 0 to 1 for lowest and maximum reflection, is the percentage of incoming radiation that a surface reflects (Andr´ es-Anaya et al., 2021; Erell et al., 2012). The presence and density of vegetation in a region, which contributes to heat mitigation, are determined using remote sensing measures, frequently from satellite photography, using the straightforward graphical indicator known as NDVI. Finally, SVF is the main parameter in determining the phenomenon known as urban canyon (Gartland, 2010). It addresses the relationship between the proportions of an urban space with the tendency of that space to store heat (Dirksen et al., 2019). Environmental criteria has as indicators solar radiation and air pollution. Intense solar radiation is a common indicator when assessing heat waves, as more hours of direct solar radiation is directly linked to lower thermal comfort. According to research, ozone levels rise in environments with high temperatures, strong solar radiation, and lengthy daylight hours. According to Pyrgou et al. (2018), each of these distinct meteorological traits is connected to heatwaves, with high ozone levels being hazardous to human health (Pyrgou et al., 2018; Stedman, 2004). For socio cultural criteria, two indicators are considered: relevance of the space and its link to historical events or traditions. Both of these indicators measure the amount of people using the space and its relevance to life within the historic area, being, therefore worst affected by heat waves conditions and a reduction in thermal comfort. The number and density of ground floor commercial activity within a public space measure the relevance of the space. For the coping capacity requirement in the case of the public spaces, the accessibility criterion measures their ability to respond to the event in a short period. In the case of historic areas, streets tend to be very narrow, so accessibility in case of an emergency is an important consideration. Hence, the indicator for these criteria is if the space is accessible for firefighters, in case of a fire (more frequent during hotter periods) or the need to evacuate a person victim of a heat stroke or similar health problems caused by heat wave conditions (Anderson & Bell, 2011; Rasilla & Fern´ andez de Arr´ oyabe, 2003). To sum up, the decision tree for public space vulnerability (Table 1) is divided into 4 criteria and 8 indicators. For a comprehensive discussion on the definition of the weight of each indicator, the establishment Fig. 8. Indicators categorization process for the buildings. Fig. 9. Indicators categorization process for the public spaces. L. Quesada-Ganuza et al. Sustainable Cities and Society 98 (2023) 104805 9 of subcategories, and the determination of sub-ranges, please refer to Quesada-Ganuza (2022). To ensure the replicability and applicability of the chosen indicators beyond the scope of this study, a rigorous selection process was employed, guided by the principles of replicability, traceability, and robustness (RACE). By adhering to these principles, the selected indicators are designed to be adaptable and usable in various case studies, enabling comparisons and facilitating the replication of vulnerability assessments in different contexts. The decision tree for public space vulnerability, outlined in Table 1, encompasses four criteria and eight indicators carefully chosen to capture the diverse dimensions of vulnerability. Each indicator’s weight, the establishment of subcategories, and the determination of sub-ranges were thoroughly defined, ensuring transparency and consistency in the assessment process. The comprehensive documentation of the indicator selection and categorization process in Quesada-Ganuza (2022) further enhances the reproducibility and robustness of the methodology (Quesada-Ganuza, 2022). A panel of 20 experts was engaged to evaluate the options, and the value functions, indicators, and criteria were weighted based on the mean of their responses. The panel of 20 experts engaged in this study consisted of a diverse and multidisciplinary group, comprising experts from various fields relevant to the analysis. among them were 10 engineers specializing in construction, mechanical systems, materials, and related disciplines and experience in risk assessment. The remaining panel members included 6 architects specializing in heritage management, urban planning, and architectural design, 1 geographer, and 3 experts in urban studies and urban management, with a specialization in climate and urban resilience. The selection of experts was carefully done to ensure a comprehensive and well-rounded representation of knowledge and perspectives. Their diverse backgrounds and expertise contributed to a thorough analysis of the indicators and criteria. To evaluate the indicator alternatives and criteria, the panel members participated in a comprehensive questionnaire. This questionnaire was specifically designed to assess the relative importance of each indicator, allowing the experts to assign weights based on their professional judgement. Through their collective input, the panel provided valuable insights and expertise that enhanced the accuracy and robustness of the vulnerability assessment methodology. The following phase in the MIVES technique was the definition of the weight for each indicator, criterion, and requirement in order to determine their relative relevance using AHP and to generate the vulnerability index. This was done after the value functions were specified. This process resulted in the following decision making trees for both buildings and open spaces (Figs. 6 and 7). 4. The process of categorising the building and public space stock When it comes to its reproducibility and a quick and data-light evaluation, categorization is a very important phase in a risk assessment process. It gives confidence when achieving general information about asset vulnerability on a macro-scale. This method helps to achieve an assessment of risk or vulnerability when fewer data is available, by creating representative categories of the elements with fewer indicators and, then, building the rest using sample elements of each category. A statistical approach may be used to analyse a large and diverse stock of buildings and public places, such as an urban area, with the goal of describing all the assets using archetypes or sample assets. Sample Fig. 10. Historic district of the city of Bilbao, the chosen area for the study. L. Quesada-Ganuza et al. Sustainable Cities and Society 98 (2023) 104805 16 a lower value than 0.3. In the case of public spaces, 2.8% presented a vulnerability higher than 0.5, 27.1% being over 0.4. Finally, 19.63% of the public spaces presented a vulnerability lower than 0.2. Overall, this study demonstrates the application of a robust vulnerability assessment methodology in the historic area of Bilbao, providing insights into the vulnerability levels of buildings and public spaces. The methodology’s ability to integrate diverse data sources and facilitate objective measurements ensures its replicability and applicability in other contexts. In addition to the vulnerability assessment results, further analysis was conducted to identify clusters within the data, highlighting the criteria and indicators that had a significant impact on the overall vulnerability. Through clustering techniques, it was revealed that certain criteria and indicators played a more prominent role in determining vulnerability levels in the historic area of Bilbao. For instance, indicators related to the urban heat island effect, such as the sky view factor and solar radiation, emerged as influential factors in understanding the vulnerability of the urban spaces to heat waves. In the case of the buildings, the presence of materials prone to degradation linked to the construction year of the buildings, along with the solar radiation they receive compose two of the more relevant components of vulnerability in the case study. Building upon this clustering analysis, a comparative assessment was performed to contextualize the findings of this study within the broader literature on vulnerability assessment methodologies. In the absence of direct comparisons with studies on heat waves in historic areas, a comparative assessment was conducted with other hazard-related methodologies and studies, as documented in the review paper (Quesada-Ganuza et al., 2021). This broader comparison allowed for insights into the similarities and differences in approaches to vulnerability assessment across various hazards. By examining other hazard contexts, such as floods or earthquakes, valuable knowledge was gained in terms of methodological considerations, applicability of indicators, and lessons learned from different risk assessment frameworks. In synthesizing the findings of the clustering analysis and the comparative assessment, this study contributes to filling the existing gap in literature by providing a more comprehensive understanding of vulnerability in historic areas, particularly in relation to heat waves. While direct comparisons with heat wave studies in historic areas remain limited, the insights gained from analysing clustering patterns and considering other hazard contexts contribute to advancing the knowledge and methodology for vulnerability assessment in this unique setting. In the field of urban vulnerability assessment, various methodologies have been developed to address the challenges posed by different hazards. For instance, the study by Apreda et al. (2019) focused on assessing the vulnerability of urban areas to both heat waves and floods, considering a broad range of physical indicators. While their methodology offers valuable insights into the overall vulnerability of urban areas, it primarily adopts a more generalized approach, assessing larger sections of the urban fabric rather than differentiating between individual buildings and open spaces. This broader perspective aligns with other methodologies that emphasize the physical aspects of vulnerability, examining the susceptibility of urban areas to a range of hazards. Studies such as Lemonsu et al. (2015) and He et al. (2021), Lemonsu et al. (2015) have also explored physical vulnerability and the indicators that impact the urban heat island effect, albeit at different scales and with varying approaches. These studies have provided important ideas and data on physical indicators, contributing to our understanding of vulnerability in urban contexts. Moreover, studies such as Sanchez et al. (2020) and Nu˜ nez Peiro et al. (2020) have emphasized the social aspects of vulnerability, considering factors like fuel poverty (Nú˜ nez Peir´ o et al., 2020; S´ anchez et al., 2020). These studies contribute to a more holistic understanding of vulnerability, complementing our focus on the specific context of historic areas. However, it is important to note that our study specifically focuses on historic areas and the unique vulnerabilities they face in the context of heat waves. The distinct characteristics of historic areas, including the architectural heritage and historical significance, needs a tailored assessment that considers the interplay between buildings, open spaces, and the historical context. While broader methodologies provide valuable insights into urban vulnerability, our targeted approach enables us to capture the nuanced vulnerabilities of historic areas during heat waves. Table 7 Weights of the public spaces requirement tree. L. Quesada-Ganuza et al. Sustainable Cities and Society 98 (2023) 104805 17 7 By comparing these different approaches and the results, we gain a comprehensive understanding of the diverse perspectives and scopes of vulnerability assessments in urban contexts. While some methodologies take a broader and more physical approach to assess vulnerability at a larger scale, our study highlights the significance of conducting targeted assessments that consider the intricate interplay between buildings, open spaces, and the historical context within historic areas. Conclusions and future work Heat waves present a challenge in the field of risk assessment, especially when considering historic urban areas, as there is a gap in knowledge. As climate change and the derived hazards become more relevant, planning and conservation strategies will need to guide the adaptation of historic areas to face a more challenging future. Hence, the proper understanding of vulnerability and risk is a mayor necessity to prioritize and use adaptation resources. The vulnerability assessment methodology presented in this study uses a comprehensive set of multidimensional indicators to understand the vulnerability of buildings and open spaces to heat waves within historic urban areas. The methodology applies a holistic approach, gathering indicators from a physical, socio-economic, cultural and environmental perspective. These indicators are developed through a multiscale approach, taking into account the flexibility and replicability of the methodology. The authors’ knowledge of the area and visual inspection during the 2022 summer’s heat waves of different areas of the case study confirmed the results and provided validation for the methodology. As future work, the results of individual indicators could be validated with a combination of simulations and in situ measurements of the heatwave conditions and is effects. In the case of the categorization for the public spaces, even if the vulnerability accuracy was high, the categorization left out the most and less vulnerable elements, being the ones categorized all of similar level Fig. 15. Vulnerability of buildings in Bilbao adjusting the values to minimum and maximum. L. Quesada-Ganuza et al. Sustainable Cities and Society 98 (2023) 104805 18 of vulnerability. This concluded that the homogeneity among the urban spaces in a historic area makes small differences among the indicators very relevant when calculating vulnerability, so the categorization method did not bring the most accurate results. In the case of the buildings, the results presented a very low margin of error, 2%, providing a good alternative to a full assessment with less data requirements, and consequently, resources in terms of time and cost. The categorization process would gain more importance in cases where the variety of spaces is more heterogenic, and the categories more varied as a result, which makes it more relevant in case of assessment at an urban or even regional scale. An adequate data management strategy is necessary in order to obtain a robust and replicable methodology that ensures the connection between scales and the replication capacity. Data access for urban areas is complex and varies between case studies, especially in complex historic areas where availability of information is scarce and difficult to gather via fieldwork or other methods. The methodology should be, therefore, flexible to permit adjustments regarding data availability and updates over time, when data becomes available or adaptive actions take place. The latter would lead to a dynamic risk analysis. In conclusion, the methodology presented provides a robust and objective approach for assessing the risk of historic areas to heat waves, The vulnerability study presented in this paper is the first step in the development of a final risk assessment methodology that will result with the future combination of hazard and exposure to complete the IPCC risk framework. For the future steps, it is essential to consider the evolving framework presented in the IPCC’s Sixth Assessment Report (AR6) (IPCC, 2022). While our current study is based on the AR5 framework, we acknowledge the importance of incorporating the AR6 framework in future steps towards risk assessment and account for future adaptation measures. The AR6 framework places a greater emphasis on the interactions and responses among the determinants of risk. It considers the Fig. 16. Vulnerability of open spaces in Bilbao adjusting the values to minimum and maximum. L. Quesada-Ganuza et al. Sustainable Cities and Society 98 (2023) 104805 19 uni-directional, bi-directional, and aggregate interactions among the various components that contribute to risk (IPCC, 2022). This refreshed approach provides a more explicit understanding of the specific interactions within and between the determinants of risk, enabling a more detailed and accurate assessment of risk. In the context of climate change impacts, risks arise from the dynamic interactions between climate-related hazards, exposure, and vulnerability of the affected system. However, when considering climate change responses, risks can arise from potential trade-offs, negative side-effects, or the potential for responses not achieving their intended objectives (IPCC, 2022). By acknowledging the advancements in the AR6 framework, our future research aims to integrate these considerations into future work and the development of the methodology towards risk assessment. 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