A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Santiago de Chile

Systemic inequalities in heat risk for greater London

The temperature rise and increases in extreme heat events related to global climate change is a growing public health threat. Populations in temperate climates, including the UK, must urgently adapt to increased hot weather as current infrastructure primarily focusses on resilience to cold. As we adapt, care should be taken to ensure existing health inequalities are reduced. Lessons can be learned from regions that experience warmer climates and applied to adaptation in the UK. We identified known indicators of heat-health risk and explored their distribution across area level income for London. Understanding these indicators and their distributions across populations can support the development of interventions that have the dual aim of improving health and reducing inequalities. An exploratory analysis was conducted for each indicator at neighbourhood level to assess existence of disparities in their distributions across London. A systems-thinking approach was employed to deduce if these amount to systemic inequalities in heat risk, whereby those most exposed to heat are more susceptible and less able to adapt. Using this information, we proposed interventions and made recommendations for their implementation. We find inequalities across indicators relating to exposure, vulnerability, and adaptive capacity. Including inequalities in urban greening and access to greenspace, physical and mental health and access to communication and support. Through a system diagram we demonstrate how these indicators interact and suggest that systemic inequalities in risk exist and will become more evident as exposure increases with rising temperatures, depending on how we adapt. We use this information to identify barriers to the effective implementation of adaptation strategies and make recommendations on the implementation of interventions. This includes effective and wide-reaching communication considering the various channels and accessibility requirements of the population and consideration of all dwelling tenures when implementing policies relating to home improvements in the context of heat.

Elucidating Uncertainty in Heat Vulnerability Mapping: Perspectives on Impact Variables and Modeling Approaches

Heat vulnerability maps are vital for identifying at-risk areas and guiding interventions, yet their relationship with health outcomes is underexplored. This study investigates the uncertainty in heat vulnerability maps generated using health outcomes and various statistical models. We constructed vulnerability maps for 167 municipalities in Korea, focusing on the mild and severe health impacts of heat waves on morbidity and mortality. The outcomes included incidence rates of heat-related outpatient visits (morbidity) and attributable mortality rates (mortality) among individuals aged 65 years and older. To construct these maps, we utilized 11 socioeconomic variables related to population, climate, and economic factors. Both linear and nonlinear statistical models were employed to assign these socioeconomic variables to heat vulnerability. We observed variations in the crucial socioeconomic variables affecting morbidity and mortality in the vulnerability maps. Notably, nonlinear models depicted the spatial patterns of health outcomes more accurately than linear models, considering the relationship between health outcomes and socioeconomic variables. Our findings emphasize the differences in the spatial distribution of heat vulnerability based on health outcomes and the choice of statistical models. These insights underscore the importance of selecting appropriate models to enhance the reliability of heat vulnerability maps and their relevance for policy-making.

A low-carbon electricity sector in Europe risks sustaining regional inequalities in benefits and vulnerabilities

Improving equity is an emerging priority in climate and energy strategies, but little is known how these strategies would alter inequalities. Regional inequalities such as price, employment and land use are especially relevant in the electricity sector, which must decarbonize first to allow other sectors to decarbonize. Here, we show that a European low-carbon electricity sector in 2035 can reduce but also sustain associated regional inequalities. Using spatially-explicit modeling for 296 sub-national regions, we demonstrate that emission cuts consistent with net-zero greenhouse gas emissions in 2050 result in continent-wide benefits by 2035 regarding electricity sector investments, employment gains, and decreased greenhouse gas and particulate matter emissions. However, the benefits risk being concentrated in affluent regions of Northern Europe, while regions of Southern and Southeastern Europe risk high vulnerabilities due to high adverse impacts and sensitivities, and low adaptive capacities. Future analysis should investigate policy mechanisms for reducing and compensating inequalities.

Statistically Validated Urban Heat Island Risk Indicators for UHI Susceptibility Assessment

This research proposes a collection of urban heat island (UHI) risk indicators under four UHI risk components: hazard, exposure, sensitivity, and adaptive capacity. There are 46 UHI risk indicators linked to three pillars of sustainability: social equity, economic viability, and environmental protection. In this study, the UHI risk indicators were first validated by experts to determine their relevancy and subsequently applied to randomly sampled dwellers of Thailand's capital Bangkok. The UHI indicators were further validated with confirmatory factor analysis to determine the factor loadings (0-1) and reliability. Under the hazard component, the percentage of days when the daily minimum temperature is less than the 10th percentile exhibited the highest indicator-level factor loading (0.915). Vehicular traffic was the UHI exposure indicator with the highest factor loading (0.923), and the proportion of green space to build environment was the UHI sensitivity indicator with the highest factor loading (0.910). For the UHI adaptive capacity component, the highest factor loading (0.910) belonged to government policy and action. To effectively mitigate UHI impacts, greater emphasis should be placed on the indicators with highest factor loadings. Essentially, this research is the first to use statistical structural equation modeling to validate UHI indicators.

Characteristics of Households' Vulnerability to Extreme Heat: An Analytical Cross-Sectional Study from India

High ambient temperature is a key public health problem, as it is linked to high heat-related morbidity and mortality. We intended to recognize the characteristics connected to heat vulnerability and the coping practices among Indian urbanites of Angul and Kolkata. In 2020, a cross-sectional design was applied to 500 households (HHs) each in Angul and Kolkata. Information was gathered on various characteristics including sociodemographics, household, exposure, sensitivity, and coping practices regarding heat and summer heat illness history, and these characteristics led to the computation of a heat vulnerability index (HVI). Bivariate and multivariable logistic regression analyses were used with HVI as the outcome variable to identify the determinants of high vulnerability to heat. The results show that some common and some different factors are responsible for determining the heat vulnerability of a household across different cities. For Angul, the factors that influence vulnerability are a greater number of rooms in houses, the use of cooling methods such as air conditioning, having comorbid conditions, the gender of the household head, and distance from nearby a primary health centre (PHC). For Kolkata, the factors are unemployment, income, the number of rooms, sleeping patterns, avoidance of nonvegetarian food, sources of water, comorbidities, and distance from a PHC. The study shows that every city has a different set of variables that influences vulnerability, and each factor should be considered in design plans to mitigate vulnerability to extreme heat.

Vulnerability of Australia to heatwaves: A systematic review on influencing factors, impacts, and mitigation options

BACKGROUND

Heatwaves have received major attention globally due to their detrimental effects on human health and the environment. The frequency, duration, and severity of heatwaves have increased recently due to changes in climatic conditions, anthropogenic forcing, and rapid urbanization. Australia is highly vulnerable to this hazard. Although there have been an increasing number of studies conducted in Australia related to the heatwave phenomena, a systematic review of heatwave vulnerability has rarely been reported in the literature.

OBJECTIVES

This study aims to provide a systematic and overarching review of the different components of heatwave vulnerability (e.g., exposure, sensitivity, and adaptive capacity) in Australia.

METHODS

A systematic review was conducted using the PRISMA protocol. Peer-reviewed English language articles published between January 2000 and December 2021 were selected using a combination of search keywords in Web of Science, Scopus, and PubMed. Articles were critically analyzed based on three specific heatwave vulnerability components: exposure, sensitivity, and adaptive capacity.

RESULTS AND DISCUSSION

A total of 107 articles meeting all search criteria were chosen. Although there has been an increasing trend of heat-related studies in Australia, most of these studies have concentrated on exposure and adaptive capacity components. Evidence suggests that the frequency, severity, and duration of heatwaves in Australian cities has been increasing, and that this is likely to continue under current climate change scenarios. This study noted that heatwave vulnerability is associated with geographical and climatic factors, space, time, socioeconomic and demographic factors, as well as the physiological condition of people. Various heat mitigation and adaptation measures implemented around the globe have proven to be efficient in reducing the impacts of heatwaves.

CONCLUSION

This study provides increased clarity regarding the various drivers of heatwave vulnerability in Australia. Such knowledge is crucial in informing extreme heat adaptation and mitigation planning.

Socioeconomic inequalities and the surface heat island distribution in Santiago, Chile

Surface urban heat islands (SUHIs) are an important socio-environmental problem associated with large cities, such as the Santiago Metropolitan Area (SMA), in Chile. Here, we analyze daytime and nighttime variations of SUHIs for each season of the year during the period 2000-2020. To evaluate socioeconomic inequities in the distribution of SUHIs, we establish statistical relationships with socioeconomic status, land price, and urban vegetation. We use the MODIS satellite images to obtain the land surface temperatures and the normalized difference vegetation index (NDVI) through the Google Earth Engine platform. The results indicate more intense SUHIs during the nighttime in the eastern sector, coinciding with higher socioeconomic status and larger green areas. This area during the day is cooler than the rest of the city. The areas with lower and middle socioeconomic status suffer more intense SUHIs (daytime and nighttime) and match poor environmental and urban qualities. These results show the high segregation of SMA. Urban planning is subordinated to land prices with a structure maintained over the study period. The lack of social-climate justice is unsustainable, and such inequalities may be exacerbated in the context of climate change. Thus, these results can contribute to the planning of the SMA.

Research on the Characteristics of High-Temperature Heat Waves and Outdoor Thermal Comfort: A Typical Space in Chongqing Yuzhong District as an Example

For the high-density urban space heat wave problem, take the core urban area of the mountainous city of Chongqing as an example, four types of typical urban functional spaces, including commercial areas, residential areas, mountain parks, and riverfront parks, were measured during a heat wave cycle, and the characteristics of high-temperature heat waves in different urban spaces were compared through the analysis of air temperature, surface temperature, relative humidity, solar thermal radiation, and other thermal environment parameters. Combined with the questionnaire research related to the heat comfort of the urban population, the physiological equivalent temperature (PET) was selected to describe the heat sensation of the human body, to summarize the elements and patterns of the influence of heat waves on heat comfort of the population in urban spaces, and to establish a prediction model of outdoor heat comfort in summer. It shows that: (1) temperatures recorded during the heat waves are influenced by urban space elements and are differentiated, with older residential areas recording the highest temperatures, followed by commercial areas, and green park areas comparing favorably with both; (2) crowd thermal comfort is correlated with the thermal environment formed by space elements, PET is significantly positively correlated with air temperature, thermal radiation and surface temperature, and significantly negatively correlated with relative humidity, air temperature and thermal radiation have more influence on thermal comfort has a greater impact, while relative humidity and surface temperature have a relatively small impact; (3) reasonable spatial form and shade planning, vegetation and water body settings, high thermal storage substrate and other design elements can alleviate high-temperature heat waves, reduce the thermal neutral temperature and improve thermal comfort. The research results provide some basis for the investigation of the formation mechanism of high-temperature heat waves in mountainous cities and the optimal design of urban spatial thermal environment.

Assessing the Spatial Mapping of Heat Vulnerability under Urban Heat Island (UHI) Effect in the Dhaka Metropolitan Area

The urban heat island (UHI) phenomenon gets intensified in the process of urbanization, which increases the vulnerability of urban dwellers to heatwaves. The UHI-induced vulnerability to heatwaves has increased in Bangladesh during past decades. Thus, this study aims to examine the UHI and vulnerability to heatwaves in the city of Dhaka using a heat vulnerability index (HVI). The HVI is constructed using various demographic, socioeconomic, and environmental risk variables at thana level. Principal component analysis (PCA) was applied to the 26 normalized variables for each of the 41 thanas of Dhaka to prepare the HVI. Result shows that more than 60% of the city is under built-up areas, while vegetation cover and water bodies are in low proportion. Analysis of HVI shows that the very high- and high-risk zones comprise 6 and 11 thanas, while low- and very low-risk zones comprise only 5 and 8 thanas. The correlation of HVI with variables such as exposure (0.62) and sensitivity (0.80) was found to be highly positive, while adaptive capacity had a negative correlation (−0.26) with the HVI. Findings of this study can be utilized in the mitigation of UHI phenomenon and maintaining the thermal comfort of Dhaka.

Modeling the Relationships Between Historical Redlining, Urban Heat, and Heat-Related Emergency Department Visits: An Examination of 11 Texas Cities

Place-based structural inequalities can have critical implications for the health of vulnerable populations. Historical urban policies, such as redlining, have contributed to current inequalities in exposure to intra-urban heat. However, it is unknown whether these spatial inequalities are associated with disparities in heat-related health outcomes. The aim of this study is to determine the relationships between historical redlining, intra-urban heat conditions, and heat-related emergency department visits using data from eleven Texas cities. At the zip code level, the proportion of historical redlining was determined, and heat exposure was measured using daytime and nighttime land surface temperature (LST). Heat-related inpatient and outpatient rates were calculated based on emergency department visit data that included ten categories of heat-related diseases between 2016 and 2019. Regression or spatial error/lag models revealed significant associations between higher proportions of redlined areas in the neighborhood and higher LST (Coef. = 0.0122, 95% CI = 0.0039 - 0.0205). After adjusting for indicators of social vulnerability, neighborhoods with higher proportions of redlining showed significantly elevated heat-related outpatient visit rate (Coef. = 0.0036, 95% CI = 0.0007-0.0066) and inpatient admission rate (Coef. = 0.0018, 95% CI = 0.0001-0.0035). These results highlight the role of historical discriminatory policies on the disparities of heat-related illness and suggest a need for equity-based urban heat planning and management strategies.

Intraurban heterogeneity of space-time land surface temperature trends in six climate-diverse cities

Surface urban heat islands (SUHIs) are present in all cities, derived from their thermal properties. While looking at the spatiotemporal variability of land surface temperature (LST), there is still a gap in understanding patterns of change. In this paper, we analysed diurnal and nocturnal annual mean LST trends in continental (Beijing), temperate (Mexico City and Santiago), and arid (Cairo, Hyderabad, and Riyadh) cities employing 1 km MODIS data (2003-2019). Each time-series was assessed with the structure of a space-time cube. Hot and cold spots were detected for each year and the LST trends were analysed. Each pixel was classified into different space-time LST trends and their SUHIs were estimated. Cities exhibit trends of increasing temperatures in cold and hot spots for diurnal and nocturnal data. Temperatures are increasing faster in hot spots for diurnal and in cold spots for nocturnal scenes. Steady hot spots and warming hot spots exhibit the highest SUHIs for day and night. Our approach provides a framework to empirically delineate the spatial intraurban heterogeneity of LST patterns over time. This spatially explicit information provides insights into urban areas requiring heat mitigation strategies and can be used to monitor the performance of measures already implemented for climate adaptation.

A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Urbanites of Four Cities of India

Extreme heat and heat waves have been established as disasters which can lead to a great loss of life. Several studies over the years, both within and outside of India, have shown how extreme heat events lead to an overall increase in mortality. However, the impact of extreme heat, similar to other disasters, depends upon the vulnerability of the population. This study aims to assess the extreme heat vulnerability of the population of four cities with different characteristics across India. This cross-sectional study included 500 households from each city across the urban localities (both slum and non-slum) of Ongole in Andhra Pradesh, Karimnagar in Telangana, Kolkata in West Bengal and Angul in Odisha. Twenty-one indicators were used to construct a household vulnerability index to understand the vulnerability of the cities. The results have shown that the majority of the households fell under moderate to high vulnerability level across all the cities. Angul and Kolkata were found to be more highly vulnerable as compared to Ongole and Karimnagar. Further analysis also revealed that household vulnerability is more significantly related to adaptive capacity than sensitivity and exposure. Heat Vulnerability Index can help in identifying the vulnerable population and scaling up adaptive practices.

Approaches for identifying heat-vulnerable populations and locations: A systematic review

Heat related morbidity and mortality, especially during extreme heat events, are increasing due to climate change. More Americans die from heat than from all other natural disasters combined. Identifying the populations and locations that are under high risk of heat vulnerability is important for urban planning and design policy making as well as health interventions. An increasing number of heat vulnerability/risk models and indices (HV/R) have been developed based on indicators related to population heat susceptibility such as sociodemographic and environmental factors. The objectives of this study are to summarize and analyze current HV/R's construction, calculation, and validation, evaluate the limitation of these methods, and provide directions for future HV/R and related studies. This systematic review used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework and used 5 datasets for the literature search. Journal articles that developed indices or models to assess population level heat-related vulnerability or risks in the past 50 years were included. A total of 52 papers were included for analysis on model construction, data sources, weighting schemes and model validation. By synthesizing the findings, we suggested: (1) include relevant and accurately measured indicators; (2) select rational weighting methods and; (3) conduct model validation. We also concluded that it is important for future heat vulnerability models and indices studies to: (1) be conducted in more tropical areas; (2) include a comprehensive understanding of energy exchanges between landscape elements and humans; and (3) be applied in urban planning and policy making practice.

A human-centred assessment framework to prioritise heat mitigation efforts for active travel at city scale

Hot weather not only impacts upon human physical comfort and health, but also impacts the way that people access and experience active travel options such as walking and cycling. By evaluating the street thermal environment of a city alongside an assessment of those communities that are the most vulnerable to the effects of heat, we can prioritise areas in which heat mitigation interventions are most needed. In this paper, we propose a new approach for policy makers to determine where to delegate limited resources for heat mitigation with most effective outcomes for the communities. We use eye-level street panorama images and community profiles to provide a bottom-up, human-centred perspective of the city scale assessment, highlighting the situation of urban tree shade provision throughout the streets in comparison with environmental and social-economic status. The approach leverages multiple sources of spatial data including satellite thermal images, Google street view (GSV) images, land use and demographic census data. A deep learning model was developed to automate the classification of streetscape types and percentages at the street- and eye-view level. The methodology is metrics based and scalable which provides a data driven assessment of heat-related vulnerability. The findings of this study first contribute to sustainable development by developing a method to identify geographical areas or neighbourhoods that require heat mitigation; and enforce policies improving tree shade on routes, as a heat adaptation strategy, which will lead to increasing active travel and produce significant health benefits for residents. The approach can be also used to guide post COVID-19 city planning and design.

Investigating the Integration of Cultural Heritage Disaster Risk Management into Urban Planning Tools. The Ravenna Case Study

As increasingly recognized by scholars, climate change is posing new challenges in the field of disaster risk management and urban planning. Even though cultural heritage has passed through decades and centuries, it has never experienced such unexpected and variable events as those forecasted by climate change for the foreseeable future, making it a sensitive element of the living environment. By selecting the city of Ravenna and the cultural heritage site of the Santa Croce Church and archaeological area as a case study, the paper aims at providing an insight into the role that urban planning tools have when it comes to improving the resilience of historical areas, coping with climate change through improvements to the disaster risk management of cultural heritage. Starting from a deep analysis of the existing spatial and urban planning tools that operate at different scales on the Ravenna territory, the adaptive capacity of the historical area toward the identified risks was assessed. The results may lead, on the one hand, to improving the integration of cultural heritage risk management into urban planning tools; on the other hand, they contribute to improving the scope and the governance of the heritage management plans in order to cope with climate change risks and their effects.

Social inequalities in heat-attributable mortality in the city of Turin, northwest of Italy: a time series analysis from 1982 to 2018

BACKGROUND

Understanding context specific heat-health risks in urban areas is important, especially given anticipated severe increases in summer temperatures due to climate change effects. We investigate social inequalities in the association between daily temperatures and mortality in summer in the city of Turin for the period 1982-2018 among different social and demographic groups such as sex, age, educational level, marital status and household occupants.

METHODS

Mortality data are represented by individual all-cause mortality counts for the summer months between 1982 and 2018. Socioeconomic level and daily mean temperature were assigned to each deceased. A time series Poisson regression with distributed lag non-linear models was fitted to capture the complex nonlinear dependency between daily mortality and temperature in summer. The mortality risk due to heat is represented by the Relative Risk (RR) at the 99th percentile of daily summer temperatures for each population subgroup.

RESULTS

All-cause mortality risk is higher among women (1.88; 95% CI = 1.77, 2.00) and the elderly (2.13; 95% CI = 1.94, 2.33). With regard to education, the highest significant effects for men is observed among higher education levels (1.66; 95% CI = 1.38, 1.99), while risks for women is higher for the lower educational level (1.93; 95% CI = 1.79, 2.08). Results on marital status highlighted a stronger association for widower in men (1.66; 95% CI = 1.38, 2.00) and for separated and divorced in women (2.11; 95% CI = 1.51, 2.94). The risk ratio of household occupants reveals a stronger association for men who lived alone (1.61; 95% CI = 1.39, 1.86), while for women results are almost equivalent between alone and not alone groups.

CONCLUSIONS

The associations between heat and mortality is unequal across different aspects of social vulnerability, and, inter alia, factors influencing the population vulnerability to temperatures can be related to demographic, social, and economic aspects. A number of issues are identified and recommendations for the prioritisation of further research are provided. A better knowledge of these effect modifiers is needed to identify the axes of social inequality across the most vulnerable population sub-groups.

Health effects of heat vulnerability in Rio de Janeiro: a validation model for policy applications

Extreme heat events can lead to increased risk of heat-related deaths. Furthermore, urban areas are often hotter than their rural surroundings, exacerbating heat waves. Unfortunately, validation is difficult; to our knowledge, most validations, even if they control for temperatures, really only validate a social vulnerability index instead of a heat vulnerability index. Here we investigate how to construct and validate a heat vulnerability index given uncertainty ranges in data for the city of Rio de Janeiro. First, we compare excess deaths of certain types of circulatory diseases during heat waves. Second, we use demographic and environmental data and factor analysis to construct a set of unobserved factors and respective weightings related to heat vulnerability, including a Monte Carlo analysis to represent the uncertainty ranges assigned to the input data. Finally, we use distance to hospital and clinics and their health record data as an instrumental variable to validate our factors. We find that we can validate the Rio de Janeiro heat vulnerability index against excess deaths during heat waves; specifically, we use three types of regressions coupled with difference in difference calculations to show this is indeed a heat vulnerability index as opposed to a social vulnerability index. The factor analysis identifies two factors that contribute to >70% of the variability in the data; one socio-economic factor and one urban form factor. This suggests it is necessary to add a step to existing methods for validation of heat vulnerability indices, that of the difference-in-difference calculation.

Intraurban social risk and mortality patterns during extreme heat events: A case study of Moscow, 2010-2017

There is currently an increase in the number of heat waves occurring worldwide. Moscow experienced the effects of an extreme heat wave in 2010, which resulted in more than 10,000 extra deaths and significant economic damage. This study conducted a comprehensive assessment of the social risks existing during the occurrence of heat waves and allowed us to identify the spatial heterogeneity of the city in terms of thermal risk and the consequences for public health. Using a detailed simulation of the meteorological regime based on the COSMO-CLM regional climate model and the physiologically equivalent temperature (PET), a spatial assessment of thermal stress in the summer of 2010 was carried out. Based on statistical data, the components of social risk (vulnerabilities and adaptive capacity of the population) were calculated and mapped. We also performed an analysis of their changes in 2010-2017. A significant differentiation of the territory of Moscow has been revealed in terms of the thermal stress and vulnerability of the population to heat waves. The spatial pattern of thermal stress agrees quite well with the excess deaths observed during the period from July to August 2010. The identified negative trend of increasing vulnerability of the population has grown in most districts of Moscow. The adaptive capacity has been reduced in most of Moscow. The growth of adaptive capacity mainly affects the most prosperous areas of the city.

Mapping Heat-Related Risks in Northern Jiangxi Province of China Based on Two Spatial Assessment Frameworks Approaches

Heat-health risk is a growing concern in many regions of China due to the more frequent occurrence of extremely hot weather. Spatial indexes based on various heat assessment frameworks can be used for the assessment of heat risks. In this study, we adopted two approaches—Crichton’s risk triangle and heat vulnerability index (HVI) to identify heat-health risks in the Northern Jiangxi Province of China, by using remote sensing and socio-economic data. The Geographical Information System (GIS) overlay and principal component analysis (PCA) were separately used in two frameworks to integrate parameters. The results show that the most densely populated community in the suburbs, instead of city centers, are exposed to the highest heat risk. A comparison of two heat assessment mapping indicates that the distribution of HVI highlights the vulnerability differences between census tracts. In contrast, the heat risk index of Crichton’s risk triangle has a prominent representation for regions with high risks. The stepwise multiple linear regression zero-order correlation coefficient between HVI and outdoor workers is 0.715, highlighting the vulnerability of this particular group. Spearman’s rho nonparametric correlation and the mean test reveals that heat risk index is strongly correlated with HVI in most of the main urban regions in the study area, with a significantly lower value than the latter. The analysis of variance shows that the distribution of HVI exhibits greater variety across urban regions than that of heat risk index. Our research provides new insight into heat risk assessment for further study of heat health risk in developing countries.

Mapping Human Vulnerability to Extreme Heat: A Critical Assessment of Heat Vulnerability Indices Created Using Principal Components Analysis

BACKGROUND

Extreme heat poses current and future risks to human health. Heat vulnerability indices (HVIs), commonly developed using principal components analysis (PCA), are mapped to identify populations vulnerable to extreme heat. Few studies critically assess implications of analytic choices made when employing this methodology for fine-scale vulnerability mapping.

OBJECTIVE

We investigated sensitivity of HVIs created by applying PCA to input variables and whether training input variables on heat-health data produced HVIs with similar spatial vulnerability patterns for Detroit, Michigan, USA.

METHODS

We acquired 2010 Census tract and block group level data, land cover data, daily ambient apparent temperature, and all-cause mortality during May-September, 2000-2009. We used PCA to construct HVIs using: a) "unsupervised"-PCA applied to variables selected a priori as risk factors for heat-related health outcomes; b) "supervised"-PCA applied only to variables significantly correlated with proportion of all-cause mortality occurring on extreme heat days (i.e., days with 2-d mean apparent temperature above month-specific 95th percentiles).

RESULTS

Unsupervised and supervised HVIs yielded differing spatial vulnerability patterns, depending on selected land cover input variables. Supervised PCA explained 62% of variance in the input variables and was applied on half the variables used in the unsupervised method. Census tract-level supervised HVI values were positively associated with increased proportion of mortality occurring on extreme heat days; supervised PCA could not be applied to block group data. Unsupervised HVI values were not associated with extreme heat mortality for either tracts or block groups.

DISCUSSION

HVIs calculated using PCA are sensitive to input data and scale. Supervised HVIs may provide marginally more specific indicators of heat vulnerability than unsupervised HVIs. PCA-derived HVIs address correlation among vulnerability indicators, although the resulting output requires careful contextual interpretation beyond generating epidemiological research questions. Methods with reliably stable outputs should be leveraged for prioritizing heat interventions. https://doi.org/10.1289/EHP4030.

Housing as a critical determinant of heat vulnerability and health

Municipalities use Heat Vulnerability Indices (HVIs) to quantify and map relative distribution of risks to human health in the event of a heatwave. These maps ostensibly allow public agencies to identify the highest-risk neighborhoods, and to concentrate emergency planning efforts and resources accordingly (e.g., to establish the locations of cooling centers). The method of constructing an HVI varies by municipality, but common inputs include demographic variables such as age and income - and to some extent, metrics such as land cover. However, taking demographic data as a proxy for heat vulnerability may provide an incomplete or inaccurate assessment of risk. A critical limitation in HVIs may be a lack of focus on housing characteristics and how they mediate indoor heat exposure. To provide an objective assessment of this limitation, we first reviewed HVIs in the literature and those published or commissioned by municipalities. We subsequently verified that most of these HVIs excluded housing factors. Next, to scope the potential consequences, we used physics-based simulations of housing prototypes (46,000 housing permutations per city) to estimate the variation in indoor heat exposure within high-vulnerability neighborhoods in Boston and Phoenix. The results show that by excluding building-level determinants of exposure, HVIs fail to capture important components of heat vulnerability. Moreover, we demonstrate how these maps currently overlook important nuances regarding the impact of building age and air conditioning functionality. Finally, we discuss the challenges of implementing housing stock characteristics in HVIs and propose methods for overcoming these challenges.

Spatial Heterogeneous of Ecological Vulnerability in Arid and Semi-Arid Area: A Case of the Ningxia Hui Autonomous Region, China

Ecological vulnerability, as an important evaluation method reflecting regional ecological status and the degree of stability, is the key content in global change and sustainable development. Most studies mainly focus on changes of ecological vulnerability concerning the temporal trend, but rarely take arid and semi-arid areas into consideration to explore the spatial heterogeneity of the ecological vulnerability index (EVI) there. In this study, we selected the Ningxia Hui Autonomous Region on the Loess Plateau of China, a typical arid and semi-arid area, as a case to investigate the spatial heterogeneity of the EVI every five years, from 1990 to 2015. Based on remote sensing data, meteorological data, and economic statistical data, this study first evaluated the temporal‒spatial change of ecological vulnerability in the study area by Geo-information Tupu. Further, we explored the spatial heterogeneity of the ecological vulnerability using Getis-Ord Gi*. Results show that: (1) the regions with high ecological vulnerability are mainly concentrated in the north of the study area, which has high levels of economic growth, while the regions with low ecological vulnerability are mainly distributed in the relatively poor regions in the south of the study area. (2) From 1990 to 2015, ecological vulnerability showed an increasing trend in the study area. Additionally, there is significant transformation between different grades of the EVI, where the area of transformation between a slight vulnerability level and a light vulnerability level accounts for 41.56% of the transformation area. (3) Hot-spot areas of the EVI are mainly concentrated in the north of the study area, and cold-spot areas are mainly concentrated in the center and south of the study area. Spatial heterogeneity of ecological vulnerability is significant in the central and southern areas but insignificant in the north of the study area. (4) The grassland area is the main driving factor of the change in ecological vulnerability, which is also affected by both arid and semi-arid climates and ecological projects. This study can provide theoretical references for sustainable development to present feasible suggestions on protection measures and management modes in arid and semi-arid areas.

The application of frameworks for measuring social vulnerability and resilience to geophysical hazards within developing countries: A systematic review and narrative synthesis

Quantifying and mapping resilience and social vulnerability is a widely used technique to support risk management, with recent years seeing a proliferation of applications across the Global South. To synthesise this emerging literature, we conducted a systematic review of applications of social vulnerability and resilience frameworks in Lower and Middle Income Countries (LMICs) using the PRISMA methodology. 2152 papers were extracted from 15 databases and then screened according to our pre-defined criteria, leaving 68 studies for full text analysis. Our analysis revealed that: (1) Most studies consider vulnerability or resilience to be generic properties of social systems; (2) Few papers measured vulnerability or resilience in a way that tests whether they are relatively stable or dynamic features of social systems; (3) Many applications rely on stock applications of existing frameworks, with little adaptation to specific cultural, societal or economic contexts; (4) There is a lack of systematic validation; (5) More hypothesis-driven studies (as opposed to descriptive mapping exercises) are required in order to develop a better understanding of the mechanisms through which vulnerability and resilience shape the capacity to prepare for, respond and recover from disasters.

Assessing Urban Risk to Extreme Heat in China

Many cities are experiencing persistent risk in China due to frequent extreme weather events. Some extreme weather events, such as extreme heat hazard, have seriously threatened human health and socio-economic development in cities. There is an urgent need to measure the degree of extreme heat risk and identify cites with the highest levels of extreme heat risk. In this study, we presented a risk assessment framework of extreme heat and considered risk as a combination of hazard, exposure, and vulnerability. Based on these three dimensions, we selected relevant variables from historical meteorological data (1960–2016) and socioeconomic statistics in 2016, establishing an indicator system of extreme heat risk evaluation. Finally, we developed an extreme heat risk index to quantify the levels of extreme heat risk of 296 prefecture-level cities in China and revealed the spatial pattern of extreme heat risk in China in 2016 and their dominant factors. The results show that (1) cities with high levels of extreme heat hazard are mainly located in the south of China, especially in the southeast of China; (2) the spatial distribution of the extreme heat risk index shows obvious agglomeration characteristics; (3) the spatial distribution of the extreme heat risk is still mostly controlled by natural geographical conditions such as climate and topography; (4) among the four types of hazard-dominated, exposure-dominated, vulnerability-dominated, and low risk cities, the number of vulnerability-dominated cities is the largest. The results of this study can provide support for the risk management of extreme heat disasters and the formation of targeted countermeasures in China.

Heat health risk assessment in Philippine cities using remotely sensed data and social-ecological indicators

More than half of the world’s population currently live in urban areas and are particularly at risk from the combined effects of the urban heat island phenomenon and heat increases due to climate change. Here, by using remotely sensed surface temperature data and social-ecological indicators, focusing on the hot dry season, and applying the risk framework of the Intergovernmental Panel on Climate Change, we assessed the current heat health risk in 139 Philippine cities, which account for about 40% of the country’s total population. The cities at high or very high risk are found in Metro Manila, where levels of heat hazard and exposure are high. The most vulnerable cities are, however, found mainly outside the national capital region, where sensitivity is higher and capacity to cope and adapt is lower. Cities with high levels of heat vulnerability and exposure must be prioritized for adaptation. Our results will contribute to risk profiling in the Philippines and to the understanding of city-level heat health risks in developing regions of the Asia-Pacific.

Evaluating the heat risk among city dwellers is important. Here, the authors assessed the heat risk in Philippine cities using remote sensing data and social-ecological indicators and found that the cities at high or very high risk are found in Metro Manila, where levels of heat hazard and exposure are high.

A Comparative Study of the Physiological and Socio-Economic Vulnerabilities to Heat Waves of the Population of the Metropolis of Lyon (France) in a Climate Change Context

Increases in the frequency and intensity of heat waves are direct consequences of global climate change with a higher risk for urban populations due to the urban heat island effect. Reducing urban overheating is a priority, as is identifying the most vulnerable people to establish targeted and coordinated public health policies. There are many ways of understanding the concept of vulnerability and multiple definitions and applications exist in the literature. To date, however, nothing has been done on the territory of this study, the metropolis of Lyon (France). The objective is thus to construct two vulnerability indices: physiological, focusing on the organism's capacities to respond to heat waves; and socio-economic, based on the social and economic characteristics and capacities of the community. To this end, two complementary methodologies have been implemented: the AHP (Analytic Hierarchy Process) and the PCA (Principal Component Analysis) with Varimax rotation, respectively. The results were then spatialized to the smallest demographic census unit in France. The areas highlighted differed due to conceptual and methodological differences: the highest physiological vulnerabilities are in the center while the socio-economic ones are in the eastern periphery of the urban area. The location of these areas will enable prevention campaigns to be carried out, targeted according to the publics concerned.

Is Sensible Heat Flux Useful for the Assessment of Thermal Vulnerability in Seoul (Korea)?

Climate change has led to increases in global temperatures, raising concerns regarding the threat of lethal heat waves and deterioration of the thermal environment. In the present study, we adopted two methods for spatial modelling of the thermal environment based on sensible heat and temperature. A vulnerability map reflecting daytime temperature was derived to plot thermal vulnerability based on sensible heat and climate change exposure factors. The correlation (0.73) between spatial distribution of sensible heat vulnerability and mortality rate was significantly greater than that (0.30) between the spatial distribution of temperature vulnerability and mortality rate. These findings indicate that deriving thermally vulnerable areas based on sensible heat are more objective than thermally vulnerable areas based on existing temperatures. Our findings support the notion that the distribution of sensible heat vulnerability at the community level is useful for evaluating the thermal environment in specific neighbourhoods. Thus, our results may aid in establishing spatial planning standards to improve environmental sustainability in a metropolitan community.

Appraisal of the heat vulnerability index in Punjab: a case study of spatial pattern for exposure, sensitivity, and adaptive capacity in megacity Lahore, Pakistan

In this study, the heat vulnerability index has been developed for a megacity Lahore. Although Pakistan stands at 12th rank among highly exposed countries to climate change, very little research has been dedicated in exploring the heat-related vulnerability of exposed populations. We have applied the principal component analysis with varimax rotation on well-established indicators of exposure, sensitivity, and adaptive capacity to determine the heat vulnerability. This study has resulted in two principal components sharing 70.4% variance. Principal component 1 comprises pre-existing illness, population density, housing density, education, and normalized difference vegetation index with following significant (> 0.4) loading values 0.91, 0.91, 0.91, 0.57, and - 0.773, respectively, and principal component 2 combines the nature of housing material (0.964) followed by the water availability (0.962) and minority status (0.539). The hot spot analysis and overlay analysis have also been applied on the extracted component, and the resultant co-occurrence of high variable class, high vulnerability, and hot spots of vulnerability helped to grip those areas which imperatively require the applications of heat-related health interventions. The heat vulnerability index developed in our study clarifies that the most vulnerable populations are confined in the central vicinities of Lahore and less vulnerable are those which inhibit towards the outskirts of the city.

MI-Environment: Geospatial patterns and inequality of relative heat stress vulnerability in Michigan

Heat stress causes morbidity and mortality and is increasing with climate change. Heat stress can pose particular challenges in northern regions not well adapted to heat. To assist decision makers, we identified the relative vulnerability of census tracts within Michigan to factors that increase exposure to heat stress or reflect susceptibilities in the population based on a California heat vulnerability index. In the MI-Environment assessment, we used a Geographic Information System (GIS) to combine future ensemble climate model projections to create a total of 9 geospatial and demographic variables. As part of a broader planned cumulative environmental exposure assessment, the statewide heat vulnerability index (HVI) maps display the location and relative magnitude of exposure on three metrics: built environment (Place), future expected long-term temperature averages (Temperature), and population susceptibility (People). We observed varied and distinct patterns for each of the three component indices. We assessed how equitably those exposures are distributed by racial and socioeconomic factors. This analysis showed that each of the component indices and the aggregate HVI are disproportionately distributed along racial and socioeconomic lines in Michigan. Census tracts with higher percentages of people of color had larger exposure to HVI factors with a deviation from equity of -0.115 [95% CI -0.108, -0.122]. Similarly, for census tracts with higher percentage of people experiencing poverty, the deviation from equity was -0.101 [95% CI -0.094, -0.107]. The MI-Environment visualization tool can help communities prepare for climate change and resolve inequities by identifying census tracts with the most vulnerable residents and highest potential exposures.

Estimating Fine-Scale Heat Vulnerability in Beijing Through Two Approaches: Spatial Patterns, Similarities, and Divergence

High temperatures in urban areas cause a significant negative impact on the residents’ health. In a megacity such as Beijing, where both the land cover and social composition of residents are highly spatially heterogeneous, understanding heat vulnerability at a relatively fine scale is a prerequisite for place-based heat intervention actions. Both principal component analysis (PCA) and equal-weighted index (EWI) are commonly used in heat vulnerability studies. However, the extent to which the choice of these approaches may impact the results remains unclear. Our study aimed to fill this gap by estimating heat vulnerability at the jiedao scale (the smallest census unit) in Beijing based on socioeconomic characteristics, heat exposure, and the use of air conditioners. Our results show that the choice of methods had a considerable impact on the spatial patterns of estimated heat vulnerability. PCA resulted in a ring-like pattern (high in the central and low in the suburb), whereas EWI revealed a north–south discrepancy (low in the north and high in the south). Such a difference is caused by the weighting scheme used in the PCA. Our findings indicate that heat vulnerability pattern revealed by a single measure needs to be interpreted with caution because different measures may produce disparate results.

New ECOSTRESS and MODIS Land Surface Temperature Data Reveal Fine-Scale Heat Vulnerability in Cities: A Case Study for Los Angeles County, California

Rapid 21st century urbanization combined with anthropogenic climate warming are significantly increasing heat-related health threats in cities worldwide. In Los Angeles (LA), increasing trends in extreme heat are expected to intensify and exacerbate the urban heat island effect, leading to greater health risks for vulnerable populations. Partnerships between city policymakers and scientists are becoming more important as the need to provide data-driven recommendations for sustainability and mitigation efforts becomes critical. Here we present a model to produce heat vulnerability index (HVI) maps driven by surface temperature data from National Aeronautics and Space Administration’s (NASA) new Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) thermal infrared sensor. ECOSTRESS was launched in June 2018 with the capability to image fine-scale urban temperatures at a 70 m resolution throughout different times of the day and night. The HVI model further includes information on socio-demographic data, green vegetation abundance, and historical heatwave temperatures from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Aqua spacecraft since 2002. During a period of high heat in July 2018, we identified the five most vulnerable communities at a sub-city block scale in the LA region. The persistence of high HVI throughout the day and night in these areas indicates a clear and urgent need for implementing cooling technologies and green infrastructure to curb future warming.

Assessing the Heat Vulnerability of Different Local Climate Zones in the Old Areas of a Chinese Megacity

Frequent and extreme heat waves have strongly influenced the sustainable development of cities and resulted in a higher level of mortality in residents. Using the Local Climate Zone (LCZ) classification scheme, combined with the factors of land surface temperature (LST), building age (BA), and housing price (HP), and the normalized values of which represent heat exposure, sensitivity, and adaptability, respectively, this paper investigates a practical method for assessing the heat vulnerability of different LCZ classes in the old areas of a Chinese megacity, taking the Yuzhong district of Chongqing city as a case study. The results reveal that the distribution of LCZ classes in this study area exhibits a typical circle-layer distribution pattern from the city center to the suburbs. Heavy industry areas are the most vulnerable, with the highest exposure to heat waves, the oldest building age and the lowest housing price. Compact class areas (compact high-rise, compact mid-rise and compact low-rise) are usually more vulnerable than open class areas (open high-rise, open mid-rise, and open low-rise) and low-rise buildings are always more susceptible to heat waves than mid-rise and high-rise buildings. The methods and findings can help us to better understand the comprehensive and space–time action rules of heat vulnerability, thereby inspiring scientific and rational urban planning strategies to mitigate or adapt to urban heat weaves towards the sustainable development of cities and society.

Mortality and morbidity associated with ambient temperatures in Taiwan

BACKGROUND

This study evaluated integrated risks of all-cause mortality, emergency room visits (ERVs), and outpatient visits associated with ambient temperature in all cities and counties of Taiwan. In addition, the modifying effects of socio-economic and environmental factors on temperature-health associations were also evaluated.

METHODS

A distributed lag non-linear model was applied to estimate the cumulative relative risks (RRs) with confidence intervals of all-cause mortality, ERVs, and outpatient visits associated with extreme temperature events. Random-effect meta-analysis was used to estimate the pooled RR of all-cause mortality, ERVs, and outpatient visits influenced by socio-economic and environmental factors.

RESULTS

Temperature-related risks varied with study area and health outcome. Meta-analysis showed greater all-cause mortality risk occurred in low temperatures than in high temperatures. Integrated RR of all-cause mortality was 1.71 (95% confidence interval [CI]:1.43-2.04) in the 5th percentile temperature and 1.10 (95% CI: 1.05-1.15) in the 95th percentile temperature, while the lowest mortality risk was in the 60th percentile temperature (22.2 °C). Risk for ERVs increased when temperature increased (RR was 1.21 [95% CI: 1.17-1.26] in 95th percentile temperature), but risk of outpatient visits increased at low temperatures (RR was 1.06 [95% CI: 1.01-1.12] in the 5th percentile temperature). Certain socio-economic factors significantly modified low-temperature-related mortality risks, including number of employed populations, elders living alone from lower-income families, and public and medical services.

CONCLUSIONS

This study found that mortality and outpatient visits were higher at low temperature, while ERVs risk was higher at high temperature. Future plans for public health and emerging medical services responding to extreme temperatures should consider regional and integrated evaluations of temperature-related health risks and modifying factors.

A Raster-Based Subdividing Indicator to Map Urban Heat Vulnerability: A Case Study in Sydney, Australia

Assessing and mapping urban heat vulnerability has developed significantly over the past decade. Many studies have mapped urban heat vulnerability with a census unit-based general indicator (CGI). However, this kind of indicator has many problems, such as inaccurate assessment results and lacking comparability among different studies. This paper seeks to address this research gap and proposes a raster-based subdividing indicator to map urban heat vulnerability. We created a raster-based subdividing indicator (RSI) to map urban heat vulnerability from 3 aspects: exposure, sensitivity and adaptive capacity. We applied and compared it with a raster-based general indicator (RGI) and a census unit-based general indicator (CGI) in Sydney, Australia. Spatial statistics and analysis were used to investigate the performance among those three indicators. The results indicate that: (1) compared with the RSI framework, 67.54% of very high heat vulnerability pixels were ignored in the RGI framework; and up to 83.63% of very high heat vulnerability pixels were ignored in the CGI framework; (2) Compared with the previous CGI framework, a RSI framework has many advantages. These include more accurate results, more flexible model structure, and higher comparability among different studies. This study recommends using a RSI framework to map urban heat vulnerability in the future.

The Heat Exposure Integrated Deprivation Index (HEIDI): A data-driven approach to quantifying neighborhood risk during extreme hot weather

Mortality attributable to extreme hot weather is a growing concern in many urban environments, and spatial heat vulnerability indexes are often used to identify areas at relatively higher and lower risk. Three indexes were developed for greater Vancouver, Canada using a pool of 20 potentially predictive variables categorized to reflect social vulnerability, population density, temperature exposure, and urban form. One variable was chosen from each category: an existing deprivation index, senior population density, apparent temperature, and road density, respectively. The three indexes were constructed from these variables using (1) unweighted, (2) weighted, and (3) data-driven Heat Exposure Integrated Deprivation Index (HEIDI) approaches. The performance of each index was assessed using mortality data from 1998-2014, and the maps were compared with respect to spatial patterns identified. The population-weighted spatial correlation between the three indexes ranged from 0.68-0.89. The HEIDI approach produced a graduated map of vulnerability, whereas the other approaches primarily identified areas of highest risk. All indexes performed best under extreme temperatures, but HEIDI was more useful at lower thresholds. Each of the indexes in isolation provides valuable information for public health protection, but combining the HEIDI approach with unweighted and weighted methods provides richer information about areas most vulnerable to heat.