Assessing Heat Health Risk for Sustainability in Beijing’s Urban Heat Island

Variations of Urban Thermal Risk with Local Climate Zones

Due to the differences in land cover and natural surroundings within cities, residents in various regions face different thermal risks. Therefore, this study combined multi-source data to analyze the relationship between urban heat risk and local climate zones (LCZ). We found that in downtown Shenyang, the building-type LCZ was mainly found in urban centers, while the natural- type LCZ was mainly found in suburbs. Heat risk was highest in urban centers, gradually decreasing along the suburban direction. The thermal risk indices of the building-type LCZs were significantly higher than those of the natural types. Among the building types of LCZs, LCZ 8 (open middle high-rise) had the highest average thermal risk index (0.48), followed by LCZ 3 (0.46). Among the natural types of LCZs, LCZ E (bare rock and paved) and LCZ F (bare soil and sand) had the highest thermal risk indices, reaching 0.31 and 0.29, respectively. This study evaluated the thermal risk of the Shenyang central urban area from the perspective of LCZs and combined it with high-resolution remote sensing data to provide a reference for thermal risk mitigation in future urban planning.

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.

The relationship between the intensified heat waves and deteriorated summertime ozone pollution in the Beijing-Tianjin-Hebei region, China, during 2013-2017

Summertime ozone (O₃) pollution has frequently occurred in the Beijing-Tianjin-Hebei (BTH) region, China, since 2013, resulting in detrimental impacts on human health and ecosystems. The contribution of weather shifts to O₃ concentration variability owing to climate change remains elusive. By combining regional air chemistry model simulations with near-surface observations, we found that anthropogenic emission changes contributed to approximately 23% of the increase in maximum daily 8-h average O₃ concentrations in the BTH region in June-July-August (JJA) 2017 (compared with that in 2013). With respect to the weather shift influence, the frequencies, durations, and magnitudes of O₃ exceedance were consistent with those of the heat wave events in the BTH region during JJA in 2013-2017. Intensified heat waves are a significant driver for worsening O₃ pollution. In particular, the prolonged duration of heat waves creates consecutive adverse weather conditions that cause O₃ accumulation and severe O₃ pollution. Our results suggest that the variability in extreme summer heat is closely related to the occurrence of high O₃ concentrations, which is a significant driver of deteriorating O₃ pollution.

Spatially Balanced Sampling for Validation of GlobeLand30 Using Landscape Pattern-Based Inclusion Probability

Global and local land-cover mapping products provide important data on land surface. However, the accuracy of land-cover products is the key issue for their further scientific application. There has been neglect of the relationship between inclusion probability and spatial heterogeneity in traditional spatially balanced sampling. The aim of this paper was to propose an improved spatially balanced sampling method using landscape pattern-based inclusion probability. Compared with other global land-cover datasets, Globeland30 has the advantages of high resolution and high classification accuracy. A two-stage stratified spatially balanced sampling scheme was designed and applied to the regional validation of GlobeLand30 in China. In this paper, the whole area was divided into three parts: the Tibetan Plateau region, the Northwest China region, and the East China region. The results show that 7242 sample points were selected, and the overall accuracy of GlobeLand30-2010 in China was found to be 80.46%, which is close to the third-party assessment accuracy of GlobeLand30. This method improves the representativeness of samples, reduces the classification error of remote sensing, and provides better guidance for biodiversity and sustainable development of environment.

Beyond intensity of urban heat island effect: A continental scale analysis on land surface temperature in major Chinese cities

Intensity of urban heat island (UHII) is a key indicator to quantify the magnitude of UHI effect. Change in UHII, however, can be affected by change in urban or rural temperature, or both. Numerous studies have investigated the change of UHII, but how it relates to change in urban and rural temperature is poorly understood. Here we present a continental scale analysis on the change in UHII from 2000 to 2015 in 31 major cities in China, and further explored whether such change was caused by urban warming. We used time series analysis based on MODIS land surface temperature product (MOD11A2) in summer. We found: (1) A majority of the cities (25 out of 31) had an increasing trend in UHII from 2000 to 2015, among which 44% were significant, suggesting a significantly intensified UHI effects. (2) Intensified UHII does not necessarily mean deterioration of urban thermal environment, and vice versa. For the 25 cities with an increasing trend in UHII, 11 cities had a decreasing trend of LST in both urban and rural areas. Meanwhile, for the 6 cities with a decreasing trend in UHII, three had warming trend in both urban and rural areas. (3) The attribution of changes in UHII to that of urban and rural LST indicated that it is necessary to quantify the change of LST in both urban and rural areas to fully quantify the impact of urbanization on UHI effect.

Study of the Urban Heat Island (UHI) Using Remote Sensing Data/Techniques: A Systematic Review

Urban Heat Islands (UHI) consist of the occurrence of higher temperatures in urbanized areas when compared to rural areas. During the warmer seasons, this effect can lead to thermal discomfort, higher energy consumption, and aggravated pollution effects. The application of Remote Sensing (RS) data/techniques using thermal sensors onboard satellites, drones, or aircraft, allow for the estimation of Land Surface Temperature (LST). This article presents a systematic review of publications in Scopus and Web of Science (WOS) on UHI analysis using RS data/techniques and LST, from 2000 to 2020. The selection of articles considered keywords, title, abstract, and when deemed necessary, the full text. The process was conducted by two independent researchers and 579 articles, published in English, were selected. Qualitative and quantitative analyses were performed. Cfa climate areas are the most represented, as the Northern Hemisphere concentrates the most studied areas, especially in Asia (69.94%); Landsat products were the most applied to estimates LST (68.39%) and LULC (55.96%); ArcGIS (30.74%) was most used software for data treatment, and correlation (38.69%) was the most applied statistic technique. There is an increasing number of publications, especially from 2016, and the transversality of UHI studies corroborates the relevance of this topic.

Defining Heatwaves with Respect to Human Biometeorology. The Case of Attica Region, Greece

To date, due to climate change, heatwaves are more frequent, with greater intensity and duration resulting in deleterious impacts on human health. To be able to manage heatwaves and quantify the impacts on human health, it is crucial to define them and implement policy preventive measures. However, heatwaves are relative to the climate of a location: The same meteorological conditions can constitute a heatwave in one place but not in another. Due to different climatic conditions, social characteristics, and adaptation, heatwaves should be defined on a local scale, which poses difficulties when it comes to comparison of different definitions. The aim of the present study is to define heatwaves, implementing robust statistical analysis for three different indicators (temperature, physiological equivalent temperature (PET), and universal thermal climate index (UTCI)) for three causes of mortality (i.e., cardiological and respiratory mortality and cardiorespiratory mortality) using Attica (Greece) as a case study. Our results define a heatwave for Attica as a period of at least 3 days when the mean temperature is higher than the 97.5th percentile. Afterwards, we encapsulate the harvesting effect by implementing robust statistical analysis, using the Superposed Epoch analysis. Consequently, quantifying heatwaves is crucial so as to create early warning systems and prevent avoidable mortality.

Including Urban Heat Island in Bioclimatic Early-Design Phases: A Simplified Methodology and Sample Applications

Urban heat island and urban-driven climate variations are recognized issues and may considerably affect the local climatic potential of free-running technologies. Nevertheless, green design and bioclimatic early-design analyses are generally based on typical rural climate data, without including urban effects. This paper aims to define a simple approach to considering urban shapes and expected effects on local bioclimatic potential indicators to support early-design choices. Furthermore, the proposed approach is based on simplifying urban shapes to simplify analyses in early-design phases. The proposed approach was applied to a sample location (Turin, temperate climate) and five other climate conditions representative of Eurasian climates. The results show that the inclusion of the urban climate dimension considerably reduced rural HDD (heating degree-days) from 10% to 30% and increased CDD (cooling degree-days) from 70% to 95%. The results reveal the importance of including the urban climate dimension in early-design phases, such as building programming in which specific design actions are not yet defined, to support the correct definition of early-design bioclimatic analyses.

Temperature of Paved Streets in Urban Mockups and Its Implication of Reflective Cool Pavements

In summer, urban heat islands increase building cooling demands, aggravate air pollution, and cause heat-related illnesses. As a mitigation strategy, reflective cool pavements have been deemed an effective measure to decrease the temperature in urban areas. However, the reflection of paved streets in an urban area will be different from that in an open area. It remains unknown which fraction of paved streets needs to be cooled upmost, and if increasing the albedo of paved streets can effectively reduce their temperature. This study measured the skin temperature of two urban mockups, of which one contained white streets and the other, gray streets. The streets were orientated at different strikes. It was found that in summer the East-West street was hotter than both the cross street and the South-North street. At nighttime, the heat released from building blocks kept the paved street about 0.2 °C hotter than paved areas in open spaces. It was also found that street orientation controlled the skin temperature of an urban street while the sky view factor (or building height and street width) acted in a secondary role only. Increasing the albedo of the paved street in an urban canyon effectively reduced the skin temperature of the street. Reflective pavements should be built preferentially on East-West streets and the cross streets.

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.

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.

Satellite-based data driven quantification of pluvial floods over Europe under future climatic and socioeconomic changes

Flooding is one of the major threats jeopardizing lives and properties of the people, and its risk is expected to increase remarkably under changing climatic and socioeconomic conditions. Yet, future flood risk has not been well studied due primarily to a limited availability of detailed and consistent data on future vulnerability components and the computationally expensive continental flood modeling. Here we perform a top-down data driven flood risk assessment for 20-, 30-, 50- and 100-year return periods over Europe at the continental, regional and national levels for the late 21st century. To account for the impact of changes in both climatic and socioeconomic conditions on floods, the Shared Socioeconomic Pathways (SSPs) are merged with Representative Concentration Pathways (RCPs), integrating hazard and several social, economic and agricultural exposure-vulnerability proxy indicators. Our results show a ubiquitous drastic increase up to 87% in future flood risks of different return periods over Europe, with eastern and southern regions experiencing the highest risk increase. A fossil-fuel based development in the future would lead to 14-15% higher flood risk compared to a sustainable development, which goes up to 23% in north Europe. The amplified future flood risk is predominantly driven by climate change, although with a large uncertainty, rather than socioeconomic drivers.

Fine-scale mapping of an evidence-based heat health risk index for high-density cities: Hong Kong as a case study

The most recent extreme heat recorded in Europe re-alerts the world to the threat of heat stress. Future extreme heat events are reported to be more frequent, long-lasting, and intense. The intense exposure to hot temperatures can cause an excess of heat-related deaths, leading to an increasing risk of heat-related health. In reducing Heat Health Risk (HHR), the use of fine-scale evidence-based mapping of heat-related health risk index (HHRI) and its underlying contributors is essential for policy-making and site-specific action plans. However, its use is still considered to be at an early stage, especially in high-density cities like Hong Kong. This study conducted a spatially explicit assessment of HHR in Hong Kong and constructed a HHRI based on indicators categorized through Principle Component Analysis (PCA) into four meaningful components representing social/language, social isolation, socioeconomic, and urbanization/environmental risks. The applicability of the index was validated against heat-related mortality data at the community level. The community-level maps of HHRI and its subcomponents revealed that portions of Kowloon Peninsula had always suffered exceptionally high HHR ten years ago and after, but the hot spots and problematic communities experienced displacement and the dominant underlying factors of their HHR also varied. Results also showed that HHRI correlated fairly well with the heat-related deaths ratio (R² = 0.60) at the community level for most of Hong Kong (62.33% of all communities that contain 81.69% of total population). Our analysis results helped generate an evidence-based index to assess HHR in high-density cities like Hong Kong and provided fine-scale maps of the index and its subcomponents, with the aim of benefiting site-specific policy making and optimizing the existing action plans.

Spatial patterns of health vulnerability to heatwaves in Vietnam

The increasing frequency and intensity of heat events have weighty impacts on public health in Vietnam, but their effects vary across regions. In this study, we have applied a vulnerability assessment framework (VAF) to systematically assess the spatial pattern of health vulnerability to heatwaves in Vietnam. The VAF was computed as the function of three dimensions: exposure, sensitivity, and adaptive capacity, with the indicators for each dimension derived from the relevant literature, consultation with experts, and available data. An analytic hierarchy process (AHP) was used to determine the weight of indicators. Each province in Vietnam's vulnerability to the health impacts of heatwaves was evaluated by applying the vulnerability index, computed using 13 indicators (sensitivity index, 9; adaptive capacity index, 3; and exposure index, 1). As a result of this analysis, this study has identified heatwave vulnerability 'hotspots', primarily in the Southeast, Central Highlands, and South Central Coast of Vietnam. However, these hotspots are not necessarily the same as the area most vulnerable to climate change, because some areas that are more sensitive to heatwaves may have a higher capacity to adapt to them due to a host of factors including their population characteristics (e.g. rates of the elderly or children), socio-economic and geographical conditions, and the availability of air-conditioners. This kind of information, provided by the vulnerability index framework, allows policymakers to determine how to more efficiently allocate resources and devise appropriate interventions to minimise the impact of heatwaves with strategies tailored to each region of Vietnam.

Identifying Urban Flood Regulation Priority Areas in Beijing Based on an Ecosystem Services Approach

Climate change and rapid urbanization have severe impacts on urban flood regulation ecosystem services (UFRES). Quantifying the UFRES has attracted increasing attention for urban sustainable development. However, few studies have focused on how to identify urban flood regulation priority areas. In this study, we simulated urban surface runoff by using the soil conservation services-curve number model, and quantified UFRES supply and demand by using relative indicators (i.e., runoff reduction ratio and urban vulnerability) at the subdistrict scale in Beijing, China. Then, an urban flood regulation priority index was developed by integrating UFRES demand and supply, and further used to identify priority areas. The results show that the mean runoff reduction ratio in Beijing decreased from 38.70% (for a 1-year rainfall return period) to 24.74% (for a 100-year rainfall return period). Subdistricts with low UFRES supply were mainly located in the urban central area and the southeastern zone, while subdistricts with high UFRES demand were mainly located in the urban central region. Meanwhile, places with high priority for flood regulation were mainly located in the inner city, and low priority areas were mainly located in northwestern, southwestern, and northeastern Beijing. Our results also imply that the urban flood regulation priority index is an effective indicator to identify urban flood regulation priority areas. These findings could provide urban planners with a comprehensive understanding of UFRES and scientific guidance to improve them.

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.

Wearable sensors for personal temperature exposure assessments: A comparative study

The impacts of heat on human health has sparked research on different approaches to measure, map, and predict heat exposure at more accurate and precise spatiotemporal scales. Personal heat sensor studies rely on small sensors that can continuously measure ambient temperatures as individuals move through time and space. The comparison between different types of sensors and sensor placements have yet to be fully researched. The objective of this study is to assess the validity of personal ambient temperature sensors. To accomplish this objective, we evaluated the performance of multiple low-cost wearable sensors (HOBOs, iButton Thermochrons, iButton Hygrochrons, and Kestrel DROP D3FW Fire) for measuring ambient temperature in a (1) field exposure study by varying the placement on human subjects and in a (2) field calibration study by co-locating sensors with fixed site weather station monitors. A secondary aim involved investigating consensus between validation metrics that can be used in future sensor comparison studies. Bland-Altman analysis, correlation coefficients, and index of agreement statistics were used to quantify the difference between sensor and weather station ambient temperature measurements. Results demonstrated significant differences in measured temperatures for sensors based on sensor type and placement on participants. Future research should account for the differences in personal ambient temperature readings based on sensor type and placement.

Assessing the Impact of Land Cover Changes on Surface Urban Heat Islands with High-Spatial-Resolution Imagery on a Local Scale: Workflow and Case Study

Low-altitude remote sensing platform has been increasingly applied to observing local thermal environments due to its obvious advantage in spatial resolution and apparent flexibility in data acquisition. However, there is a general lack of systematic analysis for land cover (LC) classification, surface urban heat island (SUHI), and their spatial and temporal change patterns. In this study, a workflow is presented to assess the LC’s impact on SUHI, based on the visible and thermal infrared images with high spatial resolution captured by an unmanned airship in the central area of the Sino-Singapore Guangzhou Knowledge City in 2012 and 2015. Then, the accuracy assessment of LC classification and land surface temperature (LST) retrieval are performed. Finally, the commonly-used indexes in the field of satellites are applied to analyzing the spatial and temporal changes in the SUHI pattern on a local scale. The results show that the supervised maximum likelihood algorithm can deliver satisfactory overall accuracy and Kappa coefficient for LC classification; the root mean square error of the retrieved LST can reach 1.87 °C. Moreover, the LST demonstrates greater consistency with land cover type (LCT) and more fluctuation within an LCT on a local scale than on an urban scale. The normalized LST classified by the mean and standard deviation (STD) is suitable for the high-spatial situation; however, the thermal field level and the corresponded STD multiple need to be judiciously selected. This study exhibits an effective pathway to assess SUHI pattern and its changes using high-spatial-resolution images on a local scale. It is also indicated that proper landscape composition, spatial configuration and materials on a local scale exert greater impacts on SUHI.

Multi-Temporal Effects of Urban Forms and Functions on Urban Heat Islands Based on Local Climate Zone Classification

Urban forms and functions have critical impacts on urban heat islands (UHIs). The concept of a “local climate zone” (LCZ) provides a standard and objective protocol for characterizing urban forms and functions, which has been used to link urban settings with UHIs. However, only a few structure types and surface cover properties are included under the same climate background or only one or two time scales are considered with a high spatial resolution. This study assesses multi-temporal land surface temperature (LST) characteristics across 18 different LCZ types in Beijing, China, from July 2017 to June 2018. A geographic information system-based method is employed to classify LCZs based on five morphological and coverage indicators derived from a city street map and Landsat images, and a spatiotemporal fusion model is adopted to generate hourly 100-m LSTs by blending Landsat, Moderate Resolution Imaging Spectroradiometer (MODIS), and FengYun-2F LSTs. Then, annual and diurnal cycle parameters and heat island and cool island (HI or CI) frequency are linked to LCZs at annual, seasonal, monthly, and diurnal scales. Results indicate that: (1) the warmest zones are compact and mid and low-rise built-up areas, while the coolest zones are water and vegetated types; (2) compact and open high-rise built-up areas and vegetated types have seasonal thermal patterns but with different causes; (3) diurnal temperature ranges are the highest for compact and large low-rise settings but the lowest for water and dense or scattered trees; and (4) HIs are the most frequent summertime and daytime events, while CIs occur primarily during winter days, making them more or less frequent for open or compact and high- or low-rise built-up areas. Overall, the distinguishable LSTs or UHIs between LCZs are closely associated with the structure and coverage properties. Factors such as geolocation, climate, and layout also interfere with the thermal behavior. This study provides comprehensive information on how different urban forms and functions are related to LST variations at different time scales, which supports urban thermal regulation through urban design.

Mapping heat-related health risks of elderly citizens in mountainous area: A case study of Chongqing, China

Heat wave becomes a leading cause of weather-related illness and death across the world under the background of climate change, urban heat island, and population ageing. Heat health risk assessment is an important starting point for heat-related morbidity and mortality reduction within the risk governance framework. Chongqing, a mountainous municipality with a fast rate of population ageing in China, was selected as a case study for mapping the heat health risk of the elderly population at a raster scale. The results indicated that the high heat hazard and human exposure areas were mainly distributed in the metropolitan areas, which largely resulted in high heat health risk in the urban areas. However, the high heat vulnerability pixels were mainly concentrated at the remote mountainous regions which have broken terrains and low socioeconomic statuses. Compared with traditional general heat risk indicator, this new model can provide more targeted spatial information to decision makers, and is helpful to improve the flexibility and comparability of heat risk assessment tool. Furthermore, this new model is particularly valuable for quantifying heat health risk in developing countries with limited open access data.

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.

The footprint of urban heat island effect in 302 Chinese cities: Temporal trends and associated factors

The urban heat island (UHI) effect has been a concern for decades due its adverse influence on energy consumption, air and water quality, and, most importantly, the health of urban dwellers. Researchers have paid much attention to the magnitude of the UHI effect, but ignored its spatial extent (i.e. footprint) which is another important aspect of the UHI effect. In this study, we systematically analyzed the footprint of surface UHI (SUHI) effect in 302 Chinese cities, especially temporal trends of the footprint, by using multi-source remote sensing data. The footprint of SUHI effect (FP) was estimated by the Gaussian surface, and its temporal trend was examined by the Mann-Kendal and the Sen's slope estimator non-parametric tests. We found the FP showed evident diurnal (daytime > nighttime), seasonal (summer > winter) and inter-city (big cities > small and medium-sized cities) differences. During the period 2003-2016, over 80% of the 302 cities exhibited increasing trends of the FP in annual days and summer days, and the increasing trends were statistically significant (p < 0.05) in about half of these cities. In the nights, the FP increased in more than 70% of the cities, and about one-third of the 302 cities experienced significantly increasing trends of the FP. On average, the annual daytime and annual nighttime FPs increased at a rate of 5.0% per year and 3.8% per year, respectively. More importantly, the correlation analysis indicated that the increase of anthropogenic heat emissions and the decrease of vegetation activities and surface albedos should take lead responsibility for the expansion of the FP in the urbanization process. These results reveal that the spatial extent of heat island effect has expanded significantly in numerous Chinese cities, and this increasing trend will be sustained in the coming years if no more effective measures are carried out.

Quantification and evaluation of intra-urban heat-stress variability in Seoul, Korea

This study quantifies heat-stress hazard (air temperature), vulnerability (heat vulnerability index and age score), and risk (heat-related mortality) on the district scale in Seoul, Korea, for a comprehensive heat-stress impact assessment. Moreover, the heat-stress impact assessment is evaluated by checking the spatial consistency between heat-stress hazard, vulnerability, and risk, which was rarely done before. We applied numerical and geo-empirical models to simulate the spatial pattern of heat-stress hazard. For heat-stress vulnerability, we used demographic and socioeconomic factors. Heat-related mortality was estimated based on an event-based heat-stress risk analysis. Results are that heat-stress hazard, vulnerability, and risk are spatially variable in Seoul. The highest heat-stress hazard was detected in the districts Mapo, Yeongdeungpo, and Yangcheon, the highest vulnerability in Jongno and the highest risk in Jongno and Yangcheon. The different components (heat-stress hazard, vulnerability, and risk) and variables (heat vulnerability index and percentage of seniors) showed different spatial patterns. Knowledge about the causes of higher heat-stress risk, either the hazard or vulnerability, is helpful to design tailored adaptation measures that focus on the reduction of thermal loads or on the preparation of the vulnerable population. The evaluation showed that heat-stress vulnerability and hazard explain the spatial pattern of risk only partly. This highlights the need to evaluate heat-stress impact assessment systems to produce reliable urban heat-stress maps.

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.

Spatially explicit assessment of heat health risk by using multi-sensor remote sensing images and socioeconomic data in Yangtze River Delta, China

BACKGROUND

The increase in the frequency and intensity of extreme heat events, which are potentially associated with climate change in the near future, highlights the importance of heat health risk assessment, a significant reference for heat-related death reduction and intervention. However, a spatiotemporal mismatch exists between gridded heat hazard and human exposure in risk assessment, which hinders the identification of high-risk areas at finer scales.

METHODS

A human settlement index integrated by nighttime light images, enhanced vegetation index, and digital elevation model data was utilized to assess the human exposure at high spatial resolution. Heat hazard and vulnerability index were generated by land surface temperature and demographic and socioeconomic census data, respectively. Spatially explicit assessment of heat health risk and its driving factors was conducted in the Yangtze River Delta (YRD), east China at 250 m pixel level.

RESULTS

High-risk areas were mainly distributed in the urbanized areas of YRD, which were mostly driven by high human exposure and heat hazard index. In some less-urbanized cities and suburban and rural areas of mega-cities, the heat health risks are in second priority. The risks in some less-developed areas were high despite the low human exposure index because of high heat hazard and vulnerability index.

CONCLUSIONS

This study illustrated a methodology for identifying high-risk areas by combining freely available multi-source data. Highly urbanized areas were considered hotspots of high heat health risks, which were largely driven by the increasing urban heat island effects and population density in urban areas. Repercussions of overheating were weakened due to the low social vulnerability in some central areas benefitting from the low proportion of sensitive population or the high level of socioeconomic development. By contrast, high social vulnerability intensifies heat health risks in some less-urbanized cities and suburban areas of mega-cities.

The Urban Heat Island: Implications for Health in a Changing Environment

PURPOSE OF REVIEW

The Urban Heat Island (UHI) is a well-studied phenomenon, whereby urban areas are generally warmer than surrounding suburban and rural areas. The most direct effect on health from the UHI is due to heat risk, which is exacerbated in urban areas, particularly during heat waves. However, there may be health benefits from warming during colder months. This review highlights recent attempts to quantitatively estimate the health impacts of the UHI and estimations of the health benefits of UHI mitigation measures.

RECENT FINDINGS

Climate change, increasing urbanisation and an ageing population in much of the world, is likely to increase the risks to health from the UHI, particularly from heat exposure. Studies have shown increased health risks in urban populations compared with rural or suburban populations in hot weather and a disproportionate impact on more vulnerable social groups. Estimations of the impacts of various mitigation techniques suggest that a range of measures could reduce health impacts from heat and bring other benefits to health and wellbeing. The impact of the UHI on heat-related health is significant, although often overlooked, particularly when considering future impacts associated with climate change. Multiple factors should be considered when designing mitigation measures in urban environments in order to maximise health benefits and avoid unintended negative effects.

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.

Effectiveness of rapid rail transit system in Beijing

The effectiveness of rapid rail transit system is analyzed using tools of complex network for the first time. We evaluated the effectiveness of the system in Beijing quantitatively from different perspectives, including descriptive statistics analysis, bridging property, centrality property, ability of connecting different part of the system and ability of disease spreading. The results showed that the public transport of Beijing does benefit from the rapid rail transit lines, and the benefit of different regions from RRTS is gradually decreased from the north to the south. The paper concluded with some policy suggestions regarding how to promote the system. This study offered significant insight that can help understand the public transportation better. The methodology can be easily applied to analyze other urban public systems, such as electricity grid, water system, to develop more livable cities.

Global and regional changes in exposure to extreme heat and the relative contributions of climate and population change

The frequency and intensity of extreme heat wave events have increased in the past several decades and are likely to continue to increase in the future under the influence of human-induced climate change. Exposure refers to people, property, systems, or other elements present in hazard zones that are thereby subject to potential losses. Exposure to extreme heat and changes therein are not just determined by climate changes but also population changes. Here we analyze output for three scenarios of greenhouse gas emissions and socio-economic growth to estimate future exposure change taking account of both climate and population factors. We find that for the higher emission scenario (RCP8.5-SSP3), the global exposure increases nearly 30-fold by 2100. The average exposure for Africa is over 118 times greater than it has been historically, while the exposure for Europe increases by only a factor of four. Importantly, in the absence of climate change, exposure is reduced by 75-95% globally and across all geographic regions, as compared with exposure under the high emission scenario. Under lower emission scenarios RCP4.5-SSP2 and RCP2.6-SSP1, the global exposure is reduced by 65% and 85% respectively, highlighting the efficacy of mitigation efforts in reducing exposure to extreme heat.

Spatially Explicit Mapping of Heat Health Risk Utilizing Environmental and Socioeconomic Data

Extreme heat events, a leading cause of weather-related fatality worldwide, are expected to intensify, last longer, and occur more frequently in the near future. In heat health risk assessments, a spatiotemporal mismatch usually exists between hazard (heat stress) data and exposure (population distribution) data. Such mismatch is present because demographic data are generally updated every couple of years and unavailable at the subcensus unit level, which hinders the ability to diagnose human risks. In the present work, a human settlement index based on multisensor remote sensing data, including nighttime light, vegetation index, and digital elevation model data, was used for heat exposure assessment on a per-pixel basis. Moreover, the nighttime urban heat island effect was considered in heat hazard assessment. The heat-related health risk was spatially explicitly assessed and mapped at the 250 m × 250 m pixel level across Zhejiang Province in eastern China. The results showed that the accumulated heat risk estimates and the heat-related deaths were significantly correlated at the county level (Spearman's correlation coefficient = 0.76, P ≤ 0.01). Our analysis introduced a spatially specific methodology for the risk mapping of heat-related health outcomes, which is useful for decision support in preparation and mitigation of heat-related risk and potential adaptation.

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

Climate change will worsen the high levels of urban vulnerability in Latin American cities due to specific environmental stressors. Some impacts of climate change, such as high temperatures in urban environments, have not yet been addressed through adaptation strategies, which are based on poorly supported data. These impacts remain outside the scope of urban planning. New spatially explicit approaches that identify highly vulnerable urban areas and include specific adaptation requirements are needed in current urban planning practices to cope with heat hazards. In this paper, a heat vulnerability index is proposed for Santiago, Chile. The index was created using a GIS-based spatial information system and was constructed from spatially explicit indexes for exposure, sensitivity and adaptive capacity levels derived from remote sensing data and socio-economic information assessed via principal component analysis (PCA). The objective of this study is to determine the levels of heat vulnerability at local scales by providing insights into these indexes at the intra city scale. The results reveal a spatial pattern of heat vulnerability with strong variations among individual spatial indexes. While exposure and adaptive capacities depict a clear spatial pattern, sensitivity follows a complex spatial distribution. These conditions change when examining PCA results, showing that sensitivity is more robust than exposure and adaptive capacity. These indexes can be used both for urban planning purposes and for proposing specific policies and measures that can help minimize heat hazards in highly dynamic urban areas. The proposed methodology can be applied to other Latin American cities to support policy making.

The Construction and Validation of the Heat Vulnerability Index, a Review

The occurrence of extreme heat and its adverse effects will be exacerbated with the trend of global warming. An increasing number of researchers have been working on aggregating multiple heat-related indicators to create composite indices for heat vulnerability assessments and have visualized the vulnerability through geographic information systems to provide references for reducing the adverse effects of extreme heat more effectively. This review includes 15 studies concerning heat vulnerability assessment. We have studied the indicators utilized and the methods adopted in these studies for the construction of the heat vulnerability index (HVI) and then further reviewed some of the studies that validated the HVI. We concluded that the HVI is useful for targeting the intervention of heat risk, and that heat-related health outcomes could be used to validate and optimize the HVI. In the future, more studies should be conducted to provide references for the selection of heat-related indicators and the determination of weight values of these indicators in the development of the HVI. Studies concerning the application of the HVI are also needed.