Including the urban heat island in spatial heat health risk assessment strategies: a case study for Birmingham, UK

Shared insights for heat health risk adaptation in metropolitan areas of developing countries

Global warming has led to a surge in heat health risks (HHRs), the impacts of which are particularly pronounced in metropolitan areas of developing countries. In the current study, six metropolitan areas - Beijing, China; Cairo, Egypt; Jakarta, Indonesia; Mumbai, India; Rio de Janeiro, Brazil; and Tehran, Iran - were selected as the study area to further differentiate the built-up landscapes by utilizing the concept of local climate zones. Moreover, we assessed the similarities and differences in HHR associated with the landscape. Results revealed a 30.67% higher HHR in compact built-up landscapes than in the open built-up type. Urban green spaces played an effective but differentiated role in mitigating HHR. That is, low vegetation in urbanized areas and trees in suburban areas significantly mitigated HHR. Collectively, our findings emphasize the role of effective planning and management in addressing HHR and provide empirical support for implementing HHR mitigation and adaptation strategies.

Heat exposure assessment based on high-resolution spatio-temporal data of population dynamics and temperature variations

Urban heat waves pose a significant risk to the health and safety of city dwellers, with urbanization potentially amplifying the health impact of extreme heat. Accurate assessments of population heat exposure hinge on the interplay between temperature, population spatial dynamics, and the epidemiological effects of temperature on health. Yet, many past studies have over-simplified the matter by assuming static populations, leading to substantial inaccuracies in heat exposure assessments. To address these issues, this study integrates dynamic population data, fluctuating temperature, and the exposure-response relationship between temperature and health to construct an advanced heat exposure assessment framework predicated on a population dynamic model. We analyzed urban heat island characteristics, population dynamics, and heat exposure during heat wave conditions in Beijing, a major city in China. Our findings highlight significant intra-day population movement between urban and suburban areas during heat wave conditions, with spatial population flow patterns showing clear scale-dependent characteristics. These population flow dynamics intensify heat exposure levels, and the disparity between dynamic population-weighted temperature and average temperature is most pronounced at night. Our research provides a more comprehensive understanding of real urban population heat exposure levels and can furnish city administrators with more scientifically rigorous evidence.

Diurnal urban heat risk assessment using extreme air temperatures and real-time population data in Seoul

Previous heat risk assessments have limitations in obtaining accurate heat hazard sources and capturing population distributions, which change over time. This study proposes a diurnal heat risk assessment framework incorporating spatiotemporal air temperature and real-time population data. Daytime and nighttime heat risk maps were generated using hazard, exposure, and vulnerability components in Seoul during the summer of 2018. The hazard was derived from the daily extreme air temperatures obtained using the stacking machine learning model. Exposure was calculated using de facto population density, and vulnerability was assessed using demographic and socioeconomic indicators. The resulting maps revealed distinct diurnal spatial patterns, with high-risk areas in the urban core during the day and dispersed at night. Daytime heat risk was strongly correlated with heat-related illness ratios (R = 0.8) and accurately captured temporal fluctuations in heat-related illness incidence. The proposed framework can guide site-specific adaptation and response plans for dynamic urban heat events.

Evaluation of UTFVI index effect on climate change in terms of urbanization

Urban heat island density and occurrence are closely related to land use/land cover and land surface temperature variation. The effect of UHI can be described quantitatively with the urban thermal area variance index. This study aims to evaluate the UHI effect of the city of Samsun with the UTFVI index. LST data from 2000 ETM + and 2020 OLI/TIRS Landsat images were used to analyze UHI. The results showed that the UHI effect increased in Samsun's coastline band in 20 years. As a result of the field analysis made from the UTFVI maps created, in 20 years, 84% decrease in the none slice, 104% increase in the weak slice, 10% decrease in the middle slice, 15% decrease in the strong slice, 8% increase in the stronger slice, and 179% increase in the strongest slice are observed. The slice with the most intense increase is in the strongest slice and reveals the UHI effect.

Spatiotemporal analysis of the surface urban heat island (SUHI), air pollution and disease pattern: an applied study on the city of Granada (Spain)

There is worldwide concern about how climate change -which involves rising temperatures- may increase the risk of contracting and developing diseases, reducing the quality of life. This study provides new research that takes into account parameters such as land surface temperature (LST), surface urban heat island (SUHI), urban hotspot (UHS), air pollution (SO₂, NO₂, CO, O₃ and aerosols), the normalized difference vegetation index (NDVI), the normalized difference building index (NDBI) and the proportion of vegetation (PV) that allows evaluating environmental quality and establishes mitigation measures in future urban developments that could improve the quality of life of a given population. With the help of Sentinel 3 and 5P satellite images, we studied these variables in the context of Granada (Spain) during the year 2021 to assess how they may affect the risk of developing diseases (stomach, colorectal, lung, prostate and bladder cancer, dementia, cerebrovascular disease, liver disease and suicide). The results, corroborated by the statistical analysis using the Data Panel technique, indicate that the variables LST, SUHI and daytime UHS, NO₂, SO₂ and NDBI have important positive correlations above 99% (p value: 0.000) with an excess risk of developing these diseases. Hence, the importance of this study for the formulation of healthy policies in cities and future research that minimizes the excess risk of diseases.

Spatio-temporal analysis of urban heat island (UHI) and its effect on urban ecology: The case of Mekelle city, Northern Ethiopia

The bio-geophysical effects of land cover classes are considered to be an important factor in land surface temperature variations between urban and suburban areas. This means that major cities are significantly warmer than surrounding suburban or rural areas, which is known as the Urban Heat Island (UHI) effect. The aim of this study was to assess and analyze the spatiotemporal variation, correlation and impact of UHIs on Mekelle city (1990-2020) using remote sensing techniques. The study's primary objective was accomplished using the a number of techniques, including the extraction of LULC classes, estimation of the seasonal LSTs, assessment of UHI and UTFVI, and showing the relationship between LULC and LST as well as the interactions between UHI, UTFVI, and urban LULC classes. By analyzing TIRs/OLI thermal band data after calibrating uncertainty in the images and validating it using the concept of theoretical relationships and least squares fitting method, estimates of local LST, UHI (both in Mekelle and periphery rural areas), and UTFVI were obtained. The result of standard multiple regression models showed that impervious urban land surface, built-up areas, and dry bare soil highly contribute and influence variation at LST intensity caused for the formation of UHI in the study area. The result showed that the maximum UHI value in Mekelle city was 2.73 °C during the dry season in 1990. It decreased slightly to 2.53 °C in 2000 and then increased regularly to 2.83 °C and 2.98 °C in 2010 and 2020, respectively. To determine the city's UHI status in comparison to eight selected peripheral suburban areas, a trend analysis has been done. The UHI intensity of Mekelle city was higher relatively to that of most of the periphery suburban districts, particularly in 2020 (both dry and rainy seasons); this could be due to the city's explosive growth. It's worth noting that the research area affected by the urban heat island effect has grown over time, and as a result, the study area also has severe microclimate conditions that primarily damage the quality of urban life and create the worst conditions for thermal discomfort. The results of this study provide major conceptual understandings of how improper distribution and use of urban land affects the urban environment and fuels the creation of the UHI and thermal discomfort phenomena. Hence policy makers and urban planners should consider the effects of LST and UHI and integrate UHI comprehensive mitigation strategies with urban development patterns, and current and projected local climate changes in order to create sustainable urban environments, cities, and communities. In conclusion, compared to the conventional method, satellite remote sensing provides a faster and more efficient method for researching LST and UHI.

The influence of heat and cold waves on mortality in Russian subarctic cities with varying climates

Publications on ambient temperature-related mortality among Arctic or subarctic populations are extremely rare. While circumpolar areas cover large portions of several European countries, Canada, and the USA, the population of these territories is relatively small, and the data needed for statistical analysis of the health impacts of extreme temperature events are frequently insufficient. This study utilizes standard time series regression techniques to estimate relative increases in cause- and age-specific daily mortality rates during heat waves and cold spells in four Russian cities with a subarctic climate. The statistical significance of the obtained effect estimates tends to be greater in the continental climate than in the marine climate. A small meta-analysis was built around the obtained site-specific health effects. The effects were homogeneous and calculated for the selected weather-dependent health outcomes. The relative risks of mortality due to ischemic heart disease, all diseases of the circulatory system, and all non-accidental causes during cold spells in the age group ≥ 65 years were 1.20 (95% CI: 1.11-1.29), 1.14 (1.08-1.20), and 1.12 (1.07-1.17), respectively. Cold spells were more harmful to the health of the residents of Murmansk, Archangelsk, and Magadan than heat waves, and only in Yakutsk, heat waves were more dangerous. The results of this study can help the public health authorities develop specific measures for the prevention of excess deaths during cold spells and heat waves in the exposed subarctic populations.

Mapping the gaps between cooling benefits of urban greenspace and population heat vulnerability

We provide a novel method to assess the heat mitigation impacts of greenspace though studying the mechanisms of ecosystems responsible for benefits and connecting them to heat exposure metrics. We demonstrate how the ecosystem services framework can be integrated into current practices of environmental health research using supply/demand state-of-the-art methods of ecological modeling of urban greenspace. We compared the supply of cooling ecosystem services in Boston measured through an indicator of high resolution evapotranspiration modeling, with the demand for benefits from cooling measured as a heat exposure risk score based on exposure, hazard and population characteristics. The resulting evapotranspiration indicator follows a pattern similar to conventional greenspace indicators based on vegetation abundance, except in warmer areas such as those with higher levels of impervious surface. We identified demand-supply mismatch areas across the city of Boston, some coinciding with affordable housing complexes and long term care facilities. This novel ES-framework provides cross-disciplinary methods to prioritize urban areas where greenspace interventions can have the most impact based on heat-related demand.

Categorizing and Harmonizing Natural, Technological, and Socio-Economic Perils Following the Catastrophe Modeling Paradigm

The literature on probabilistic hazard and risk assessment shows a rich and wide variety of modeling strategies tailored to specific perils. On one hand, catastrophe (CAT) modeling, a recent professional and scientific discipline, provides a general structure for the quantification of natural (e.g., geological, hydrological, meteorological) and man-made (e.g., terrorist, cyber) catastrophes. On the other hand, peril characteristics and related processes have yet to be categorized and harmonized to enable adequate comparison, limit silo effects, and simplify the implementation of emerging risks. We reviewed the literature for more than 20 perils from the natural, technological, and socio-economic systems to categorize them by following the CAT modeling hazard pipeline: (1) event source → (2) size distribution → (3) intensity footprint. We defined the following categorizations, which are applicable to any type of peril, specifically: (1) point/line/area/track/diffuse source, (2) discrete event/continuous flow, and (3) spatial diffusion (static)/threshold (passive)/sustained propagation (dynamic). We then harmonized the various hazard processes using energy as the common metric, noting that the hazard pipeline's underlying physical process consists of some energy being transferred from an energy stock (the source), via an event, to the environment (the footprint).

Impact of urban land use and land cover change on urban heat island and urban thermal comfort level: a case study of Addis Ababa City, Ethiopia

The increase in the urban heat island is caused by the replacement of vegetation cover by impervious surfaces. As the population of Addis Ababa City has increased dramatically, the vegetation cover and other land cover classes have been converted into built-up areas. This study attempted to examine the relationship between urban heat islands and urban thermal comfort (UTCL) and land use and land cover (LULC) change using geospatial technologies in Addis Ababa City, Ethiopia. Landsat TM 1991, Landsat ETM + 2005, and Landsat OLI/TIRS 2021 data were used in this study. During the study period, LULC change, land surface temperature (LST), and urban heat island were calculated using the multispectral and thermal infrared bands (1991-2021). Results revealed that the built-up area in 1991 was 96.6 km² (18.3%), and increased to 165.4 km² (31.4%) and 277.2 km² (52.6%) by 2005 and 2021, respectively. In contrast, agriculture and vegetation land cover classes were declined by 66.8 km² and 25.7 km², respectively between 1991 and 2021. Rapid conversion of LULC change increases the mean LST of Addis Ababa City by 8.3 °C over the last three decades. According to the results, a high LST was recorded over built-up regions and areas with little vegetative cover. Furthermore, the central areas of the study area suffered a greater UHI effect than the surrounding areas. The results of the urban thermal field variance index (UTFVI) revealed that the UHI varies greatly across the city. Strong, stronger, and strongest urban heat islands dominated the central, southwestern, and southeastern suburbans of the study area, respectively. The excellent comfort level has declined from 16.3 km² (3.1%) in 1991 to 12.1 km² (2.3%) in 2021. The study proposed that local community awareness needs to be raised for environmental conservation through the establishment of urban green spaces that reduce UHI and increase comfort in Addis Ababa City.

Economic burden of premature deaths attributable to non-optimum temperatures in Italy: A nationwide time-series analysis from 2015 to 2019

BACKGROUND

Human beings and society are experiencing substantial consequences caused by non-optimum temperatures. However, limited studies have assessed the economic burden of premature deaths attributable to non-optimum temperatures.

OBJECTIVES

To characterize the association between daily mean temperature and the economic burden of premature deaths.

METHODS

A total of 3 228 098 deaths were identified from a national mortality dataset in Italy during 2015 and 2019. We used the value of statistical life to quantify the economic losses of premature death. A two-stage time-series analysis was performed to evaluate the economic losses of premature deaths associated with non-optimum temperatures. Attributable burden for non-optimum temperatures compared with minimum risk temperature were estimated. Potential effect modifiers were further explored.

RESULTS

From 2015 to 2019, the economic loss of premature deaths due to non-optimum temperatures was $525.52 billion (95% CI: $461.84-$580.80 billion), with the attributable fraction of 5.74% (95% CI: 5.04%-6.34%). Attributable economic burden was largely due to moderate cold temperatures ($309.54 billion, 95% CI: $249.49-$357.34 billion). A higher economic burden was observed for people above the age of 65, accounting for 75.97% ($452.42, 95%CI: $406.97-$488.76 billion) of the total economic burden. In particular, higher fractions attributable to heat temperatures were observed for provinces with the lowest level of GDP per capita but the highest level of urbanization.

DISCUSSION

This study shows a considerable economic burden of premature deaths attributed to non-optimum temperatures. These figures can help inform tailored prevention to tackle the large economic burden imposed by non-optimum temperatures.

Assessment of urban thermal field variance index and thermal comfort level of Addis Ababa metropolitan city, Ethiopia

Land use land cover (LULC) conversion around urban areas is the root cause for the increasing trend of land surface temperature (LST) in many cities. The increase in LST is driven by the replacement of vegetation cover and other LULC by impervious surface. This study is aimed to assess the extent of urban thermal field variance index (UTFVI) and thermal comfort level of Addis Ababa city using geospatial techniques and linear regression model. Landsat image of 1990 TM, 2000 of ETM+ and 2020 of OLI/TIRS are used to analyze LST and Urban Heat Islands (UHI) for assessing UTFVI and urban thermal comfort level. The results showed that the UHI over Addis Ababa city is substantial increased over the past decades. The results reveled that LST has increased by 7.9 °C due to decline of vegetation cover and expansion of built-up area. Results show that about 225 km² (42.7%) is excellent comfort for urban resident while about 241.4 km² (45.8%) is categorized as worst ecological evaluation index, which results discomfort to the city dwellers. The key findings of from this study are crucial for informing city administrators and urban planners to reduce urban heat islands by investing on urban green areas and open spaces.

Risk Factors for Severe and Fatal Heat-Related Illness in UK Dogs—A VetCompass Study

Heat-related illness (HRI) is predicted to increase in dogs due to rising global temperatures. This study evaluated retrospective VetCompass veterinary clinical records to explore geographical variability and ambient conditions associated with HRI events in UK dogs, and report the intrinsic (canine) and extrinsic (location, trigger, ambient weather) risk factors for severe disease and fatal outcome in dogs affected by HRI. Dogs living in London had the greatest odds for developing HRI compared with dogs living in the North West (OR 1.9, 95% CI 1.31–2.74). The median ambient temperature on days of HRI events was 16.9 °C. For dogs with HRI, age, bodyweight and trigger were risk factors associated with severe disease. Age, skull shape and clinical grade of HRI presentation were associated with a fatal outcome. Whilst the majority of HRI events overall were triggered by exertion, the risk of severe disease was greater in situations where dogs could not escape the heat source (vehicular confinement), and the risk of death in HRI cases was greater for those dogs with reduced capacity to thermoregulate (older and brachycephalic dogs). These results highlight the need for better owner awareness of the factors that increase the risk of severe and fatal HRI, as a first stage in protecting canine welfare in the face of rising global temperatures.

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.

Heterogeneous Urban Thermal Contribution of Functional Construction Land Zones: A Case Study in Shenzhen, China

Anthropogenic interferences through various intensive social-economic activities within construction land have induced and strengthened the Urban Heat Island (UHI) effects in global cities. Focused on the relative heat effect produced by different social-economic functions, this study established a general framework for functional construction land zones (FCLZs) mapping and investigated their heterogeneous contribution to the urban thermal environment, and then the thermal responses in FCLZs with 12 environmental indicators were analyzed. Taking Shenzhen as an example city, the results show that the total contribution and thermal effects within FCLZs are significantly different. Specifically, the FCLZs contribution to UHI regions highly exceeds the corresponding proportions of their area. The median warming capacity order of FCLZs is: Manufacture function (3.99 °C) > Warehousing and logistics function (3.69 °C) > Street and transportation function (3.61 °C) > Business services function (3.06 °C) > Administration and public services function (2.54 °C) > Green spaces and squares function (2.40 °C) > Residential function (2.21 °C). Both difference and consistency coexist in the responses of differential surface temperature (DST) to environmental indicators in FCLZs. The thermal responses of DST to biophysical and building indicators in groups of FCLZs are approximately consistent linear relationships with different intercepts, while the saturation effects shown in location and social-economic indicators indicate that distance and social-economic development control UHI effects in a non-linear way. This study could extend the understanding of urban thermal warming mechanisms and help to scientifically adjust environmental indicators in urban planning.

Mapping Heat-Health Vulnerability Based on Remote Sensing: A Case Study in Karachi

As a result of global climate change, the frequency and intensity of heat waves have increased significantly. According to the World Meteorological Organization (WMO), extreme temperatures in southwestern Pakistan have exceeded 54 °C in successive years. The identification and assessment of heat-health vulnerability (HHV) are important for controlling heat-related diseases and mortality. At present, heat waves have many definitions. To better describe the heat wave mortality risk, we redefine the heat wave by regarding the most frequent temperature (MFT) as the minimum temperature threshold for HHV for the first time. In addition, different indicators that serve as relevant evaluation factors of exposure, sensitivity and adaptability are selected to conduct a kilometre-level HHV assessment. The hesitant analytic hierarchy process (H-AHP) method is used to evaluate each index weight. Finally, we incorporate the weights into the data layers to establish the final HHV assessment model. The vulnerability in the study area is divided into five levels, high, middle-high, medium, middle-low and low, with proportions of 3.06%, 46.55%, 41.85%, 8.53% and 0%, respectively. Health facilities and urbanization were found to provide advantages for vulnerability reduction. Our study improved the resolution to describe the spatial heterogeneity of HHV, which provided a reference for more detailed model construction. It can help local government formulate more targeted control measures to reduce morbidity and mortality during heat waves.

Sensitivities of heat-wave mortality projections: Moving towards stochastic model assumptions

This paper analyses the probabilistic future behaviour of heat-waves (HWs) in the city of Madrid in the twenty-first century, using maximum daily temperatures from twenty-one climate circulation models under two representative concentration pathways (RCP 8.5 & RCP 4.5). HWs are modelled considering three factors: number per annum, duration and intensity, characterised by three stochastic processes: Poisson, Gamma and truncated Gaussian, respectively. Potential correlations between these processes are also considered. The probabilistic temperature behaviour is combined with an epidemiological model with stochastic mortality risk following a generalized extreme value distribution (gev). The objective of this study is to obtain probability distributions of mortality and risk measures such as the mean value of the 5% of worst cases in the 21st century, in particular from 2025 to 2100. Estimates from stochastic models for characterising HWs and epidemiological impacts on human health can vary from one climate model to another, so relying on a single climate model can be problematic. For this reason, the calculations are carried out for 21 models and the average of the results is obtained. A sensitivity adaptation analysis is also performed. Under RCP 8.5 for 2100 for Madrid city a mean excess of 3.6 °C over the 38 °C temperature threshold is expected as the average of all models, with an expected attributable mortality of 1614 people, but these figures may be substantially exceeded in some cases if the highest-risk cases occur.

Precast Concrete Pavements of High Albedo to Achieve the Net “Zero-Emissions” Commitments

Pavements store heat, which is subsequently released into the atmosphere, heating the surrounding air. Therefore, this process contributes to climate change and global warming. For this reason, the use of high-solar-reflectance (albedo) pavements is seen as one of the potential mitigation methods for climate change. Concrete pavements have a much higher albedo than asphalt due to their light gray color compared with black pavements. Accordingly, the widespread utilization of highly reflective concrete pavements will improve local climate change mitigation. Nevertheless, concrete albedo slightly decreases over time because of weathering. Albedo and solar reflectance index (SRI) measurements were taken on actual precast concrete pavements made with different mixes. The methodology applied for this project is based on the comparison between the asphalt and concrete pavements’ reflectivity. Conventional concrete mix designs can provide cool pavements with SRI higher than 29. Replacement of black pavements by highly reflective concrete pavements appeared to be a cost-effective and easily implemented measure to combat climate change. Finally, multidisciplinary studies considering factors such as building materials’ albedo, among other mitigation measures, should be performed to provide more precise and reliable guidance to policymakers, stakeholders, decision makers and urban planners.

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.

Urban Green Infrastructure and Green Open Spaces: An Issue of Social Fairness in Times of COVID-19 Crisis

At the time of the restrictions and lockdown during the COVID-19 pandemic, it became apparent how difficult it is for city dwellers to adhere to the prescribed behavioural measures and the protective distance in densely built urban areas. Inner-city parks and green spaces were heavily used for recreational purposes and were thus periodically overcrowded. These observations highlight the need for green open spaces in urban areas, especially in exceptional situations regarding pandemics and climate-related heat periods. Green open spaces and greened buildings help cities and the population cope with the consequences of climate change and have a decisive positive effect on human health and well-being. This paper aims to outline which social issues are related to the availability of green infrastructure close to home and which health consequences need to be considered. The COVID-19 challenges could offer a chance and an opportunity to increase the resilience of cities and their inhabitants in various terms. A cross-disciplinary team of authors (public health, urban and landscape planning, landscaping and vegetation technologies science) describes and discusses challenges and opportunities that arise from this crisis for cities from an inter-disciplinary perspective, concluding that urban green infrastructure helps in two ways: to adapt to climate change and the challenges posed by COVID-19.

Disparities of weather type and geographical location in the impacts of temperature variability on cancer mortality: A multicity case-crossover study in Jiangsu Province, China

BACKGROUND

Considering the serious health burden caused by adverse weather events, increasing researches focused on the relationship between temperature variability (TV) and cause-specific mortality, but its association with cancer was not well explored. We aimed to investigate the impacts of TV on cancer mortality and examine the modifying effects of weather type and geographical location as well as other characteristics.

MATERIALS AND METHODS

Daily city-specific data of cancer deaths, mean temperature (Tmean), maximum and minimum temperatures (Tmax and Tmin), relative humidity (RH), rainfall, and air pollutants were collected during 2016-2017 in 13 cities in Jiangsu Province, China. TV_0-t was defined as the standard deviation of the daily Tmax and Tmin on the exposure 0-t days. A two-stage analysis was applied. First, a time-stratified case-crossover design was used to examine the odds ratio (OR) and attributable fraction of cancer mortality per 1 °C increase in TV by adjusting for potential confounders. Random effect meta-analysis was used to summarize the pooled ORs. Second, stratified analysis was performed for weather type, geographical location, demographics, and other city-level characteristics. The weather was defined as four types according to days during warm or cold season combined with high or low RH.

RESULTS

A total of 303670 cases were included in our study. Meta-analysis showed that the ORs of cancer mortality per 1 °C increase in TV_0-t significantly increased and peaked in TV_0-2 (OR=1.0098, 95% CI: 1.0039-1.0157). The attributable fraction of TV_0-2 on cancer mortality was 4.74%, accounting for 14395 deaths in the study period. Significant ORs of TV-related cancer mortality were found during the warm season combined with high RH and in the northern region of Jiangsu. Susceptible groups of TV-related cancer mortality were identified as female patients, patients aged 45-65 years, and those living in cities with lower per capita green area.

CONCLUSIONS

TV can significantly increase the risk of cancer mortality, especially during warm and humid days and in the northern region of Jiangsu. Findings are of great significance to formulate urban planning, resource allocation, and health intervention to prolong the life of cancer patients.

A novel methodology for epidemic risk assessment of COVID-19 outbreak

We propose a novel data-driven framework for assessing the a-priori epidemic risk of a geographical area and for identifying high-risk areas within a country. Our risk index is evaluated as a function of three different components: the hazard of the disease, the exposure of the area and the vulnerability of its inhabitants. As an application, we discuss the case of COVID-19 outbreak in Italy. We characterize each of the twenty Italian regions by using available historical data on air pollution, human mobility, winter temperature, housing concentration, health care density, population size and age. We find that the epidemic risk is higher in some of the Northern regions with respect to Central and Southern Italy. The corresponding risk index shows correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can help explaining why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto have suffered much more than the rest of the country. Although the COVID-19 outbreak started in both North (Lombardia) and Central Italy (Lazio) almost at the same time, when the first cases were officially certified at the beginning of 2020, the disease has spread faster and with heavier consequences in regions with higher epidemic risk. Our framework can be extended and tested on other epidemic data, such as those on seasonal flu, and applied to other countries. We also present a policy model connected with our methodology, which might help policy-makers to take informed decisions.

Using Citizen Sensing to Identify Heat-Exposed Neighbourhoods

Rural areas cool off by night but built-up urban areas lack similar relief and may threaten vulnerable people’s health during heat waves. Temperature varies within a city due to the heterogenous nature of urban environments, but official measurement stations are unable to capture local variations, since they use few measurement stations typically set up outside of urban areas. Meteorological measurements may as such be at odds with citizen sensing, where absolute accuracy is sacrificed in pursuit of increased coverage. In this article, we use geographic information processing methodologies and generate 144 hourly apparent temperature surfaces for Rotterdam during a six-day heat wave that took place in July 2019 in The Netherlands. These surfaces are used to generate a humidex degree hours (HDH) composite map. The HDH metric integrates apparent temperature intensity with duration into one spatially explicit value and is used to identify geographical areas in Rotterdam where citizens may experience adverse health effects of prolonged heat exposure. Combining the HDH map with demographic data allows us to identify the most heat-exposed areas with the largest share of vulnerable population. These neighbourhoods may be the locations most in need of adaptation measures.

The impact of cool and green roofs on summertime temperatures in the cities of Jerusalem and Tel Aviv

Experiments were conducted to assess the potential impact of cool and/or green roofs to mitigate summertime conditions in two cities of Israel, Jerusalem and Tel Aviv, which differ in elevation, humidity, and housing density. Tel Aviv is located along the coastal plain and characterized by low- and medium-density housing in a humid climate. Jerusalem is in the central mountains (elevation >750 m), and characterized by medium- and high-density housing in a dry climate. The fraction of potential roofs available for reflective cooling and the fraction of green versus impervious surface areas were estimated from "Google Earth." Both were utilized as input into the Urban Canopy Model (UCM) within the Weather Research and Forecasting model, along with the residential building density. Increasing the albedo (cool roofs) had a larger impact on roof surface radiometric temperatures than covering the roof with irrigated soil and vegetation. Cool roof surface temperature differences were about 20 °C, compared to between 10 and 15 °C for wet soils with vegetation. The impact of varying albedo on 2-m. surface temperatures was about 0.4 °C, and the impact of varying soil moisture 0.1 °C. Increasing the leaf area index from 1.5 to 4.5 had a comparatively small impact on 2 m temperatures. Imposed anthropomorphic heating added about 0.2 °C to 2-m surface temperatures, which was less than values found in other studies conducted with more sophisticated building energy models. The surface temperature and heat index within Tel Aviv were more sensitive to mitigation efforts than those in Jerusalem, but both cities could benefit from mitigation efforts.

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.

Explicit Spatializing Heat-Exposure Risk and Local Associated Factors by coupling social media data and automatic meteorological station data

Extremely high temperatures, a major cause for weather-related public health issues, are projected to intensify and become more frequent. To mitigate the adverse effects, a low-cost and effective risk assessment method should be developed. Therefore, we applied automatic meteorological station data and population mobility data to develop a high spatiotemporal resolution temperature risk assessment method. The population mobility analysis results showed the working/residential complex pattern in Tianhe District, with hotspots of spatial clustering located in the north, southwest, and southeast of the study area. Taking the population mobility patterns into consideration, high-temperature risk assessment results with a resolution of 100 m were obtained. The total mortality cases in 2014 and 2015 were used to validate this result. The validation showed that the total mortality in the high-temperature risk areas accounted for over 36% of that in Tianhe District. Thus, the method introduced in this study is capable of reflecting weather-related risk. Furthermore, the high-temperature risk assessment results showed that most of the risky areas were located in the southwest of the study area. Two peak times of the risk areas were determined, being before dawn and in the evening. Compared with the risk areas during weekdays, those at weekends expanded. In addition, we used the geographically weighted regression model to investigate the potential influencing factors. Individual factor contributed more than 22.4% to the spatial distribution of heat exposure. Catering services, transportation services, and living services were higher than others, with mean R² values of 0.28, 0.23, and 0.25, respectively. More than 47.9% of spatial distribution of heat exposure was attributed to joint function of influencing factors, with global R² ranged from 0.23 to 0.34. Our research introduces a spatial-specific method to quantitatively assess high-temperature risk. Moreover, the mechanisms behind the spatial distribution of the high-temperature risk were discussed. The theoretical and management implications can help urban designers and energy governors to develop useful strategies to mitigate weather-related public health risks.

A review of the impact of blue space on the urban microclimate

The urban heat island (UHI) phenomenon represents a major public health issue and has received great attention due to rapid urbanisation. Blue spaces have long been considered a possible mitigation strategy to ameliorate the UHI. However, our knowledge regarding the interaction of waterbodies with their urban surroundings is still limited. This review attempts through a comparative analysis of the available literature to examine the thermal effects of static blue spaces on the urban climate. Remote sensing studies are the most common approach analysed in this review but there is a clear disparity between the cooling potentials reported by remote sensing as opposed to field measurements or numerical simulations, likely due to a lack of nocturnal measurements, when warming due to thermal inertia can occur and consideration of the latent heat flux. The size and shape of blue spaces are shown to be important variables for the cooling achieved in urban settings but there is no consensus in the literature. This is likely due to the different locations and climates of the studies, it can be hypothesised that in locations with an even distribution of wind directions a rounder waterbody is more effective while in locations where wind direction is more uniform an elongated waterbody aligned to the wind is more effective due to the increased fetch. From the analysis of the literature, it is clear that there is still a distinct knowledge gap regarding the physical interpretation of waterbodies' contribution to the urban climate. There is also a current lack of information about the diurnal and seasonal variability of the various structures and processes. There is evidence, however, that the comfort achieved by sensible cooling can be offset by the increased water vapour content and that during the night blue spaces may actually exacerbate the UHI, reducing urban thermal comfort.

A simple high-resolution heat-stress forecast for Seoul, Korea: coupling climate information with an operational numerical weather prediction model

To provide a simple high-resolution heat-stress forecast for Seoul, Korea, we coupled a high-resolution climate simulation (25 m grid spacing) for an average heat day with the operational forecasting model (5 km grid spacing). Thereby, we accounted for the meso-scale weather conditions and local-scale air temperature induced by land cover and the urban heat island effect. Moreover, we estimated the impacts of heat events using heat-related mortality rate. Applying the simple high-resolution heat-stress forecast for July and August 2016, we detected a substantial spatial variability in maximum air temperature and heat-related mortality rate in Seoul. The evaluation of simulated maximum air temperature compared to observations revealed a small deviation (MB = 0.11 K, RMSD = 1.40 K). Despite the limitation of using average conditions, it was an efficient way to identify particularly affected areas, neighbourhoods, and districts for releasing more location-specific heat-stress warnings.

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.

Urban Heat Island Monitoring and Impacts on Citizen’s General Health Status in Isfahan Metropolis: A Remote Sensing and Field Survey Approach

Urban heat islands (UHIs) are one of the urban management challenges, especially in metropolises, which can affect citizens’ health and well-being. This study used a combination of remote sensing techniques with field survey to investigate systematically the effects of UHI on citizens’ health in Isfahan metropolis, Iran. For this purpose, the land surface temperature (LST) over a three-year period was monitored by Landsat-8 satellite imagery based on the split window algorithm. Then, the areas where UHI and urban cold island (UCI) phenomena occurred were identified and a general health questionnaire-28 (GHQ-28) was applied to evaluate the health status of 800 citizens in terms of physical health, anxiety and sleep, social function, and depression in UHI and UCI treatments. The average LST during the study period was 45.5 ± 2.3 °C and results showed that the Zayandeh-Rood river and the surrounding greenery had an important role in regulating the ambient temperature and promoting the citizens’ health. Citizens living in the suburban areas were more exposed to the UHIs phenomena, and statistical analysis of the GHQ-28 results indicated that they showed severe significant (P < 0.05) responses in terms of non-physical health sub-scales (i.e., anxiety and sleep, social functioning, and depression). Therefore, it can be concluded that not all citizens in the Isfahan metropolis are in the same environmental conditions and city managers and planners should pay more attention to the citizens living in the UHIs. The most important proceedings in this area would be the creation and development of parks and green belts, as well as the allocation of health-medical facilities and citizen education.

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.

Perceptions and experiences of outdoor occupational workers using digital devices for geospatial biometeorological monitoring

Wearable devices have the potential to track and monitor a wide range of biometeorological conditions (e.g., temperature, UV, air quality) and health outcomes (e.g., mental stress, physical activity, physiologic strain, and cognitive impairments). These sensors provide the potential for personalized environmental exposure information that can be harnessed for at-risk populations. Personalized environmental exposure information is of particular importance for populations that are continuously exposed to hazardous environmental conditions or with underlying health conditions. Yet, for these devices to be effective, individuals must be willing to monitor their health and, if prompted, adhere to warnings or notifications. To date, no study has examined the perceptions and use of digital devices and wearable sensors among vulnerable outdoor working populations. This study evaluated digital device use and perceptions among a population of groundworkers in three diverse geographic sites in the southeastern USA (Boone, NC, Raleigh, NC, and Starkville, MS). Our results demonstrate that biometeorological health interventions should focus on smartphone technology as a platform for monitoring environmental exposure and associated health outcomes. It was encouraging to find that those study participants were very likely to wear sensors and utilize global positioning system technology despite potential privacy issues. In addition, 3 out of 4 workers indicated that they would change their behavior if given a personalized heat preventive warning. Future development of wearable sensors and smartphone applications should integrate personalized weather warnings and ensure privacy to facilitate the use of these technologies among vulnerable populations.

Cyclone risk assessment of the Cox's Bazar district and Rohingya refugee camps in southeast Bangladesh

Bangladesh has a long history of devastating tropical cyclones. In view of the effects of the storms on the country, risk assessment is essential for devising the mitigation strategies at various levels. By way of bringing the conceptual structure of general risk model in practice, this work aims to examine the spatial patterns of cyclone risk in the Cox's Bazar district (I) and Rohingya refugee camps (II) located on the southeastern coast of Bangladesh. We use 14 parameters representing the hazard, exposure, and vulnerability as the components of risk. The selected parameters were analyzed and integrated though the complementary use of Analytic Hierarchy Process (AHP) and Geographic Information System (GIS) for depicting the cyclone risk situation comprehensively at both the spatial scales. The status of the cyclone risk was identified and quantified as very high (6.84%, 3.43%), high (45.78%, 27.82%), moderate (5.97%, 39.42%), low (40.62%, 28.70%), and very low (0.81%, 0.61%) for the spatial scale I and II respectively. In general, northwestern and southern peripheral areas exhibited higher risk than the central and northeastern parts of the Cox's Bazar district; and in the refugee settlements, camp number 1E, 1W, 7, and 13 revealed relatively higher levels of the risk. The results of the assessment (I) were correlated with experiential damage from the 1991 cyclone; a reasonable consistency was noticed between the simulated scenario and the observed impacts. We assume that the deliverables of this spatial analysis could be useful to stakeholders while formulating the cyclone risk mitigation policies for the region. Furthermore, this work demonstrates that the applied method would deliver reliable results if tested in other coastal environments.

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.

Heat risk assessment for the Brussels capital region under different urban planning and greenhouse gas emission scenarios

Urban residents are exposed to higher levels of heat stress in comparison to the rural population. As this phenomenon could be enhanced by both global greenhouse gas emissions (GHG) and urban expansion, urban planners and policymakers should integrate both in their assessment. One way to consider these two concepts is by using urban climate models at a high resolution. In this study, the influence of urban expansion and GHG emission scenarios is evaluated at 100 m spatial resolution for the city of Brussels (Belgium) in the near (2031-2050) and far (2081-2100) future. Two possible urban planning scenarios (translated into local climate zones, LCZs) in combination with two representative concentration pathways (RCPs 4.5 and 8.5) have been implemented in the urban climate model UrbClim. The projections show that the influence of GHG emissions trumps urban planning measures in each period. In the near future, no large differences are seen between the RCP scenarios; in the far future, both heat stress and risk values are twice as large for RCP 8.5 compared to RCP 4.5. Depending on the GHG scenario and the LCZ type, heat stress is projected to increase by a factor of 10 by 2090 compared to the present-day climate and urban planning conditions. The imprint of vulnerability and exposure is clearly visible in the heat risk assessment, leading to very high levels of heat risk, most notably for the North Western part of the Brussels Capital Region. The results demonstrate the need for mitigation and adaptation plans at different policy levels that strive for lower GHG emissions and the development of sustainable urban areas safeguarding livability in cities.

Seasonal temperature patterns and durations of acceptable temperature range in houses in Brisbane, Australia

A paradigm shift to the use of indoor rather than outdoor temperature to estimate the exposure risk of low and high temperatures is vital for better prediction of temperature health effects and timely health warnings, and will also assist in understanding the influence of temperature on energy consumption and comfort. This study aimed to quantify the percentage of hours during the year that indoor temperature (living room) was in the extended comfort band (18-28 °C) of a subtropical climate, and identify the diurnal pattern of indoor temperatures in different seasons. Data used was collected in a previous study on the association between indoor and outdoor temperature. A k-shape cluster analysis resulted in two clusters of indoor temperature patterns for both weekdays and weekends. A bimodal pattern was identified during the cool season and a flat top pattern for the warm season, with many variations at weekends. These patterns can be attributed to the influence of cooling and heating processes depending on the season as well as occupancy, occupants' interference, and building materials. During the intermediate season, a sinusoidal pattern was observed for both weekdays and weekends because occupants likely relied on outdoor temperature conditions which were similar to those expected indoors without heating or cooling devices. The percentage of hours in which the indoor temperature of the houses ranged within the extended comfort band was 72-97% throughout the year, but for the coldest and hottest months it was 50-75%. These findings show that Brisbane residents are at possible risk of exposure to cold and hot temperatures due to the poor thermal performance of houses, and confirm that there is no standard indoor temperature pattern for all houses.

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.

Urban environmental influences on the temperature-mortality relationship associated mental disorders and cardiorespiratory diseases during normal summer days in a subtropical city

Temperature is associated with mortality risk across cities. However, there is lack of study investigating the summer effect on mortality associated with mental/behavioral disorders, especially in cities with subtropical climate. In addition, summer mortality in subtropical cities is different from tropical cities, and previous studies have not investigated the urban environmental inequality on heat mortality associated with mental/behavioral disorders. A register-based study was developed to estimate the temperature effects on decedents on days with 50^th percentile of average daily temperature between 2007 and 2014 in Hong Kong (n = 133,359). Poisson regression was firstly applied to estimate the incidence rate ratio (IRR) from the summer temperature effects on all-cause mortality, cardiovascular mortality, respiratory mortality, and mortality associated with mental/behavioral disorders. For a 1 °C increase in average temperature on days with temperature ≥ 24.51 °C, IRRs of mortality associated with mental and behavioral disorders on lag 0 and lag 1 days were 1.033 [1.004, 1.062] and 1.030 [1.002, 1.060], while temperature effects on cardiovascular mortality and respiratory mortality during normal summer days (not extreme heat events) were not significant. A further investigation with linear regression has shown that decedents with mental/behavioral disorders on higher temperature days resided in areas with lower percentage of sky view, lower percentage of vegetation cover, higher level of neighborhood-level PM_2.5, higher level of neighborhood-level NO, and higher level of neighborhood-level black carbon (BC). In order to develop protocols for community healthcare based on the "Leaving no one behind" scheme documented in the 2016 Sustainable Development Goals report of the United Nations, it is necessary to include heat effects on mental/behavioral disorders, especially people with dementia, for community planning and healthcare development.

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.

The association between temperature variability and cause-specific mortality: Evidence from 47 Japanese prefectures during 1972-2015

BACKGROUND

In the context of climate change, extreme temperature events are known to be associated with increased mortality risk. However, data about the mortality risk related to temperature variability (TV) accounting for both intra- and inter-day variations in temperature are limited.

OBJECTIVES

The present study aims to quantify the associations between TV and cause-specific mortality in Japan, evaluate whether the effects of TV are modified by prefecture-level characteristics and examine the temporal trend in mortality risk of TV.

METHODS

Data on daily all-cause and 11 cause-specific mortality and meteorological variables in 47 Japanese prefectures from 1972 to 2015 were collected. TV was defined as the standard deviation of daily minimum and maximum temperatures during exposure days. A quasi-Poisson regression model combined with a distributed lag non-linear model was firstly applied to assess the prefecture-specific mortality effects of TV, adjusting for potential confounders. The pooled effects of TV at the national level were then obtained via a meta-analysis through the restricted maximum-likelihood estimation. Potential effect modification by prefecture characteristics was firstly examined using a meta-regression analysis, and the joint modification of season and humidity was then evaluated after including product terms in two-stage analyses. Finally, the temporal trend in TV effects was evaluated by a random-effect meta regression model after obtaining the prefecture-year-specific effects.

RESULTS

TV had significant adverse effects on all-cause and cause-specific mortality. The effects of TV were more detrimental to those with asthma and senility. In general, the estimates of mortality risk increased with longer exposure days. A 1 °C increase in TV at 0-7 days of exposure was associated with a 0.9% (95% confidence intervals: 0.82%-0.98%) increase in all-cause mortality. All-cause mortality risk of TV showed a decreasing trend during our study period. TV effects were larger in densely populated prefectures and on warm and humid days.

CONCLUSIONS

TV-related death is a significant issue in Japan that requires effective interventions.

Heat Waves and Human Well-Being in Madrid (Spain)

Heat waves pose additional risks to urban spaces because of the additional heat provided by urban heat islands (UHIs) as well as poorer air quality. Our study focuses on the analysis of UHIs, human thermal comfort, and air quality for the city of Madrid, Spain during heat waves. Heat wave periods are defined using the long-term records from the urban station Madrid-Retiro. Two types of UHI were studied: the canopy layer UHI (CLUHI) was evaluated using air temperature time-series from five meteorological stations; the surface UHI (SUHI) was derived from land surface temperature (LST) images from MODIS (Moderate Resolution Imaging Spectroradiometer) products. To assess human thermal comfort, the Physiological Equivalent Temperature (PET) index was applied. Air quality was analyzed from the records of two air quality networks. More frequent and longer heat waves have been observed since 1980; the nocturnal CLUHI and both the diurnal and nocturnal SUHI experience an intensification, which have led to an increasing number of tropical nights. Conversely, thermal stress is extreme by day in the city due to the lack of cooling by winds. Finally, air quality during heat waves deteriorates because of the higher than normal amount of particles arriving from Northern Africa.

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.

Assessment of heat exposure in cities: Combining the dynamics of temperature and population

Urban populations are typically subject to higher outdoor heat exposure than nearby rural areas due to the urban heat island (UHI) effect. Excessive Heat Events (EHEs) further amplify heat stress imposed on city dwellers. Heat exposure largely depends on the spatial and temporal distribution of temperature and population, however, few studies considered their concurrent variations. To better characterize exposure to heat in the context of long-term urban climatology and during excessive heat events, this study focuses on the dynamics of ambient temperature and population and proposes an open-data-based approach for spatiotemporal analysis of urban exposure to heat by using air temperature estimated from satellite observations and commute-adjusted diurnal population calculated primarily on the Census Transportation Planning Products. We use the metropolitan area of Chicago, U.S.A. as a case study to analyze the urban heat pattern changes during EHEs and their influence on population heat exposure diurnally. The intra-urban spatiotemporal analysis reveals that the population's exposure to heat changes fast as the nighttime temperature increases and the EHEs increase the spatial exposure impact due to the ubiquitous higher nocturnal temperature over the Chicago metropolitan area. "Hotspots" associated with a higher temperature and greater number of urban residents are identified in the heat exposure map. Meanwhile, the spatial extent of high ambient exposure areas varies diurnally. Our study contributes to a better understanding of the dynamic heat exposure patterns in urban areas. The approaches presented in this article can be used for informing heat mitigation as well as emergency response strategies at specific times and locations.

Evidence for Urban-Rural Disparity in Temperature-Mortality Relationships in Zhejiang Province, China

BACKGROUND

Temperature-related mortality risks have mostly been studied in urban areas, with limited evidence for urban-rural differences in the temperature impacts on health outcomes.

OBJECTIVES

We investigated whether temperature-mortality relationships vary between urban and rural counties in China.

METHODS

We collected daily data on 1 km gridded temperature and mortality in 89 counties of Zhejiang Province, China, for 2009 and 2015. We first performed a two-stage analysis to estimate the temperature effects on mortality in urban and rural counties. Second, we performed meta-regression to investigate the modifying effect of the urbanization level. Stratified analyses were performed by all-cause, nonaccidental (stratified by age and sex), cardiopulmonary, cardiovascular, and respiratory mortality. We also calculated the fraction of mortality and number of deaths attributable to nonoptimum temperatures associated with both cold and heat components. The potential sources of the urban-rural differences were explored using meta-regression with county-level characteristics.

RESULTS

Increased mortality risks were associated with low and high temperatures in both rural and urban areas, but rural counties had higher relative risks (RRs), attributable fractions of mortality, and attributable death counts than urban counties. The urban-rural disparity was apparent for cold (first percentile relative to minimum mortality temperature), with an RR of 1.47 [95% confidence interval (CI): 1.32, 1.62] associated with all-cause mortality for urban counties, and 1.98 (95% CI: 1.87, 2.10) for rural counties. Among the potential sources of the urban-rural disparity are age structure, education, GDP, health care services, air conditioners, and occupation types.

CONCLUSIONS

Rural residents are more sensitive to both cold and hot temperatures than urban residents in Zhejiang Province, China, particularly the elderly. The findings suggest past studies using exposure-response functions derived from urban areas may underestimate the mortality burden for the population as a whole. The public health agencies aimed at controlling temperature-related mortality should develop area-specific strategies, such as to reduce the urban-rural gaps in access to health care and awareness of risk prevention. Future projections on climate health impacts should consider the urban-rural disparity in mortality risks. https://doi.org/10.1289/EHP3556.

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.

Spatiotemporal analysis of regional socio-economic vulnerability change associated with heat risks in Canada

Excess mortality can be caused by extreme hot weather events, which are increasing in severity and frequency in Canada due to climate change. Individual and social vulnerability factors influence the mortality risk associated with a given heat exposure. We constructed heat vulnerability indices using census data from 2006 and 2011 in Canada, developed a novel design to compare spatiotemporal changes of heat vulnerability, and identified locations that may be increasingly vulnerable to heat. The results suggest that 1) urban areas in Canada are particularly vulnerable to heat, 2) suburban areas and satellite cities around major metropolitan areas show the greatest increases in vulnerability, and 3) heat vulnerability changes are driven primarily by changes in the density of older ages and infants. Our approach is applicable to heat vulnerability analyses in other countries.

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.