Mortality Associated with High Ambient Temperatures, Heatwaves, and the Urban Heat Island in Athens, Greece

Assessing and forecasting collective urban heat exposure with smart city digital twins

Due to population growth, climate change, and the urban heat island effect, heat exposure is becoming an important issue faced by urban built environments. Heat exposure assessment is a prerequisite for mitigation measures to reduce the impact of heat exposure. However, there is limited research on urban heat exposure assessment approaches that provides fine-scale spatiotemporal heat exposure information, integrated with meteorological status and human collective exposure as they move about in cities, to enable proactive heat exposure mitigation measures. Smart city digital twins (SCDTs) provide a new potential avenue for addressing this gap, enabling fine spatiotemporal scales, human-infrastructure interaction modeling, and predictive and decision support capabilities. This study aims to develop and test an SCDT for collective urban heat exposure assessment and forecasting. Meteorological sensors and computer vision techniques were implemented in Columbus, Georgia, to acquire temperature, humidity, and passersby count data. These data were then integrated into a collective temperature humidity index. A time-series prediction model and a crowd simulation were employed to predict future short-term heat exposures based on the data accumulated by this SCDT and to support heat exposure mitigation efforts. The results demonstrate the potential of SCDT to enhance public safety by providing city officials with a tool for discovering, predicting, and, ultimately, mitigating community exposure to extreme heat.

The extreme heat wave of July-August 2021 in the Athens urban area (Greece): Atmospheric and human-biometeorological analysis exploiting ultra-high resolution numerical modeling and the local climate zone framework

Greece was affected by a prolonged and extreme heat wave (HW) event (July 28-August 05) during the abnormally hot summer of 2021, with the maximum temperature in Athens, the capital of the country, reaching up to 43.9 °C in the city center. This observation corresponds to the second highest maximum temperature recorded since 1900, based on the historical temperature time series of the National Observatory of Athens weather station at Thissio. In the present study, a multi-scale numerical modeling system is used to analyze the urban climate and thermal bioclimate in the Athens urban area (AUA) in the course of the HW event, as well as during 3 days prior to the heat wave and 3 days after the episode. The system consists of the Weather Research and Forecasting model, the advanced urban scheme BEP/BEM (Building Energy Parameterization/Building Energy Model) and the human-biometeorological model RayMan Pro, and incorporates the local climate zone (LCZ) classification scheme. The system's validation results demonstrated a robust modeling set-up, characterized by high capability in capturing the observed magnitude and diurnal variation of the urban meteorological and heat stress conditions. The analysis of two- and three-dimensional fields of near-surface air temperature, humidity and wind unraveled the interplay of geographical factors (surface relief and proximity to the sea), background atmospheric circulations (Etesians and sea breeze) and HW-related synoptic forcing with the AUA's urban form. These interactions had a significant impact on the LCZs heat stress responsiveness, expressed using the modified physiologically equivalent temperature (mPET), between different regions of the study area, as well as at inter- and intra-LCZ level (statistically significant differences at 95 % confidence interval), providing thus, urban design and health-related implications that can be exploited in human thermal discomfort mitigation strategies in AUA.

Climate change and human health in the Eastern Mediterranean and Middle East: Literature review, research priorities and policy suggestions

Human health is linked to climatic factors in complex ways, and climate change can have profound direct and indirect impacts on the health status of any given region. Susceptibility to climate change is modulated by biological, ecological and socio-political factors such as age, gender, geographic location, socio-economic status, occupation, health status and housing conditions, among other. In the Eastern Mediterranean and Middle East (EMME), climatic factors known to affect human health include extreme heat, water shortages and air pollution. Furthermore, the epidemiology of vector-borne diseases (VBDs) and the health consequences of population displacement are also influenced by climate change in this region. To inform future policies for adaptation and mitigation measures, and based on an extensive review of the available knowledge, we recommend several research priorities for the region. These include the generation of more empirical evidence on exposure-response functions involving climate change and specific health outcomes, the development of appropriate methodologies to evaluate the physical and psychological effects of climate change on vulnerable populations, determining how climate change alters the ecological determinants of human health, improving our understanding of the effects of long-term exposure to heat stress and air pollution, and evaluating the interactions between adaptation and mitigation strategies. Because national boundaries do not limit most climate-related factors expected to impact human health, we propose that adaptation/mitigation policies must have a regional scope, and therefore require collaborative efforts among EMME nations. Policy suggestions include a decisive region-wide decarbonisation, the integration of environmentally driven morbidity and mortality data throughout the region, advancing the development and widespread use of affordable technologies for the production and management of drinking water by non-traditional means, the development of comprehensive strategies to improve the health status of displaced populations, and fostering regional networks for monitoring and controlling the spread of infectious diseases and disease vectors.

Analysis of the heat- and cold-related cardiovascular mortality in an urban mediterranean environment through various thermal indices

During the last decades the effects of thermal stress on public health have been a great concern worldwide. Thermal stress is determined by air temperature in combination with other meteorological parameters, such as relative humidity and wind speed. The present study is focused on the Mediterranean city of Thessaloniki, Greece and it aims to explore the association between thermal stress and mortality from cardiovascular diseases, using both air temperature and other thermal indices as indicators. For that, an over-dispersed Poisson regression function was used, in combination with distributed lag non-linear models, in order to capture the delayed and nonlinear effects of temperature. Our results revealed a reverse J-shaped exposure-response curve for the total population and females and a U-shaped association for males. In all cases examined, the minimum mortality temperature was identified around the 80th percentile of each distribution. It is noteworthy that despite the fact that the highest risks of cardiovascular mortality were estimated for exposure to extreme temperatures, moderate temperatures were found to cause the highest burden of mortality. On the whole, our estimations demonstrated that the population in Thessaloniki is more susceptible to cold effects and in regard with gender, females seem to be more vulnerable to ambient thermal conditions.

Heat and air quality related cause-based elderly mortalities and emergency visits

The combined effects of heat events and poor air quality conditions can severely affect population health. A novel correlational method was developed to assess the impact of the short-term variations of environmental variables (air pollutants and ambient conditions) on community health responses (mortalities and emergency department visits). A multi-dimensional clustering approach was proposed by combining hierarchical and k-means clustering to promote flexibility and robustness to improve the correlation procedure. The study focused on the health records of the elderly population and people diagnosed with cardiorespiratory causes. The study investigated multiple health records on different levels of investigation: total, elderly, cause-based, and elderly cause-based records. The developed method was validated by investigating the short-term impact of ambient air temperature, relative humidity, ground-level ozone, and fine particulate matter on the health records during hot and warm seasons in the municipalities of Mississauga and Brampton, Peel Region, Ontario, Canada for 15 years. The analysis confirmed the association between moderate levels of environmental variables and increased short-term daily total deaths and emergency department visits, while the elderly sector showed higher vulnerability to environmental changes. Furthermore, the association with extreme heat conditions and poor air quality levels was affirmed with cause-based mortalities and emergency visits; the correlation was strongest with elderly cause-based health records. Findings confirm that cardiorespiratory patients, especially elderly people, were at the greatest risk of poor environmental conditions.

The Impact of Ambient Temperature on Cardiorespiratory Mortality in Northern Greece

It is well-established that exposure to non-optimum temperatures adversely affects public health, with the negative impact varying with latitude, as well as various climatic and population characteristics. This work aims to assess the relationship between ambient temperature and mortality from cardiorespiratory diseases in Eastern Macedonia and Thrace, in Northern Greece. For this, a standard time-series over-dispersed Poisson regression was fit, along with a distributed lag nonlinear model (DLNM), using a maximum lag of 21 days, to capture the non-linear and delayed temperature-related effects. A U-shaped relationship was found between temperature and cardiorespiratory mortality for the overall population and various subgroups and the minimum mortality temperature was observed around the 65th percentile of the temperature distribution. Exposure to extremely high temperatures was found to put the highest risk of cardiorespiratory mortality in all cases, except for females which were found to be more sensitive to extreme cold. It is remarkable that the highest burden of temperature-related mortality was attributed to moderate temperatures and primarily to moderate cold. The elderly were found to be particularly susceptible to both cold and hot thermal stress. These results provide new evidence on the health response of the population to low and high temperatures and could be useful to local authorities and policy-makers for developing interventions and prevention strategies for reducing the adverse impact of ambient temperature.

A Methodology for Bridging the Gap between Regional- and City-Scale Climate Simulations for the Urban Thermal Environment

The main objective of this study is to bridge the gap between regional- and city-scale climate simulations, with the focus given to the thermal environment. A dynamic-statistical downscaling methodology for defining daily maximum (Tmax) and minimum (Tmin) temperatures is developed based on artificial neural networks (ANNs) and multiple linear regression models (MLRs). The approach involves the use of simulations from two EURO-CORDEX regional climate models (RCMs) (at approximately 12 km × 12 km) that are further downscaled to a finer resolution (1 km × 1 km). A feature selection methodology is applied to select the optimum subset of parameters for training the machine learning models. The downscaling methodology is initially applied to two RCMs, driven by the ERA-Interim reanalysis (2008–2011) and high-resolution urban climate model simulations (UrbClims). The performance of the relationships is validated and found to successfully simulate the spatiotemporal distribution of Tmax and Tmin over Athens. Finally, the relationships that were extracted by the models are further used to quantify changes for Tmax and Tmin in high resolution, between the historical period (1971–2000) and mid-century (2041–2071) climate projections for two different representative concentration pathways (RCP4.5 and RCP8.5). Based on the results, both mean Tmax and Tmin are estimated to increase by 1.7 °C and 1.5 °C for RCP4.5 and 2.3 °C and 2.1 °C for RCP8.5, respectively, with distinct spatiotemporal patterns over the study area.

Short-Term Effects of Apparent Temperature on Cause-Specific Mortality in the Urban Area of Thessaloniki, Greece

Although there is a growing interest in the association between ambient temperatures and mortality, little evidence is available for Thessaloniki, the second largest city of Greece. In this study, we present an assessment of the effects of temperature on daily mortality from 2006 to 2016 in the urban area of Thessaloniki, by describing the exposure-lag-response association between temperature and cause-specific mortality with the use of a distributed lag non-linear model (DLNM). A J-shaped relationship was found between temperature and mortality. The highest values of risk were evident for respiratory (RR > 10) and cardiovascular causes (RR > 3), probably due to the fact that health status of individuals with chronic respiratory and cardiovascular diseases rapidly deteriorates during hot periods. Cold effects had longer lags of up to 15 days, whereas heat effects were short-lived, up to 4 days. Percentage change in all- and cause-specific mortality per 1 °C change above and below Minimum Mortality Temperature showed a larger increase for all-cause mortality in heat (1.95%, 95% CI: 1.07–2.84), in contrast to a smaller increase in cold (0.54%, 95% CI: 0, 1.09). Overall, 3.51% of all-cause deaths were attributable to temperature, whereas deaths attributed to heat (2.34%) were more than deaths attributed to cold (1.34%). The findings of this study present important evidence for planning public-health interventions, to reduce the health impact of extreme temperatures.

Fixed and Mobile Low-Cost Sensing Approaches for Microclimate Monitoring in Urban Areas: A Preliminary Study in the City of Bolzano (Italy)

In the current scenario of massive urbanization and global climate change, an intelligent monitoring of the environmental variables is becoming fundamental to ensure good living conditions in cities. Indeed, the acquisition of data with high spatiotemporal resolution can enable the assessment of environmental vulnerabilities in urban areas towards the definition of responsive adaptation and mitigation strategies. In this context, the current work presents a two-fold approach based on low-cost cloud-connected sensors for (i) fixed and (ii) mobile monitoring of several environmental parameters. This paper, which focuses on the measurement aspects of the urban micro-climate, describes in detail the hardware and software components of both approaches, and how to exploit them for setting up a field campaign. The methods were tested in the city of Bolzano (Italy), demonstrating their suitability for identifying the spatial variability of the microclimate in relation to the urban morphology, and for highlighting the presence of the urban heat island and estimating its intensity.

Procedure for the selection and evaluation of prefabricated housing buildings for the implementation of green roofs in the context of Urban Heat Island mitigation. The example of Wrocław, Poland

The assessment of the suitability of existing buildings for implementation of green roofs is an important research issue, especially in the context of Urban Heat Island (UHI), the negative impacts of which are locally exacerbated by the global warming. The studies carried out so far have covered a variety of buildings and have taken into account a range of different conditions. Relatively little attention has been paid to the possibilities of greening the roofs of prefabricated apartment blocks from the second half of the 20th century in the context of the potential climate effect. Yet, these buildings are found in many cities around the world, and seem in fact attractive for greening. In view of the above, we proposed a three-stage investigatory procedure to: (I) identify and classify buildings based on the number of floors and the rooftop available area; (II) select buildings by designating priority areas depending on the highest UHI intensity and roof density; (III) analyse the roof load capacity to develop retrofit scenarios. The procedure was applied to prefabricated housing estates built in the 1970s and 1980s in Wrocław, Poland. The research shows that there are 1962 buildings of different heights and roof area of 722405 m2, of which 480 buildings with a roof area of 122749.1 m2 were selected for greening within priority areas. The structure of the studied roofs was not designed to carry additional loads, which requires the application of complementary solutions. Scenario 1 assumes extensive greening provided that the existing ventilated roof is strengthened, scenario 2 -semi-intensive greening, which however requires the conversion of the ventilated roof to a non-ventilated one. The presented procedure can be applied in any other city with prefabricated apartment blocks and available UHI data, and serve to support the decision to implement green roofs to mitigate UHI.

Effect of non-optimum ambient temperature on cognitive function of elderly women in Germany

Non-optimum ambient temperature has been associated with a variety of health outcomes in the elderly population. However, few studies have examined its adverse effects on neurocognitive function. In this study, we explored the temperature-cognition association in elderly women. We investigated 777 elderly women from the German SALIA cohort during the 2007-2010 follow-up. Cognitive function was evaluated using the CERAD-Plus test battery. Modelled data on daily weather conditions were assigned to the residential addresses. The temperature-cognition association over lag 0-10 days was estimated using multivariable regression with distributed lag non-linear model. The daily mean temperature ranged between -6.7 and 26.0 °C during the study period for the 777 participants. We observed an inverse U-shaped association in elderly women, with the optimum temperature (15.3 °C) located at the 68th percentile of the temperature range. The average z-score of global cognitive function declined by -0.31 (95%CI: 0.73, 0.11) for extreme cold (the 2.5th percentile of temperature range) and -0.92 (95%CI: 1.50, -0.33) for extreme heat (the 97.5th percentile of temperature range), in comparison to the optimum temperature. Episodic memory was more sensitive to heat exposure, while semantic memory and executive function were the two cognitive domains sensitive to cold exposure. Individuals living in an urban area and those with a low educational level were particularly sensitive to extreme heat. In summary, non-optimum temperature was inversely associated with cognitive function in elderly women, with the effect size for heat exposure particularly substantial. The strength of association varied by cognitive domains and individual characteristics.

Non-optimum temperature-related mortality burden in China: Addressing the dual influences of climate change and urban heat islands

Under the dual effects of climate change and urban heat islands (UHI), non-optimum temperature-related mortality burdens are complex and uncertain, and are rarely discussed in China. In this study, by applying city-specific exposure-response functions to multiple temperature and population projections under different climate and urbanization scenarios, we comprehensively assessed the non-optimum temperature-related mortality burdens in China from 2000 to 2050. Our results showed that temperature-related deaths will decrease from 1.19 million in 2010 to 1.08-1.17 million in 2050, with the exception of the most populous scenario. Excess deaths attributable to non-optimal temperatures under representative concentration pathway 8.5 (RCP8.5) were 2.35% greater than those under RCP4.5. This indicates that the surge in heat-related deaths caused by climate change will be offset by the reduction in cold-related deaths. As the climate changes, high-risk areas will be confronted with more severe health challenges, which requires health protection resource relocation strategies. Simultaneously, the net effects of UHIs are beneficial in the historical periods, preventing 3493 (95% CI: 22-6964) deaths in 2000. But UHIs will cause an additional 6951 (95% CI: -17,637-31,539, SSP4-RCP4.5) to 17,041 (95% CI: -10,516-44,598, SSP5-RCP8.5) deaths in 2050. The heavier health burden in RCP8.5 than RCP4.5 indicates that a warmer climate aggravates the negative effects of UHIs. Considering the synergistic behavior of climate change and UHIs, UHI mitigation strategies should not be developed without considering climate change. Moreover, the mortality burden exhibited strong spatial variations, with heavy burdens concentrated in the hotspots including Beijing-Tianjin Metropolitan Region, Yangtze River Delta, Chengdu-Chongqing City Group, Guangzhou, Wuhan, Xi'an, Shandong, and Henan. These hotspots should be priority areas for the allocation of the national medical resources to provide effective public health interventions.

Technological opportunities for sensing of the health effects of weather and climate change: a state-of-the-art-review

Sensing and measuring meteorological and physiological parameters of humans, animals, and plants are necessary to understand the complex interactions that occur between atmospheric processes and the health of the living organisms. Advanced sensing technologies have provided both meteorological and biological data across increasingly vast spatial, spectral, temporal, and thematic scales. Information and communication technologies have reduced barriers to data dissemination, enabling the circulation of information across different jurisdictions and disciplines. Due to the advancement and rapid dissemination of these technologies, a review of the opportunities for sensing the health effects of weather and climate change is necessary. This paper provides such an overview by focusing on existing and emerging technologies and their opportunities and challenges for studying the health effects of weather and climate change on humans, animals, and plants.

Water-Stressed Plants Do Not Cool: Leaf Surface Temperature of Living Wall Plants under Drought Stress

Urban green infrastructures offer thermal regulation to mitigate urban heat island effects. To gain a better understanding of the cooling ability of transpiring plants at the leaf level, we developed a method to measure the time series of thermal data with a miniaturized, uncalibrated thermal infrared camera. We examined the canopy temperature of four characteristic living wall plants (Heuchera x cultorum, Bergenia cordifolia, Geranium sanguineum, and Brunnera macrophylla) under increasing drought stress and compared them with a well-watered control group. The method proved suitable to evaluate differences in canopy temperature between the different treatments. Leaf temperatures of water-stressed plants were 6 to 8 °C higher than those well-watered, with differences among species. In order to cool through transpiration, vegetation in green infrastructures must be sufficiently supplied with water. Thermal cameras were found to be useful to monitor vertical greening because leaf surface temperature is closely related to drought stress. The usage of thermal cameras mounted on unmanned aerial vehicles could be a rapid and easy monitoring system to cover large façades.

Analyzing the local and climatic conditions affecting the urban overheating magnitude during the Heatwaves (HWs) in a coastal city: A case study of the greater Sydney region

Urban overheating coincides with Heatwaves (HWs) and the thermal stress might get amplified in cities. To predict the interactions between urban overheating and HWs, the surface energy balance response to HWs is crucial. HW is a regional phenomenon and the climatic conditions may influence the local conditions to alter the energy budget contrast between a city and its adjacent peripheral areas. The interactions between the urban overheating and HWs are explored in a coastal city (Sydney Australia), also in the proximity of dry landmass, while considering the site characteristics, distance from the coast, and the population density. A positive response between urban overheating and HWs is reported. Advective heat flux in the form of a dualistic circulation system is found responsible for exacerbating the urban overheating magnitude (ΔT) during the HWs and altering the available energy balance. Land-coastal distance is also found as an important contributor in magnifying the urban-suburban temperature contrast. Considering the future urbanization in western Sydney, surfaces capable of retaining higher moisture content are prescribed to reduce the occurrence of extreme HW events. Activation of the ventilation corridor for the coastal wind penetration in western Sydney is another recommendation of this study.

Exploring the relationship between particulate matter, CO, SO2, NO2, O3 and urban heat island in Seoul, Korea

Urban environments face two challenging problems that are parallel in nature but yet with compelling potential synergistic interactions; urban heat island (UHI) and air pollution. We explore these interactions using in-situ temperature and air pollution data collected from 13 monitoring stations for nine years. Through regression analysis and analysis of variance (ANOVA) tests, we found that carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and particulate matter (PM) show positive correlations with UHI intensity (UHII). At the same time, Ozone (O₃) was negatively correlated with UHII. Moreover, there was a substantial seasonal effect on the strength of the correlations between UHI and air pollution, with some air pollutants showing strong associations with UHI during certain seasons (i.e., winter and autumn). The strongest interactions were observed for NO₂ (R² = 0.176) and PM10 (R² = 0.596) during the wintertime and for SO₂ (R² = 0.849), CO (R² = 0.346), PM2.5   (R² = 0.695) and O₃ (R² = 0.512) during autumn. Understanding such interactions is essential for urban climate studies and our study provides a basis for scientific discussions on integrative mitigation strategies for both UHI and air pollution in Seoul city.

A Regression Analysis of the Carbon Footprint of Megacities

Urbanization and climate change are two major issues that humanity faces in the 21st century. Megacities are large urban agglomerations with more than 10 million inhabitants that emerged in the 20th century. The world’s top 100 economies include many North and South American megacities, such as New York, Los Angeles, Mexico City, Sao Paulo and Buenos Aires; European cities such as London and Paris; and Asian cities such as Tokyo, Osaka, Seoul, Beijing and Mumbai. This paper addresses a dearth of megacity energy metabolism models in the literature. Cross-sectional data for 36 global megacities were collected from many literature and Internet sources. Variables included megacity name, country and region; population; area; population density; (per capita) GDP; income inequality measures; (per capita) energy consumption; household electricity prices; (per capita) carbon and ecological footprint; degree days; average urban heat island intensity; and temperature and precipitation. A descriptive comparison of the characteristics of megacities was followed by ordinary least squares with heteroskedasticity-robust standard errors that were used to estimate four alternative multiple regression models. The per-capita carbon footprint of megacities was positively associated with the megacity GDP per capita, and the megacity ecological footprint; and negatively associated with country income inequality, a low-income country dummy, the country household electricity price, and the megacity annual precipitation. Targeted policies are needed, but more policy autonomy should be left to megacities. Collecting longitudinal data for megacities is very challenging but should be a next step to overcome misspecification and bias issues that plague cross-sectional approaches.

On the association of ambient temperature and elderly mortality in a Mediterranean island - Crete

Extreme weather conditions affect human health. This study analyses the association of high and low temperature with cardiovascular and respiratory diseases on people over 65 years old for the years 2007 to 2015, in the region of Chania, Greece. The mortality is examined by time series analysis and further investigated by Poisson, and Negative Binomial regression, showing that one-lag in maximum temperature strongly affects the health of the elderly. Finally, cluster analysis is used from May to October, which is confirmed by discriminant analysis.

Using deep-learning to forecast the magnitude and characteristics of urban heat island in Seoul Korea

Urban heat island (UHI), a phenomenon involving increased air temperature of a city compared to the surrounding rural area, results in increased energy use and escalated health problems. To understand the magnitude and characteristics of UHI in Seoul and to accommodate for the high temporal variability and spatial heterogeneity of the UHI which make it inherently challenging to analyze using conventional statistical methods, we developed two deep learning models, a temporal UHI-model and a spatial UHI model, using a feed-forward deep neural network (DNN) architecture. Data related to meteorological elements (e.g. air temperature) and urban texture (e.g. surface albedo) were used to train and test the temporal UHI-model and the Spatial UHI-model respectively. Also, we develop and propose a new metric, UHI-hours, that quantifies the total number of hours that UHI exists in a given area. Our results show that UHI-hours is a better indicator of seasonal UHI than the commonly used index, UHI-intensity. Consequently, UHI-hours is likely to provide a better measure of the cumulative effects of UHI over time than UHI-intensity. UHI-hours will help us to better quantify the effect of UHI on, for example, the overall daily productivity of outdoor workers or heat-related mortality rates.

Exploring the Synergies between Urban Overheating and Heatwaves (HWs) in Western Sydney

There is no consensus regarding the change of magnitude of urban overheating during HW periods, and possible interactions between the two phenomena are still an open question, despite the increasing frequency and impacts of Heatwaves (HW). The purpose of this study is to explore the interactions between urban overheating and HWs in Sydney, which is under the influence of two synoptic circulation systems. For this purpose, a detailed analysis has been performed for the city of Sydney, while considering an urban (Observatory Hill), in the Central Business District (CBD), and a non-urban station in Western Sydney (Penrith Lakes). Summer 2017 was considered as a study period, and HW and Non-Heatwave (NHW) periods were identified to explore the interactions between urban overheating and HWs. A strong link was observed between urban overheating and HWs, and the difference between the peak average urban overheating magnitude during HWs and NHWs was around 8 °C. Additionally, the daytime urban overheating effect was more pronounced during the HWs when compared to nighttime. The advective flux was found as the most important interaction between urban overheating and HWs, in addition to the sensible and latent heat fluxes.

Urban-Rural Surface Temperature Deviation and Intra-Urban Variations Contained by an Urban Growth Boundary

The urban heat island (UHI) concept describes heat trapping that elevates urban temperatures relative to rural temperatures, at least in temperate/humid regions. In drylands, urban irrigation can instead produce an urban cool island (UCI) effect. However, the UHI/UCI characterization suffers from uncertainty in choosing representative urban/rural endmembers, an artificial dichotomy between UHIs and UCIs, and lack of consistent terminology for other patterns of thermal variation at nested scales. We use the case of a historically well-enforced urban growth boundary (UGB) around Portland (Oregon, USA): to explore the representativeness of the surface temperature UHI (SUHI) as derived from Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature data, to test common assumptions of characteristically “warm” or “cool” land covers (LCs), and to name other common urban thermal features of interest. We find that the UGB contains heat as well as sprawl, inducing a sharp surface temperature contrast across the urban/rural boundary. The contrast ranges widely depending on the end-members chosen, across a spectrum from positive (SUHI) to negative (SUCI) values. We propose a new, inclusive “urban thermal deviation” (UTD) term to span the spectrum of possible UHI-zero-UCI conditions. We also distinguish at finer scales “microthermal extremes” (MTEs), discrete areas tending in the same thermal direction as their LC or surroundings but to extreme (hot or cold) values, and microthermal anomalies (MTAs), that run counter to thermal expectations or tendencies for their LC or surroundings. The distinction is important because MTEs suggest a need for moderation in the local thermal landscape, whereas MTAs may suggest solutions.

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.

Potential benefits of cool roofs in reducing heat-related mortality during heatwaves in a European city

Hot weather can exacerbate health conditions such as cardiovascular and respiratory diseases, and lead to heat stroke and death. In built up areas, temperatures are commonly observed to be higher than those in surrounding rural areas, due to the Urban Heat Island (UHI) effect. Climate change and increasing urbanisation mean that future populations are likely to be at increased risk of overheating in cities, although building and city scale interventions have the potential to reduce this risk. We use a regional weather model to assess the potential effect of one type of urban intervention - reflective 'cool' roofs - to reduce local ambient temperatures, and the subsequent impact on heat-related mortality in the West Midlands, UK, with analysis undertaken for the summer of 2006, as well as two shorter heatwave periods in 2006 and 2003. We show that over a summer season, the population-weighted UHI intensity (the difference between simulated urban and rural temperature) was 1.1 °C on average, but 1.8 °C when including only night times, and reached a maximum of 9 °C in the West Midlands. Our results suggest that the UHI contributes up to 40% of heat related mortality over the summer period and that cool roofs implemented across the whole city could potentially offset 18% of seasonal heat-related mortality associated with the UHI (corresponding to 7% of total heat-related mortality). For heatwave periods, our modelling suggests that cool roofs could reduce city centre daytime 2 m air temperature by 0.5 °C on average, and up to a maximum of ~3 °C. Cool roofs reduced average UHI intensity by ~23%, and reduced heat related mortality associated with the UHI by ~25% during a heatwave. Cool roofs were most effective at reducing peak temperatures during the daytime, and therefore have the potential to limit dangerous extreme temperatures during heatwaves. Temperature reductions were dependent on the category of buildings where cool roofs were applied; targeting only commercial and industrial type buildings contributed more than half of the reduction for heatwave periods. Our modelling suggested that modifying half of all industrial/commercial urban buildings could have the same impact as modifying all high-intensity residential buildings in the West Midlands.

Integrating Urban Form, Function, and Energy Fluxes in a Heat Exposure Indicator in View of Intra-Urban Heat Island Assessment and Climate Change Adaptation

Cities worldwide are getting warmer due to the combined effects of urban heat and climate change. To this end, local policy makers need to identify the most thermally vulnerable areas within cities. The Local Climate Zone (LCZ) scheme highlights local-scale variations; however, its classes, although highly valuable, are to a certain extent generalized in order to be universally applicable. High spatial resolution indicators have the potential to better reflect city-specific challenges; in this paper, the Urban Heat Exposure (UHeatEx) indicator is developed, integrating the physical processes that drive the urban heat island (UHI). In particular, the urban form is modeled using remote sensing and geographical information system (GIS) techniques, and used to estimate the canyon aspect ratio and the storage heat flux. The Bowen ratio is calculated using the aerodynamic resistance methodology and downscaled remotely sensed surface temperatures. The anthropogenic heat flux is estimated via a synergy of top–down and bottom–up inventory approaches. UHeatEx is applied to the city of Athens, Greece; it is correlated to air temperature measurements and compared to the LCZs classification. The results reveal that UHeatEx has the capacity to better reflect the strong intra-urban variability of the thermal environment in Athens, and thus can be supportive for adaptation responses. High-resolution climate projections from the EURO-CORDEX ensemble for the region show that the adverse effects of the existing thermal inequity are expected to worsen in the coming decades.

The heat penalty of walkable neighbourhoods

"Walkability" or walking-friendliness is generally considered a favourable attribute of a neighbourhood that supports physical activity and improves health outcomes. Walkable neighbourhoods tend to have high-density infrastructure and relatively high amounts of concrete and pavement for sidewalks and streets, all of which can elevate local urban temperatures. The objective of this study was to assess whether there is a "heat penalty" associated with more walkable neighbourhoods in Montréal, Québec, Canada, using air temperature measurements taken in real time at street level during a heat event. The mean temperature of "Car-Dependent" neighbourhoods was 26.2 °C (95% CI 25.8, 26.6) whereas the mean temperature of "Walker's Paradise" neighbourhoods was 27.9 °C (95% CI 27.8, 28.1)-a difference of 1.7 °C (95% CI 1.3, 2.0). There was a strong association between higher walkability of Montréal neighbourhoods and elevated temperature (r = 0.61, p < 0.01); suggestive of a heat penalty for walkable neighbourhoods. Planning solutions that support increased walking-friendliness of neighbourhoods should consider simultaneous strategies to mitigate heat to reduce potential health consequences of the heat penalty.

Introducing Urban Overheating—Progress on Mitigation Science and Engineering Applications

Buildings and construction is the most important economic sector in the world after agriculture [...]

The effect of ambient air temperature on cardiovascular and respiratory mortality in Thessaloniki, Greece

OBJECTIVES

There is a growing body of evidence linking ambient air temperature and adverse health effects, in the form of hospitalization or even increased mortality mainly due to respiratory and cardio/cerebro-vascular illnesses. In the present study, we examine the association between high ambient air temperature and cardiovascular as well as respiratory mortality for the population of the greater area of Thessaloniki, Greece, taking into account the role of particulate pollution as a potential confounder.

METHODS

A mixed Poisson regression model, using a quasi-likelihood function to account for potential over-dispersion in the outcome distribution given covariates, was combined with distributed lag non-linear models, to estimate the non-linear and lag patterns in the association between mortality and daily mean temperature from 1999 to 2012.

RESULTS

A direct heat effect was found, as the mortality risk increased sharply above the temperature threshold of 33 °C, suggesting a significant effect of high temperatures on mortality on the same and next day of the heat events (lags 0-1) which was retained for a week, whereas a harvesting effect was noticed for the following days. Cardiovascular and respiratory mortality risk increased by 4.4% (95% CI 2.7%-6.1%) and 5.9% (95% CI 1.8%-10.3%) respectively on the same and following day of a heat event, whereas the risk dropped steeply in the following days. Particulate matter did not confound the association between high temperature and mortality in this population.

CONCLUSION

There is a significant association between mortality and hot temperatures in Thessaloniki, Greece. Reduction in exposure to increased temperatures, as part of prevention measures and strategies, should be considered for vulnerable subpopulations.

Increasing Probability of Heat-Related Mortality in a Mediterranean City Due to Urban Warming

Extreme temperatures impose thermal stress on human health, resulting in increased hospitalizations and mortality rate. We investigated the circulatory and respiratory causes of death for the years 2007 to 2014 inclusive for the urban and rural areas of Nicosia, Cyprus under urban heatwave and non-heatwave conditions. Heatwaves were defined as four or more consecutive days with mean urban daily temperature over the 90th percentile threshold temperature of the eight investigated years. Lag period of adverse health effects was found to be up to three days following the occurrence of high temperatures. The relative risk (RR) for mortality rate under heatwave and non-heatwave conditions was found taking in consideration the lag period. The results showed the increase of mortality risk particularly for men of ages 65⁻69 (RR = 2.38) and women of ages 65⁻74 (around RR = 2.54) in the urban area, showing that women were more vulnerable to heat extremities. High temperatures were also associated with high ozone concentrations, but they did not impose an excess risk factor, as they did not reach extreme values. This analysis highlights the importance of preparing for potential heat related health impacts even in Cyprus, which is an island with frequent heatwaves.

Quantifying the Trends in Land Surface Temperature and Surface Urban Heat Island Intensity in Mediterranean Cities in View of Smart Urbanization

Land Surface Temperature (LST) is a key parameter for the estimation of urban fluxes as well as for the assessment of the presence and strength of the surface urban heat island (SUHI). In an urban environment, LST depends on the way the city has been planned and developed over time. To this end, the estimation of LST needs adequate spatial and temporal data at the urban scale, especially with respect to land cover/land use. The present study is divided in two parts: at first, satellite data from MODIS-Terra 8-day product (MOD11A2) were used for the analysis of an eighteen-year time series (2001–2017) of the LST spatial and temporal distribution in five major cities of the Mediterranean during the summer months. LST trends were retrieved and assessed for their statistical significance. Secondly, LST values and trends for each city were examined in relation to land cover characteristics and patterns in order to define the contribution of urban development and planning on LST; this information is important for the drafting of smart urbanization policies and measures. Results revealed (a) positive LST trends in the urban areas especially during nighttime ranging from +0.412 °K in Marseille to +0.923 °K in Cairo and (b) the SUHI has intensified during the last eighteen years especially during daytime in European Mediterranean cities, such as Rome (+0.332 °K) and Barcelona (+0.307 °K).