Average Urban Heat Island Intensity Research Articles

Characteristics of the Urban Heat Island in Dhaka, Bangladesh, and Its Interaction with Heat Waves

AbstractThis study examines the characteristics of the urban heat island (UHI) in Dhaka, the densely populated capital city of Bangladesh under the influence of the South Asian monsoon, and its interaction with heat waves. For this, meteorological data at Dhaka (urban) and Madaripur (rural) stations and reanalysis data for the period of 1995–2019 are used for analysis. Here, the UHI intensity is defined as the urban-rural difference in 2-m temperature, and a heat wave is defined as the phenomenon which persists for two or more consecutive days with the daily maximum 2-m temperature exceeding its 90th percentile. The UHI intensity in Dhaka is in an increasing trend over the past 25 years (0.21 °C per decade). The average UHI intensity in Dhaka is 0.48 °C. The UHI is strongest in winter (0.95 °C) and weakest in the monsoon season (0.23 °C). In all seasons, the UHI is strongest at 2100 LST. The average daily maximum UHI intensity in Dhaka is 2.15 °C. Through the multiple linear regression analysis, the relative importance of previous-day daily maximum UHI intensity (PER), wind speed, relative humidity (RH), and cloud fraction which affect the daily maximum UHI intensity is examined. In the pre-monsoon season, RH is the most important variable followed by PER. In the monsoon season, RH is the predominantly important variable. In the post-monsoon season and winter, PER is the most important variable followed by RH. The occurrence frequency of heat waves in Dhaka shows a statistically significant increasing trend in the monsoon season (5.8 days per decade). It is found that heat waves in Bangladesh are associated with mid-to-upper tropospheric anticyclonic-flow and high-pressure anomalies in the pre-monsoon season and low-to-mid tropospheric anticyclonic-flow and high-pressure anomalies in the monsoon season. Under heat waves, the UHI intensity is synergistically intensified in both daytime and nighttime (nighttime only) in the pre-monsoon (monsoon) season. The decreases in relative humidity and cloud fraction are favorable for the synergistic UHI-heat wave interaction.

Влияние метеофакторов на среднесуточную интенсивность городского острова тепла Екатеринбурга

Urban heat island (UHI) intensity in the surface air temperature field is equal to the difference between temperatures (averaged for the period under consideration) in the city and in the immediate rural surroundings. Using multi-regression analysis, We investigated the meteorological factors determining the mean daily UHI intensity based on observational data at weather stations in Yekaterinburg and the village of Verkhneye Dubrovo in 2020–2022. The average value of an UHI intensity in May-September equals to 0.94 °C with a standard deviation of daily mean values of 0.71 °C. The multiple linear regression model includes the difference in the relative humidity of the atmosphere in the city and the village, the weather factor determined by wind speed and cloudiness, and atmospheric pressure. This “summer” model describes 60 % of the observed UHI variance. In December-March, the average UHI intensity equals to 0.81 °C with a standard deviation of mean daily values of 0.82 °C. The regression model includes only the weather factor explaining 27 % of the UHI variability. It is concluded that the UHI intensity in Yekaterinburg is primarily determined by solar radiation and various properties of urban and rural surfaces (albedo, emissivity, thermal properties of soils). They determine the maximal UHI intensity that is realized only in “ideal” weather (weather factor ~1). Deviations from “ideal” conditions described by meteorological factors only reduce the maximal UHI intensity. In winter, heat leaks from buildings and heating networks weakly dependent on the meteorological factors make an additional contribution to the UHI intensity.

Study of Urban Thermal Environment and Local Circulations of Guangdong‐Hong Kong‐Macao Greater Bay Area Using WRF and Local Climate Zones

AbstractThe Guangdong‐Hong Kong‐Macao Greater Bay Area (GBA), a cluster of world‐class cities, is undergoing rapid urbanization. However, the heterogeneity of the urban thermal environment resulting from the diversity of urban forms is not yet fully understood. This paper assesses the heterogeneity of the urban heat island (UHI) effect in the GBA using the coupled Weather Research and Forecasting (WRF) model/multi‐layer urban canopy and building energy model (BEP/BEM), with high‐resolution local climate zone (LCZ) map as urban land use/land cover data. The average UHI intensity is found to peak at 1.8 ± 0.4°C in the evening, when the average UHI intensity of LCZ 2 can reach a maximum of 2.4 ± 0.58°C. Properly setting air‐conditioning temperatures can effectively prevent the enhancement of the UHI phenomenon at night by the anthropogenic heat (AH) released from air‐conditioning. The UHI‐induced local circulations and enhanced surface roughness inhibit the penetration of sea breezes inland, and surface wind speed decreases in all LCZs, with a maximum change of more than 0.8 m s−1. However, the increased thermal difference between land and sea leads to enhanced sea breezes offshore, especially in the Pearl River estuary. In addition, a series of sensitivity experiments have been conducted in this paper on initial and boundary conditions, building drag coefficients and urban fractions, which paves the way for further analyzing urban climate in GBA using WRF model and LCZs.

Urban Design Impact on Local Climate and its Consequences on Building Energy Demand in Morocco

Urban design has a profound impact on the local climate, which can result in changes in temperature distribution and energy demand. The Urban Heat Island (UHI), a well-documented issue where cities typically experience higher temperatures than the cooler rural surroundings that envelop them, is closely tied to urban design and its geometrical features. This increase in temperature can lead to increased energy consumption, particularly for air conditioning, as populations strive to maintain thermal comfort. Within this framework, this paper seeks to advance our comprehension of the influence of urban design on the Urban Heat Island (UHI) effect and building energy requirements. It makes a valuable contribution to the expanding body of research in this field, offering insightful guidance on optimal urban design strategies tailored to diverse climate zones in Morocco. To achieve these goals, we explore multiple urban design scenarios incorporating variations in building heights, street aspect ratios, building layout configurations, and street orientations. We employ the Urban Weather Generator and EnergyPlus for our analysis, with the former enabling the generation of synthetic weather data that accounts for the UHI effect in urban contexts, and the latter facilitating building energy simulations. The simulation results reveal a wide-ranging hourly variation in Urban Heat Island (UHI) intensity, spanning from 11°C to -5°C across the cities under study. Among these cities, Ifrane, Marrakesh, and Fes exhibit the highest average annual UHI intensity. Incorporating UHI considerations into energy simulations has yielded notable outcomes. Low-rise buildings experience a reduction in total energy requirements, while mid-rise and high-rise buildings exhibit an increase. For instance, adopting an urban design scenario featuring 20-story buildings and a street aspect ratio of 0.33 led to a rise in total energy demands between 8% and 19%. Furthermore, the street aspect ratio (H/W) emerges as the primary driver of UHI, whereas street orientation and building layout exert the most substantial influence on building energy requirements. Inefficient building layouts result in a significant increase in building energy needs, ranging from 106% to 121%, while less energy-efficient street orientations lead to total energy needs escalating by 28% to 76%.

Geospatial and statistical analysis of urban heat islands and thermally vulnerable zones in Bangalore and Hyderabad cities in India

Urban Heat Island (UHI) effects caused by urbanization and associated anthropogenic activities have adverse environmental and social impacts. The social impacts of UHIs on Indian cities are not well documented. To fill this void, the current paper examines the spatial variation of the UHI effects on the populations of two Indian cities: Bangalore and Hyderabad. Land Surface Temperature (LST) data for the past two decades is obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to analyse the spatial and temporal variation of the thermal environment of the cities. The regions experiencing different levels of UHI effects within the cities, along with the population in these zones, are identified in the study. The average UHI intensity for the past two decades in Bangalore and Hyderabad is found to be 1.9 °C and 2.44 °C, respectively. The UHI intensity in Bangalore and Hyderabad is found to be increasing annually at a rate of 0.040 °C per year and 0.033 °C per year, respectively. Around 1 million people in Bangalore and 1.8 million people in Hyderabad are inhabitants of the high temperate zone, experiencing an average LST of 3.14 °C and 3.55 °C higher than the rest of the population, respectively. The study emphasizes the need for regionally scaled UHI mitigation strategies and identifies the most vulnerable regions within the study area to prioritize mitigation strategies.

On-site measurement and numerical simulation study on characteristic of urban heat island in a multi-block region in Beijing, China

The urban heat island (UHI) effect can lead to an increase in winter temperatures in cold regions, which in turn increases energy consumption and air pollution within urban areas. Field measurements of UHI effects can provide high-precision and high-resolution data, making them suitable for investigating the spatial-temporal distribution of UHI. However, there have been relatively few studies on the field testing of UHI effects in multiple blocks, especially those that involve continuous monitoring. Additionally, while many studies have demonstrated the impact factors of UHI intensity, there is a scarcity of research on quantitative and weight analyses of these factors. In this study, on-site measurements of UHI characteristics were carried out in a typical multi-block region in Beijing. The on-site sampling was conducted in both summer and winter seasons for 29 consecutive sampling days with 20 sampling points. The average urban heat island intensity (UHII) during the sampling period was 1.7 ± 1.2 °C in summer and 3.7 ± 1.8 °C in winter. Temperatures measured at different sampling locations varied significantly, with a maximum spatial difference of 7.5 °C in summer and 4.1 °C in winter. Simulation results showed that, in summer, each ±10% change in wind speed, albedo, or solar radiation intensity would cause the UHII to change by ∓0.16 °C, ∓0.21 °C, or ± 0.17 °C, respectively. In winter, the effects of these factors were very limited. The effect weights of wind speed, albedo, and solar radiation intensity on UHII in summer were 31.3%, 36.6%, and 32.1%, respectively. The position of green space in relation to the dominant wind direction of the city would have a greater effect on UHI mitigation in summer than in winter. This study provides a theoretical basis for mitigating UHI effects and is of great significance for sustainable urban design.

Differences in urban heat island and its driving factors between central and new urban areas of Wuhan, China.

Urban heat island (UHI) is one of the important effects of urbanization on built environment. Land surface temperature data was taken from moderate-resolution imaging spectroradiometer (MODIS) to investigate the long-term spatiotemporal patterns of UHI in Wuhan during 2001~2018 and, the UHI intensity changes of built-up land in 13 administrative regions in Wuhan were analyzed. Furthermore, 34 spatial error models and 34 ordinary least squares models were established and compared. Spatial error models showed good fitting effect, which were used to determine the influence of normalized difference vegetation index (NDVI), normalized difference building index (NDBI), and social-economic factors (population and nighttime light) on UHI intensity in central urban area and new urban area. The explanatory power changes of these four indicators during 2001~2018 were explored as well. The average UHI intensity in 2014~2018 has increased by about 0.45 °C compared to that in 2001~2005. NDBI is the most dominant factor contributing to the increase in temperature. The impact of NDVI on UHI intensity changes from negative to positive, and the impact of NDBI on UHI intensity in central urban area is weakened during 2001-2018. Social-economic factors have a greater impact on new urban area than on central urban area. These findings show the effects and the explanatory power changes of driving factors during 18 years, which can provide a better understanding of the formation and development of UHI and support for the future urban planning of Wuhan.

Optimization Methods of Urban Green Space Layout on Tropical Islands to Control Heat Island Effects

With the rapid increase in demand for the construction and development of island cities in the South China Sea, the urban heat island phenomenon in such cities should become a key factor to be considered in future urban planning. This paper took Sanya, China as a typical case, and long-term field experiments were conducted in the Mangrove Bay Area in summer and winter. An innovative urban green space cooling model was proposed, using the “green space cooling index” to quantitatively characterize the green space cooling effect, and aiming to minimize the intensity of urban heat islands. This paper studied the optimization method of green space planning and layout under the constraint of a centralized green space total area. Moreover, a genetic algorithm was adopted to optimize the calculation and the layout of the urban green space. The experimental results showed that the urban heat island intensity was more significant at night and was less effective in the daytime during summer. In winter, the urban heat island intensity had a greater effect in the daytime and was less influential at night. Finally, optimization results indicated that the average urban heat island intensity in summer was reduced by 8.8% under the optimal layout urban green space of 0.025 km2. The maximum reduction in heat island intensity occurred at 7:00 am (0.48 °C). When 0.0625 km2 urban green space was planned, the average urban heat island intensity index in summer was reduced to 0.27 °C, with a decrease of 20.5%.

Environmental co-benefits of urban design to mitigate urban heat island and PM2.5 pollution: Considering prevailing wind’s effects

The impact of PM2.5 pollution and urban heat island (UHI) on sustainable urban development and human health has been a major concern for governments. Based on Computational Fluid Dynamics (CFD) simulation and on-site monitoring, this study investigated the airflow velocity, PM2.5 concentration and urban heat island intensity (UHII) distribution in the urban area at different prevailing wind directions, from the perspective of urban design. In order to validate the accuracy of CFD simulation results, on-site monitoring of temperature and airflow velocity was conducted on the roof of a building. A low-dimensional model was adopted to improve the efficiency of CFD data analysis. Moreover, based on the results of the low-dimensional model, PM2.5 concentration and UHII in urban areas at different prevailing wind directions were assessed by clustering analysis. The findings showed that when α = 0° and 90°, the average PM2.5 concentration was 28.9–56.8% (8.76–27.66 μg/m³) lower and the average UHII was 23.4–34.2% (0.8–1.15°C) higher, compared to α = 30°, 45° and 60°. Meanwhile, the downwind area suffers from more serious PM2.5 pollution and UHII than the upwind area. These findings could potentially provide a guide for future building/urban design to improve the urban environment from the perspective of building and road construction.

Environmental impact and energy performance of groundwater heat pumps in urban retrofit

Increasing efforts are addressed to improve heating, ventilation and air conditioning systems to achieve the decarbonization goal also in the building sector. But less attention is actually devoted to their impact on the urban heat island (UHI) phenomenon. Starting from the UHI assessment and its impact on building heating and cooling demand, a performance comparison is presented between groundwater heat pumps (GWHP) supplied by a district network and air source heat pumps (ASHP_1). Hybrid systems with small ASHPs and condensing boilers (ASHP_2) are also considered. An urban area, network and heat pumps were modeled for this study. In summer, the removal from the urban area of the heat dissipated by condensers thanks to GWHPs reduces the average UHI intensity with ASHPs by 45% and the relative cooling demand increment by 42.6%. A more favorable temperature of the groundwater than outside air permits a net superiority of the GWHP efficiency. At annual level, the GWHP provides energy savings of 27% and 34.5% and CO2 emission reductions of 27% and 39.5% compared to ASHP_1 and ASHP_2 respectively. The UHI mitigation to improve comfort and resilience in urban areas is an important added value for the contribution to decarbonization that a GWHP network can provide.

Empirical evidence on the impact of urban overheating on building cooling and heating energy consumption

SummaryA primary contributor to urban overheating is the urban heat island (UHI) formed due to increased urbanization. The adverse effects of UHI on building energy use are substantial and well documented. However, such effects are typically demonstrated through numerical simulations which are susceptible to modeling uncertainties and lack of validation resulting in a pressing research gap. Here, for the first time, we conduct a large-scale assessment to demonstrate the devastating impact of UHI on building energy consumption using real building energy use data. We find empirical evidence correlating UHI with building energy use; changes in average UHI intensity of 0.5 K correspond to an increase in monthly cooling energy consumption in a range of 0.17 kWh/m2–1.84 kWh/m2. The study validates theoretical evidence on the impact of UHI on building energy and proposes a highly innovative methodology to assess the impact of overheating on the energy balance of cities.

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.

Improving the accuracy of simplified urban canopy models for arid regions using site-specific prior information

An overly complex urban climate/energy model would not be of much practical use in a decision support setting where a large number of year-long simulations are often necessary. While detailed modeling of urban momentum/energy exchanges can be attempted via Computational Fluid Dynamics (CFD) or mesoscale modeling, conducting multiple full year simulations in a design optimization or sensitivity analysis context is practically impossible. Furthermore, CFD models often do not consider climate/building energy exchanges. To address these limitations, standalone Urban Canopy Models (UCMs) have been developed, attempting to replace the full-fledged atmospheric representation with a computationally light equivalent. In this study, we investigate the impact of several modifications to a standalone Single-Layer Urban Canopy Model (SLUCM) for an arid region based on the prior availability of site-specific information. The suggested improvements are portable to SLUCM schemes incorporated within mesoscale models. The SLUCM will undergo several improvements and each variant will be evaluated based on its ability to predict UHI intensity and air-conditioning energy demand. Three original SLUCM improvements are covered in the present study. (1) We use actual radiation parameters instead of those generated for idealized geometries. It is shown that, in the absence of this improvement, standard UCMs can underestimate the average urban heat island intensity by 5% if using the Town Energy Balance (TEB) radiation scheme or overestimate it by 7% if using the Square Prism Urban Canopy (SPUC) radiation scheme. (2) We use the results of a prior steady-state RANS (Reynolds-Averaged Numerical Simulation) simulation to replace some of the default morphological parameters of the UCM by the more accurate values derived from the RANS results. It is shown that, in the absence of this improvement, standard UCMs using default empirical relations can overestimate the average urban heat island intensity by up to 22%. (3) Instead of using the empirically calculated default value of the urban canyon wind speed, we estimate it directly from the concomitant rural value using a regression model trained by historical measurements. It is shown that, in the absence of this improvement, standard UCMs can underestimate the average canyon wind velocity by more than 12%, although the other indicators (UHI, cooling demand) are not significantly affected.

Urban Heat Island in Moscow at different heights, depths and on the surface

The urban heat island (UHI) in Moscow was for the first time studied not only at the ground air level, but also at different heights, depths and on the surface using stationary, radiosonde and satellite data. Long-term dynamics of the UHI intensity in the ground air layer has been estimated since the end of the 19th century both as traditional ‘maximal intensity’ (the difference between the city centre and rural zone), and as ‘average intensity’ (the difference between all urban and all rural stations). In recent years they have been 2.0 and 1.0 ºC, respectively. The quasi-stabilization of both parameters in the second half of the 20th century was probably the result of extensive city growth at that time; the new increase in the UHI intensity seems to be connected with the densification of urban development and heat sources in the last 20 years. The mean daily vertical extension of the UHI in the atmosphere is approximately 300 m. In the upper soil layer (up to 160 cm deep) the maximal UHI intensity was about 1.6-1.7 ºC half a century ago. The average UHI intensity at the field of the surface temperature in recent years is 2.7 ºC.

Influence of synoptic scale atmospheric circulation on the development of urban heat island in Prague and Bucharest

This study has analysed the development of the urban heat island (UHI) under various synoptic scale atmospheric circulation for two large cities – Prague in central Europe and Bucharest in south-eastern Europe, including seasonal differences and long-term changes. At the best of our knowledge, it is the first comparison between two European cities from this perspective. Analysis was conducted on the base of minimum air temperature data from pairs of urban and peri-urban stations. The average UHI intensity is 2.3 °C for Prague and 1.8 °C for Bucharest, it exceeds 4 °C in 6–10% of cases, and the highest values occur in August in both cities. The annual course of monthly mean values of UHI intensities has higher amplitude in Bucharest (1.2 °C) than Prague (0.6 °C). Synoptic scale circulation is classified according to mean sea level pressure data from ECMWF Era-Interim reanalysis using cost733class software. The results show that UHI is more intense under anticyclonic situations with southern winds in the both cities. Over 1981–2016, we found that the UHI intensity followed statistically significant increasing trend, much larger trend for Bucharest than Prague (3.3 °C vs. 1.3 °C / 100 years).

A Statistical–Dynamical Downscaling for the Urban Heat Island and Building Energy Consumption—Analysis of Its Uncertainties

AbstractHigh-resolution maps of the urban heat island (UHI) and building energy consumption are relevant for urban planning in the context of climate change mitigation and adaptation. A statistical–dynamical downscaling for these parameters is proposed in the present study. It combines a statistical local weather type approach with dynamical simulations using the mesoscale atmospheric model Meso-NH coupled to the urban canopy model Town Energy Balance. The downscaling is subject to uncertainties related to the weather type approach (statistical uncertainty) and to the numerical models (dynamical uncertainty). These uncertainties are quantified for two French cities (Toulouse and Dijon) for which long-term dense high-quality observations are available. The seasonal average nocturnal UHI intensity is simulated with less than 0.2 K bias for Dijon, but it is overestimated by up to 0.8 K for Toulouse. The sensitivity of the UHI intensity to weather type is, on average, captured by Meso-NH. The statistical uncertainty is as large as the dynamical uncertainty if only one day is simulated for each weather type. It can be considerably reduced if 3–6 days are taken instead. The UHI reduces the building energy consumption by 10% in the center of Toulouse; it should therefore be taken into account in the production of building energy consumption maps.

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

Abstract 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.

The fine-scale spatial variation of mortality risk attributed to urban heat island effect in Guangzhou, China

TPS 661: Climate change: temperature effects 1, Exhibition Hall, Ground floor, August 26, 2019, 3:00 PM - 4:30 PM Background: In the context of global warming and accelerated urbanization, the urban heat island (UHI) effect is becoming obvious, especially in large cities. From a health perspective, the UHI effect increases the risk of heat-related mortality and morbidity. However, previous studies focused on the heat-related mortality variation between different cities, and lack of directly quantified the magnitude of the UHI on mortality within a city. Methods: We first used the k-means algorithm to cluster 161 streets in Guangzhou into 105 small-areas, due to the limited number of deaths in some streets. The inverse distance weight interpolation method was used to obtain the average daily temperature in each small area from 2011 to 2017, and the distribution lag nonlinear model was applied to investigate the heat-related risk in the central small-areas (68/105). Based on the UHI intensity, attributable fraction and the number of mortalities from UHI effect in each central small-areas were calculated during high-temperature season (June-September). Results: The daily average UHI intensity (UHIi) in Guangzhou is 0.71±0.41°C (range: -0.57 to 2.26 °C). Among central small-areas, the daily average UHIi ranges from 0.10±0.26 °C to 1.13±0.34°C. During high-temperature season, the attributable fraction (AF) and attributable number (AN) of mortalities resulting from UHI were1.04% or 629 cases in the central city, with the variation of AF and AN ranging from 0.22% to 10.12% or 2 to 121 cases in different central small-areas. Conclusion: UHIi and its attributable fraction or the number of mortalities were found to be spatial variation, which make the geography-targeted UHI effect reduction strategy be important for improving public health in the climate chenage scenarios.

Investigating urban heat island intensity in Istanbul

We analyzed the annual, monthly, and seasonal variations of urban heat island (UHI) intensity in Istanbul by using meteorological data measured for the period of 1960–2012 at six stations. The UHI on minimum temperature is found to be positive for all seasons, and the average UHI intensity clearly indicates seasonal changes, strongest in summer and weakest in winter. The results demonstrated increase of night time UHI intensity with 0.41–0.50 °C/decade and decrease of daytime UHI intensity with 0.13–0.18 °C/decade at the urban sites. The UHI strengthened with the expansion of the city due to increased population. The influences of meteorological variables on seasonality of the UHI intensity are examined for the days categorized depending on wind, cloud cover, and precipitation values. It is found that the UHI intensity decreases with increasing wind speed and cloud cover. The integrated response of the city atmosphere to wind speed changes differ such that daytime UHI in urban atmosphere intensifies rapidly from calm conditions to the wind speeds of 2–3 m/s, then slightly increases until 4–5-m/s wind speeds and starts to decline afterwards. On the other hand, the nighttime UHI intensities in urban sites continuously decline with the same rate until the wind speeds reach to 5–6 m/s. The difference of daytime UHI between rainy summer days and dry days is around 1 °C which is almost independent of the precipitation amount. Both nighttime and daytime UHI intensities depend on the season and site range approximately between 0.24 and 1.74 °C and − 0.62 and 2.61 °C, respectively. However, the UHI based on minimum temperature for the selected dry days with low wind and clear sky conditions increases to 1.70–3.08 °C. Land surface data from Moderate-Resolution Imaging Spectroradiometer (MODIS) Aqua and Terra show areal extension of the UHI through the north along the Bosphorus between 2000 and 2012, especially in the night observations. The continuous increase of built-up areas, paved roads, and decrease of green areas caused the growth of UHI intensity. The estimated UHI based on land surface temperature (LST) at the most urbanized locations of Istanbul reach to 8 °C for daytime and 6 °C for nighttime.

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.