Revealing the response of urban heat island effect to water body evaporation from main urban and suburb areas

Under the background of global warming, interaction between heat waves (HWs) and urban heat island (UHI) has led to trends of increase in the intensity, frequency, and duration of extreme heat events in urban areas, seriously threatening the health of urban populations. Taking Guangzhou (a tropical megacity in China) as an example, this study used automatic weather station data and ERA5 reanalysis data to explore the interaction between HWs and UHI, and to elucidate the effects of wind speed and local climate zones (LCZs) on such interaction. Results revealed obvious HWs–UHI interaction in Guangzhou, whereby HWs induces an amplification effect on UHI intensity (UHII) that was most significant at night. In the main urban area, UHII and HWs both weakened with increasing wind speed, indicating that low wind speeds contribute to increased occurrence of HWs and enhancement of UHII. Differently, in some areas peripheral to the main urban area, the UHII at medium wind speeds was stronger than that at low wind speeds, which reflect the impact of heat advection from the urban center. For different LCZs in the main urban area, the strongest UHII, highest risk of HW occurrence, and most significant HWs–UHI interaction were found in the compact mid-rise buildings and compact low-rise buildings (LCZ2 and LCZ3, respectively), followed by the compact high-rise buildings (LCZ1), which was mainly affected by the shading effect of high-rise buildings. The weakest UHII and lowest risk of HW occurrence were found in open high-rise buildings and open mid-rise buildings (LCZ4 and LCZ5, respectively), which generally have good ventilation conditions. Our findings will help to understand urban warming and its association with UHI and HW events in tropical urban regions, which has implications for rational improvement of the urban thermal environment in other tropical urban regions globally.

Urban expansion has intensified the heat-island effect, and the negative impact on the natural environment has gradually become considerable. However, urban lakes can significantly alleviate the heat-island effect caused by urbanization. Based on four-phase multispectral remote-sensing images during 2005-2020, 17 lakes in the main and surrounding urban areas of Hefei, China, were selected as the objects of our research. Each lake's cooling intensity and distance were calculated; cooling-efficiency data for different lakes were compared and analyzed considering lake areas and regional differences. The following conclusions were drawn: (1) The mean temperature of the lake had a strong positive correlation with the cooling-intensity efficiency and the cooling-distance efficiency, and it was the leading influencing factor of the cooling-intensity efficiency and the cooling-distance efficiency. The mean explanation degree was as high as 63.33% and 51.70%, respectively. (2) The lake area and the distance from the lake to the city center had a negative correlation with the cooling-intensity efficiency and cooling-distance efficiency and were the secondary factors that affect the cooling-intensity efficiency and cooling-distance efficiency. (3) The lakes around the urban area were far away from the main urban area where the heat-island effect was most concentrated, the ability of absorbing the high surface temperature caused by the heat-island effect was limited, and the cooling-intensity efficiency and cooling-distance efficiency were reduced by ~ 6.6°C/km2 and ~ 607.47m/km2, respectively, compared with the lakes in the main urban area. (4) With urban expansion and the intensified urban heat-island effect, the cooling-intensity efficiency of lakes in the main urban area gradually increased, whereas the cooling-distance efficiency of lakes decreased.

To study the urban heat island (UHI) effect in the mountainous areas of Chongqing, the UHI indexes for the Chongqing urban agglomerations were investigated in the present study. This study is based on data from 34 national weather stations and more than 2000 regional automated weather stations in Chongqing, Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light data, and 30-m high-resolution land use data and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature remote sensing data for Chongqing in 2015. Moreover, the influences of three background temperature calculation methods on the UHI effect were compared. The results showed that, if only the land use data and the city clustering algorithm (CCA) were used to divide the urban and suburban areas, the strong UHI index of Chongqing exhibited an abnormal increase in the years with extremely high temperatures, and the corresponding divided suburban and urban areas had relatively large differences in altitudes, thereby overestimating the UHI index. Therefore, in the present study, a new method for dividing the urban and suburban areas based on the combined CCA and light intensity data and a division method with the altitudes calibrated on this basis were designed. Both methods were able to satisfactorily reduce the influence of extreme climate years and excessively large differences in altitudes on the UHI index calculations and provide a new approach for future studies of the UHI index for mountainous areas with large altitude differences.

Based on the land surface temperature (LST), the land cover classification map, vegetation coverage, and surface evapotranspiration derived from EOS-MODIS satellite data, and by the use of GIS spatial analytic technique and multivariate statistical analysis method, the urban heat island (UHI) spatial distribution of the diurnal and seasonal variabilities and its driving forces are studied in Beijing city and surrounding areas in 2001. The relationships among UHI distribution and landcover categories, topographic factor, vegetation greenness, and surface evapotranspiration are analyzed. The results indicate that: (i) The significant UHI occur in Beijing city areas in the four seasons due to high heat capacity and multi-reflection of compression building, as well as with special topographic features of its three sides surrounded by mountains, especially in the summer. The UHI spatial distribution is corresponding with the urban geometry structure profile. The LST difference is approximately 4-6℃between Beijing city and suburb areas, comparatively is 8- 10℃between Beijing city area and outer suburb area in northwestern regions. (ii) The UHI distribution and intensity in daytime are different from nighttime in Beijing city area, the nighttime UHI is obvious. However, in the daytime, the significant UHI mainly appears in the summer, the autumn takes second place, and the UHI in the winter and the spring seem not obvious. The surface evapotranspiration in suburb areas is larger than that in urban areas in the summer, and high latent heat exchange is evident, which leads to LST difference between city area and suburb area. (iii) The reflection of surface landcover categories is sensitive to the UHI, the correlation between vegetation greenness and UHI shows obviously negative. The scatterplot shows that there is the negative correlation between NDVI and LST (R2 = 0.6481). The results demonstrate that the vegetation greenness is an important factor for reducing the UHI, and large-scale construction of greenbelts can considerably reduce the UHI effect.

This study investigates the influence of land use and land cover change (LULCC) on urban heat island (UHI) effects in Zhengzhou, Henan, China, amid rapid urbanization and significant landscape transformations between 1993 and 2023. Employing remote sensing and geospatial analytical methods, we analyze the spatiotemporal dynamics of UHI intensity and its relationship with LULCC variables, including built-up areas, bare land, farmlands, forests, water bodies, and grasslands/shrubs. Our findings reveal a dramatic increase in UHI intensity, rising from 1.02°C in 1993 to 2.49°C in 2023, closely associated with a 130.78% expansion of built-up areas (from 1,951.13 sqkm to 4,502.84 sqkm). Concurrently, vegetative cover has declined significantly, with forests and farmlands decreasing by 43.37% and 70.90%, respectively. Geodetector analysis stresses the role of built-up areas as the primary driver of UHI, with a strong positive correlation with UHI (R = 0.729). Conversely, farmlands (R = −0.891) and forests (R = −0.962) demonstrate notable negative correlations, highlighting their critical cooling functions. K-means clustering analysis identifies spatial heterogeneity in UHI effects, with densely built-up clusters exhibiting the highest UHI intensities, whereas vegetated and water-dominated clusters exhibit significantly lower values. These findings emphasize the detrimental impact of urbanization on local thermal dynamics while emphasizing the importance of preserving green spaces and water bodies in mitigating UHI effects. Our standpoints drive the urgent need for sustainable land-use policies that integrate green infrastructure into urban planning frameworks. These insights are crucial for fostering climate-resilient cities in the face of ongoing urbanization and climate change.

<h3>Abstract</h3> Urban heat islands, where temperatures are elevated relative to non-urban surrounds, are near-ubiquitous in cities globally. Yet, the magnitude and form of urban heat islands in the tropics, where heat has a large morbidity and mortality burden, is less well understood, especially for socioeconomically diverse communities such as those living in urban informal settlements. We utilised 29 years of Landsat satellite-derived surface temperature, corroborated by <i>in situ</i> measurements, to provide a detailed spatial and temporal assessment of urban heat islands in Makassar, Indonesia, a city that is representative of rapidly growing urban settlements across the tropics. We did so with explicit consideration of vulnerable communities living informally. Our analysis identified surface urban heat islands of up to 9.2 °C in long-urbanised parts of the city and 6.3 °C in informal settlements, the seasonal patterns of which were driven by change in non-urban areas rather than in urban areas themselves. In recently urbanised areas, the majority of urban heat island increase occurred before areas became 50% urbanised. As tropical cities continue to expand we expect that urban heat islands will develop quickly as land is urbanised, whereas the established heat island in long-urbanised areas will remain stable in response to city expansion. Green and blue space protect some informal settlements from the worst urban heat islands and maintenance of such space will be essential to mitigate the growing heat burden from urban expansion and anthropogenic climate change. We advocate for green space to be prioritised in urban planning, redevelopment and informal settlement upgrading programs, with consideration of the unique environmental and socioeconomic context of tropical cities. <h3>Highlights</h3> Long-term, fine-scale data are essential to understand the dynamics of urban heat Surface heat islands reached 9.2 °C in the urban core, 6.3 °C in informal settlements <i>In situ</i> data support the use of remote sensing for heat island characterisation The majority of heat island growth occurred before land was 50% urbanised Green and blue space can mitigate heat in informal settlements

Urban Heat Island (UHI) effects adversely impact weather, air quality, and climate. Previous studies have attributed UHI effects to localized, surface processes. Based on an observational and modeling study of an extreme UHI (heat wave) episode in the Baltimore metropolitan region, we find that upstream urbanization exacerbates UHI effects and that meteorological consequences of extra‐urban development can cascade well downwind. Under southwesterly wind, Baltimore, MD, experienced higher peak surface temperatures and higher pollution concentrations than did the larger urban area of Washington, DC. Ultra‐high resolution numerical simulations with National Land Cover Data (NLCD) of 2001 show a nonlocal, dynamical contribution to UHI effects; when the upstream urban area is replaced by natural vegetation (in the model) the UHI effects could be reduced by more than 25%. These findings suggest that judicious land‐use and urban planning, especially in rapidly developing countries, could help alleviate UHI consequences including heat stress and smog.

A new parameterization of urban areas in the Community Climate System Model version 4 (CCSM4) allows for simulation of temperature in cities where most of the global population lives. CCSM4 Coupled Model Intercomparison Project phase 5 (CMIP5) simulations [Representative Concentration Pathway (RCP) 2.6, 4.5, and 8.5] are analyzed to examine how urban and rural areas might respond differently to changes in climate. The urban heat island (UHI), defined as the urban minus rural air temperature, is used as a metric. The average UHI at the end of the twenty-first century is similar to present day in RCP2.6 and RCP4.5, but decreases in RCP8.5. Both the daytime and nocturnal UHIs decrease in RCP8.5, but the decrease in the daytime UHI is larger and more uniform across regions and seasons than in the nocturnal UHI. This is caused by changes in evaporation that warm the rural surface more than the urban. There is significant spatial and seasonal variability in the response of the nocturnal UHI caused mainly by changes in the rural surface. In Europe, the response to climate change of rural leaf–stem area in summer and clouds and rural soil moisture in winter explains the majority of this variability. Climate change increases the number of warm nights in urban areas substantially more than in rural areas. These results provide evidence that urban and rural areas respond differently to climate change. Thus, the unique aspects of the urban environment should be considered when making climate change projections, particularly since the global population is becoming increasingly urbanized.

Global Warming is a major environmental problem that all kind of organisms has been affected at present. Urban Heat Island (UHI) is one of primary impacts of Global Warming. UHI is a phenomenon that the temperature of urban area is higher than surrounding rural areas or suburban areas. This increasing trend of temperature in urban areas affects many environmental entities such as air quality, water resources, habitats behaviors, climate changes. The most remarkable incident that relate with UHI, is the difference of thermal properties of the surfaces. Many countries experience the consequences of Urban Heat Islands in many aspects such as economic, health, social and environmental affects. Thus to mitigate such impacts of UHI, it is very important to identify the main reasons behind this. In this paper UHIs in Colombo, Gampaha Districts and the relationship between UHI and vegetation cover were analyzed based on Landsat 8, 30 m resolution data. Land Surface Temperature was derived from Landsat thermal Infrared band through several equations of United State Geological Surfay (USGS) guidelines using Arc GIS 10. Conversion of Digital Number (DN) values to Top of Atmosphere (TOA) Radiance, Conversion of TOA Radiance to Satellite Brightness temperature and final calculation of Land Surface Temperature considering land surface emissivity are the steps that had been done for the analysis. Vegetation cover was derived by using vegetation index with the Red and Near Infra Red bands. The result shows that the land high surface temperature directly relates with the urbanized regions where vegetation cover is very less. High temperature difference could be identified that cause to arise the urban heat island effects in Colombo & Gampaha districts. There is a strong linearly negative correlation with correlation coefficient value of -0.742 between land surface temperature and vegetation cover. 78.8 km2 (including water) of total area had been identified as NDVI value less than 0.1. And extent of high temperature area was 74.12 km2 where temperature more than 27˚C at 10.22 am. The area in temperature range of 25-27 was 464.95 km2 and area in NDVI value range 0.1-0.2 was 333.04 km2. 1471.1 km2 was identified as NDVI value between 0.3-0.4 and the area at low temperature was 1529 km2 where temperature less than 25˚C. According to this results, high temperature at non-vegetated areas and low temperature at vegetated areas could be noted very clearly. This is probably due to the ecological function of vegetation that lay down the surface temperature from high evapotranspiration. Vegetated areas are mostly sensed with surface temperature. Thus research output can be useful for policy-makers and planners of development projects such as Western province Megapolis project as well as for general public to understand the urban heat island effects and importance of vegetation cover to mitigate such impacts. Keywords: Urban heat island, Vegetation, NDVI, Arc GIS, Landsat, Sri Lanka

Based on China’s fifth population survey (2000) data and homogenized annual mean surface air temperature data, the urban heat island (UHI) effect on the warming during the last 50 years in China was analyzed in this study. In most cities with population over 104, where there are national reference stations and principal stations, most of the temperature series are inevitably affected by the UHI effect. To detect the UHI effect, the annual mean surface air temperature (SAT) time series were firstly classified into 5 subregions by using Rotated Principal Components Analysis (RPCA) according to its high and low frequency climatic change features. Then the average UHI effect on each subregion’s regional annual mean STA was studied. Results indicate that the UHI effect on the annual mean temperatures includes three aspects: increase of the average values, decrease of variances and change of the climatic trends. The effect on the climatic trends is different from region to region. In the Yangtze River Valley and South China, the UHI effect enhances the warming trends by about 0.011 °C/decade. In the other areas, such as Northeast, North-China, and Northwest, UHI has little impact on the warming trends of the regional annual temperature; while in the Southwest of China, introducing UHI stations slows down the warming trend by −0.006 °C/decade. But no matter what subregion it is, the total warming/cooling of these effects is much smaller than the background change in regional temperature. The average UHI effect for the entire country, during the last 50 years is less than 0.06 °C, which agrees well with the IPCC (2001). This suggests that we cannot conclude that urbanization during the last 50 years has had much obvious effect on the observed warming in China.

Two Landsat scenes (acquired on 21 May 1986 and 19 May 2000) were used to examine differences in surface temperature inside and outside the city of Abu Dhabi and to examine a potential relationship between vegetation abundance and drop in temperatures. Land cover maps of Abu Dhabi city and its surroundings spanning the period 1986–2000 were created using multispectral classification, and vegetation abundance maps using the vegetation fraction index and surface temperature maps from Landsat were created to study their spatial relationships using GIS-based multivariate statistical analysis. Differences in surface temperature between urban areas and their non-urban surroundings were also studied to assess any urban heat island (UHI) effect. A map showing the magnitude of UHI effect was created and linked to the vegetation abundance map. Results show that the UHI effect in major UAE urban centres is minimal; however, more investigation is needed to confirm this hypothesis for other UAE cities.

Inter-seasonal characterization and correlation of Surface Urban Heat Island (SUHI) and Canopy Urban Heat Island (CUHI) in the urbanized environment of Delhi

The global rise of urbanization has led to the formation of surface urban heat islands and surface urban cool islands. Urban heat islands have been shown to increase thermal discomfort, which increases heat stress and heat-related diseases. In Kuwait, a hyper-arid desert climate, most of the population lives in urban and suburban areas. In this study, we characterized the spatial distribution of land surface temperatures and investigated the presence of urban heat and cool effects in Kuwait. We used historical Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra satellite 8-day composite land surface temperature (LST) from 2001 to 2017. We calculated the average LSTs of the urban/suburban governorates and compared them to the average LSTs of the rural and barren lands. We repeated the analysis for daytime and nighttime LST. During the day, the temperature difference (urban/suburban minus versus governorates) was −1.1 °C (95% CI; −1.2, −1.00, p < 0.001) indicating a daytime urban cool island. At night, the temperature difference (urban/suburban versus rural governorates) became 3.6 °C (95% CI; 3.5, 3.7, p < 0.001) indicating a nighttime urban heat island. In light of rising temperatures in Kuwait, this work can inform climate change adaptation efforts in the country including urban planning policies, but also has the potential to improve temperature exposure assessment for future population health studies.

The Mediterranean is recognized among the most responsive regions to climate change, with annual temperatures projected to increase by 1–5 °C until 2100. Large cities may experience an additional stress discomfort due to the Urban Heat Island (UHI) effect. In the present study, the WRF-ARW numerical weather prediction model was used to investigate the climate change impact on UHI for two Mediterranean cities, Rome and Thessaloniki. For this purpose, three 5-year time-slice simulations were conducted (2006–2010, 2046–2050, 2096–2100) under the Representative Concentration Pathway (RCP) 8.5 emission scenario, with a spatial resolution of 2 km. In order to comprehensively investigate the urban microclimate, we analyze future simulation data across sections crossing urban/non-urban areas, and after grouping them into three classes depending on the location of the grid cells. The urban areas of both cities present increased average minimum temperature (Tmin) in winter/summer compared to other rural areas, with an UHI of ~+1.5–3 °C on average at night/early morning. Considering UHI under future climate change, we found no significant variations (~±0.2 °C). Finally, we found that the numbers of days with Tmin ≥ 20 °C will mostly increase in urban coastal areas until 2100, while the largest increase of minimum Discomfort Index (DImin) is expected in urban low-ground areas.

Increasing urbanization and climate change challenges are leading to relevant environmental, economic and social pressures on European cities. These include increasing flood hazards and the urban heat island (UHI) effect. Nature-Based Solutions (NBS) are increasingly recognized within strategies to provide multiple ecosystem services to mitigate existing risks and pressures, as well as to make cities more resilient and livable. Although being increasingly addressed within the literature, NBS implementation on the ground still faces many technical and financial barriers. This paper aims to test the potential of selected NBS in mitigating the effects of identified climate change risks, i.e., the UHI effect and urban floods, in the Turin urban area (north-western Italy). Four different intervention NBS-based scenarios are developed. The supply of ecosystem services by NBS in each scenario is assessed using InVEST models and the effectiveness of NBS investments is analyzed by calculating and comparing the associated costs and benefits. Different results in terms of effectiveness and economic viability are observed for each scenario and each NBS. Flood risk mitigation oriented NBS seem to have the most impact, in particular forested green areas and retention ponds. The results are relevant to suggest policy mix strategies to embed NBS in city planning.