Urban Heat Research Articles

Seasonal environmental cooling benefits of urban green and blue spaces in arid regions

Green and blue spaces are vital for mitigating urban heat island impacts but are poorly studied in arid regions. In this study, we quantify monthly and seasonal cooling for five contrasting types of green and blue infrastructure (GBI): rivers, lakes, "captured" agricultural areas, urban parks, and golf courses in the Cairo and Giza provinces of Egypt. Using Landsat-8 images of Land Surface Temperature (LST) we assessed change in LST along bisecting transects and in circle plots for three replicates of each GBI type, in each of four seasons. Cooling was greatest in summer for all GBI types. Cooling differentials of LST were greater for water bodies than for green spaces. Ordered by increasing cooling potential (May LST cooling) they were: Agricultural areas (3.3 °C), Golf courses (4.3 °C), Parks (4.4 °C), Lakes (8.2 °C) and Rivers (12.2 °C). The cooling effects extending into adjacent buffer areas were greatest for blue spaces like rivers and lakes. This paper provides the first data for cooling by less-studied GBI types in arid regions, such as golf courses and urban agriculture. It provides information to support city planners to embrace green and blue spaces within metropolitan areas and to protect them from urban sprawl.

Evaluating Urban Heat Island Mitigation Strategies in Rajshahi, Using ENVI-Met: A Remote Sensing Approach

The Urban Heat Island (UHI) effect is a critical environmental challenge in the 21st century, intensified by rapid urbanization and industrialization. This study focuses on Rajshahi, a rapidly urbanizing city in Bangladesh, where the UHI effect has already begun to manifest significantly. Utilizing ENVI-met software, a comprehensive analysis was conducted to evaluate the effectiveness of urban vegetation strategies, such as green roofs and street planting, in mitigating local temperatures and improving outdoor thermal comfort in Rajshahi's Central Business District. The findings reveal that these mitigation strategies can reduce air temperatures by up to 10 Kelvin, providing substantial cooling benefits. This research highlights the importance of integrating green infrastructure into urban planning to combat the UHI effect, enhance sustainability, and improve the overall livability of urban environments. The study offers valuable insights and practical recommendations for urban planners and policymakers, aiming to foster resilient and sustainable urban development in rapidly growing cities like Rajshahi.

Mitigating Urban Heat Islands in the Global South: Data-driven Approach for Effective Cooling Strategies

Mitigating Urban Heat Islands in the Global South: Data-driven Approach for Effective Cooling Strategies

Towards more equitable cooling services of urban parks: Linking cooling effect, accessibility and attractiveness

Global warming and rapid urbanization have caused frequent occurrences of heat waves and urban heat island effect, presenting a significant threat to health of urban residents. Researches have indicated that cooling services provided by parks are essential in alleviating impact of heat wave events and urban heat island effect. However, previous researches on park cooling services center around cooling effect, with a lack of exploration regarding the fairness of such services. To fill this gap, this study quantifies the level of equity in cooling services in 18 parks in the core area of Hangzhou. Through this study, we hope to clarify the current situation of fairness of cooling services in urban parks and provide fairer park cooling services through scientific and reasonable park layouts. This will alleviate the threat of rapid urbanization and climate change to urban residents, and make the urban environment develop in a more livable direction. We assessed the cooling effect using remote sensing and the ArcGIS platform to screen parks with cooling effect and to quantify their cooling service efficiency. We utilized spatial network analysis to quantify the accessibility and origin-destination matrix data to quantify the attractiveness to reflect the level of park cooling services. The results reveal that 18 parks exhibit a noticeable cooling effect, albeit with variations observed among parks. The percentage of urban parks with low accessibility is 77.80%, indicating that the distribution of accessible space presents an uneven status quo. In addition, 72.20% of parks have low attractiveness of cooling services, indicating that some parks have insufficient attractiveness of cooling services. Based on each indicator of cooling services, we categorize urban parks into four types based on supply and demand, and propose adaptive planning measures and intervention strategies to provide a reference for equitable distribution of cooling services in urban parks.

Sampling Error of Mean and Trend of Nighttime Air Temperature at Weather Stations Over China Using Satellite Data as Proxy

AbstractMeteorological observations of surface air temperature have provided fundamental data for climate change detection and attribution. However, the weather stations are unevenly distributed, and are still very sparse in remote regions. The possible sampling error is well known, but not well quantified because we are lack of the adequate and regularly distributed measurements. The high resolution of satellite land surface temperature retrieval during night time provide a nice proxy for near surface temperature as both temperatures controlled by surface longwave radiative cooling and the nocturnal temperature inversion depress land‐atmosphere turbulent exchange. The sampling error of mean value and trend were assessed by comparing station point measurements (pixel of ∼0.01°) with grid (1°) mean and national mean from 2001 to 2021. This method permits us to make the first assessment of under‐sampling error and spatial representative error on both national mean and trend of air temperature during nighttime collected at ∼2,400 weather stations over China. The sampling error in national mean temperature is more than 3°C. The under‐sampling error due to lack of observation explains two thirds and the spatial representative error due to the difference between station and grid/regional mean elevation contribute the other one third. The sampling error in trend account for one third of the national mean trend. The urban heat island effect associated with urbanization around the weather stations (spatial representative error) can explain four fifths of the sampling error in trend, which is consistent with existing studies based on air temperature collected at paired weather station.

Radiation cooling textiles countering urban heat islands

Radiation cooling textiles countering urban heat islands

Research on the Spatial-Temporal Evolution of Changsha’s Surface Urban Heat Island from the Perspective of Local Climate Zones

Research on the Spatial-Temporal Evolution of Changsha’s Surface Urban Heat Island from the Perspective of Local Climate Zones

Effects of the Western Pacific Subtropical High on the urban heat island characteristics in the middle and lower reaches of the Yangtze River, China

The middle and lower reaches of the Yangtze River are frequently affected by the Western Pacific Subtropical High (WPSH) in summer. This leads to phenomena including air subsidence, high temperatures, low rainfall, and weak winds, all of which affect the urban heat island (UHI) effect. Currently, there are few studies on the influence of WPSH on the UHI effect. In this study, we analysed the temporal and spatial distributions of the influence of WPSH on the UHI effect by establishing two scenarios: with and without WPSH. We calculated the UHI intensity and the urban heat island proportion index (UHPI) to analyse the temporal and spatial distributions of the UHI effect. The geographical detector method was then used to analyse the factors influencing UHI. The results indicate the strong heat island effect during the day in provincial capitals and some developed cities. The area of high UHI intensity was larger under the influence of WPSH than in the years without WPSH. WPSH affected UHPI at both day and night, although the effect was more pronounced at night. The factors affecting daytime UHI intensity are mainly POP and NTL, O3 plays a large role in the years with WPSH control. The main factors affecting the UHI intensity at night are AOD, POP and NTL were mainly factors in the years without WPSH control, POP and WPSH were mainly factors in the years with WPSH control. The interactions of the factors are mainly POP and multi-factors during the daytime, and DEM and multi-factors during the nighttime. It was found that the UHI intensity was enhanced under the control of the WPSH, and the influencing factors of the diurnal UHI differed with and without the WPSH control, which ultimately provides realistic suggestions for mitigating the intensity of the UHI in areas affected by the WPSH.

Water retention and heat storage characteristics of phase change hydrogel in cooling pavement

Phase change hydrogel (PCH) combines the heat storage characteristics of phase change material with the water retention capacity of hydrogel, showing great potential in cooling pavement applications. This study aims to investigate the water retention and heat storage properties of PCH in cooling pavement, providing new insights for mitigating the urban heat island effect. Based on the principle of osmotic pressure, polyethylene glycol (PEG) solution was actively absorbed by superabsorbent polymers (SAP) to form stable PCH. By infusing the asphalt mixture skeleton with PCH-containing phase change grouting material (PCGM), a temperature-regulating phase change grouting pavement (PCGP) can be obtained. Morphological characterization showed that PCH was uniformly distributed in PCGM and effectively locked PEG during high temperature and water absorption/release processes without leakage. PCH imparted excellent water retention properties to PCGM, with a saturation water absorption rate of 44.1 %, which is 6.2 times higher than the control group, and a water retention rate of 34.31 % after heating at 60 °C for 12 hours. Furthermore, PCGM exhibited considerable heat storage performance, with a melting enthalpy of 15.74 J/g and a crystallization enthalpy of 12.07 J/g. Based on these, PCGP demonstrated outstanding temperature-regulating ability, reducing surface temperatures by 9.3 °C and 11.6 °C under dry and saturated conditions, respectively, compared to control pavement. In conclusion, this study provides a theoretical basis for the development of novel cooling pavement materials and shows great potential for its wide application in urban infrastructure construction.

Spatio-Temporal Heterogeneity of the Urban Heat Effect and Its Socio-Ecological Drivers in Yangzhou City, China

Rapid urbanization and land-use changes may affect the intensity of urban heat islands (UHIs). However, research on the eastern Chinese city of Yangzhou is lacking. Using land cover data and the InVest Urban Cooling model, this study evaluated the spatiotemporal heterogeneity of the UHI effect from 1990 to 2020 and its socioecological drivers in Yangzhou City. Landscape pattern indices such as patch area (CA), percentage of landscape (PLAND), number of patches, patch density, and aggregation index were created using Fragstats 4.2 software. Several social indicators, such as gross domestic product (GDP), night-light index, and population density, were considered to explore their correlation with UHI indicators. During the past three decades, rapid urbanization in Yangzhou has intensified the UHI effect, with the cooling capacity (cc park) and heat mitigation index (HMI) decreasing by ~9.6%; however, the mixed air temperature (T air) has increased by 0.14 °C. The main heat island areas are concentrated in southern Yangzhou, including the Hanjiang and Guangling districts, and have expanded over time. T air was positively correlated with GDP, night-light index, and population density. Moreover, for the impervious land use type, cc park and HMI were negatively correlated with CA and PLAND (p < 0.01). This study contributes to a deeper understanding of the dynamics of UHIs and provides valuable insights for policymakers, urban planners, and researchers striving to create sustainable and climate-resilient cities in Yangzhou.

Nature-Based Solutions Scenario Planning for Climate Change Adaptation in Arid and Semi-Arid Regions

Extreme climatic conditions cause a decrease in ecosystem services, the disruption of the ecological balance, and damage to human populations, especially in areas with socially vulnerable groups. Nature-based solutions applying blue-green infrastructure (BGI) against these negative impacts of climate change have an important role in planning sustainable cities. This study aims to identify priority areas and develop scenarios and strategies for spatial planning to understand the tradeoffs in approaches and to maximize the benefits of ecosystem services provided by BGI in cities with arid and semi-arid climates, using Phoenix, Arizona, a swiftly urbanizing city in the Sonoran Desert, as the study area. Using GIS-based multi-criteria decision-making techniques and the Green Infrastructure Spatial Planning model integrated with the city’s existing water structures, this study is conducted at the US census scale. The hotspots for BGI are mapped from the combined GIS-based multi-criteria evaluation and expert stakeholder-driven weighting. In the hotspots where priority areas for BGI in Phoenix are identified, the city center area with a high density of impervious surfaces is identified as the highest priority area. It is revealed that social vulnerability and environmental risks (flooding, heat) have a positive correlation in Phoenix, and stormwater management and the urban heat island are the criteria that should be considered first in BGI planning.

Optimizing Local Climate Zones through Clustering for Surface Urban Heat Island Analysis in Building Height-Scarce Cities: A Cape Town Case Study

Studying air Urban Heat Islands (AUHI) in African cities is limited by building height data scarcity and sparse air temperature (Tair) networks, leading to classification confusion and gaps in Tair data. Satellite imagery used in surface UHI (SUHI) applications overcomes the gaps which befall AUHI, thus making it the primary focus of UHI studies in areas with limited Tair stations. Consequently, we used Landsat 30 m imagery to analyse SUHI patterns using Land Surface Temperature (LST) data. Local climate zones (LCZ) as a UHI study tool have been documented to not result in distinct thermal environments at the surface level per LCZ class. The goal in this study was thus to explore relationships between LCZs and LST patterns, aiming to create a building height (BH)-independent LCZ framework capable of creating distinct thermal environments to study SUHI in African cities where LiDAR data are scarce. Random forests (RF) classified LCZ in R, and the Single Channel Algorithm (SCA) extracted LST via the Google Earth Engine. Statistical analyses, including ANOVA and Tukey’s HSD, assessed thermal distinctiveness, using a 95% confidence interval and 1 °C threshold for practical significance. Semi-Automated Agglomerative Clustering (SAAC) and Automated Divisive Clustering (ADC) grouped LCZs into thermally distinct clusters based on physical characteristics and LST data internal patterns. Built LCZs (1–9) had higher mean LSTs; LCZ 8 reached 37.6 °C in Spring, with a smaller interquartile range (IQR) (34–36 °C) and standard deviation (SD) (1.85 °C), compared to natural classes (A–G) with LCZ 11 (A–B) at 14.9 °C/LST, 17–25 °C/IQR, and 4.2 °C SD. Compact LCZs (2, 3) and open LCZs (5, 6), as well as similar LCZs in composition and density, did not show distinct thermal environments even with building height included. The SAAC and ADC clustered the 14 LCZs into six thermally distinct clusters, with the smallest LST difference being 1.19 °C, above the 1 °C threshold. This clustering approach provides an optimal LCZ framework for SUHI studies, transferable to different urban areas without relying on BH, making it more suitable than the full LCZ typology, particularly for the African context. This clustered framework ensures a thermal distinction between clusters large enough to have practical significance, which is more useful in urban planning than statistical significance.

Maternal And preGnancy hEalth duriNg elevaTed heAt – MAGENTA: Novel data linkages and methods to understand the impacts of climate change on deprived communities in Wales and London.

Background and ObjectivesThe health impacts from changing climate, including increasing frequency, severity, and duration of heat are projected to worsen. The MAGENTA study will explore the impact of heat on pregnancy-related outcomes for deprived communities in Wales and London. ApproachMAGENTA will create linked data cohorts capturing some of the most deprived and diverse communities in Europe to analyse the impact deprivation, ethnicity, heatwaves, and urban heat islands have on pregnancy-related health. A consented data-linked cohort of pregnant women will provide biological samples and undergo direct measurement of themselves and their home environments to understand the heat stress response of pregnant women not acclimatised to heat during their pregnancy. Core to the study is our public involvement strategy which includes pregnant women and women who have recently delivered a baby, co-producing the research and how results are communicated. ResultsOur electronic cohorts cover >10 years of climate and health data and capture all births in Wales >300,000 and >1.1 million in London. We will present how the novel data linkages can work in multiple trusted research environments, approaches for sharing methods in geospatial modelling and statistics across the project and preliminary findings from the study. Findings and ImplicationsThe MAGENTA study will help inform expectant parents, families and policy makers how to prepare for climate change in temperate regions. The comparison between different populations in Wales and London will give insight on where policies and interventions can be generally applied and where they need to be contextually adapted.

Assessing the impacts of vegetation loss and land surface temperature on Surface Urban Heat Island (SUHI) in Gazipur District, Bangladesh

Rapid replacement of vegetated land with impermeable land (built-up areas) is a major factor in the increase in Land Surface Temperature (LST), while increased LST worsens the temperature in cities and creates the Surface Urban Heat Island (SUHI) effect. The study aims to measure vegetation loss and Land Surface Temperature of the Gazipur district between 2000 and 2020 and explore the relationship among Normalized Difference Vegetation Index (NDVI), LST, and Urban Thermal Field Variance Index (UTFVI). The Landsat TM/OLI images with minimum cloud coverage have been used to derive different indices. The mean NDVI values are 0.21, 0.16, and 0.22 in 2000, 2010, and 2020 respectively which indicates a general improvement in the health of the vegetation. Besides, the highest LST values throughout 20 years, represent a general increasing trend. As a consequence, different land covers have experienced fluctuations in mean temperature. The result shows that the mean temperature of bare land, buildup, vegetation, and waterbody has increased by 4.77, 2.01, 2.25, and 2.23 °C respectively from 2000 to 2020. The strongest SUHI zone’s area grew by about 28% between 2000 and 2020. Additionally, the highest index value of UTFVI was 0.39 in 2000 and grew to 0.43 in 2010. It changed to 0.49 in 2020, or ten years later. Thus, the SUHI effect’s increasing intensity is visible. Also, regression analysis has been used to explore the correlation between the derived indices. Stakeholders from different sectors like urban planners and policymakers may take insights from this study to work to promote greenery for a healthy urban environment.

Quantifying urban climate response to large-scale forcing modified by local boundary layer effects

Over the past two decades, the joint manifestation of global warming and rapid urbanization has significantly increased the occurrence of heatwaves and the formation of urban heat islands in temperate cities. Consequently, this synergy has amplified the frequency and duration of periods with tropical nights (TNs) in these urban areas. While the occurrences of such extreme events demonstrate irregular and nonlinear annual patterns, they consistently manifest a discernible rising decadal trend in local or regional climatic data. In urban regions situated amidst hilly or mountainous landscapes, changing wind directions—often associated with uphill or downhill thermal flows—profoundly impact the spread and dispersion of heat-related pollution, creating unique natural ventilation patterns. Using the Lausanne/Pully urban area in Switzerland as examples of hilly and lakeshore temperate cities, this study explores the influence of wind patterns and natural urban ventilation on the nonlinearity of recorded climatic data within an urban environment. This study integrates a mesoscale numerical weather prediction model (COSMO-1), a microscale Computational Fluid Dynamics (CFD) model, field observations, variational mode decomposition technique, and statistical analysis to investigate how wind speed and direction critically influence the nonlinearity of recorded long-term trends of extreme events, specifically focusing on the frequency and duration of TNs in lakeshore and hilly cities. The results strongly indicate a direct correlation between the frequency of TNs and the occurrence of specific moderate wind patterns. These wind patterns are exclusively captured by the microscale CFD model, unlike the mesoscale model, which neglects both urban morphology and complex hilly terrains. The impact of temporal and spatial variability of the wind field on long-term observations at fixed measurement stations suggests that caution should be exercised when relying on limited spatial measurement points to monitor and quantify long-term urban climate trends, particularly in cities located in complex terrains.

Remote Sensing Monitoring and Multidimensional Impact Factor Analysis of Urban Heat Island Effect in Zhengzhou City

In the 21st century, the rapid urbanization process has led to increasingly severe urban heat island effects and other urban thermal environment issues, posing significant challenges to urban planning and environmental management. This study focuses on Zhengzhou, China, utilizing Landsat remote sensing imagery data from five key years between 2000 and 2020. By applying atmospheric correction methods, we accurately retrieved the land surface temperature (LST). The study employed a gravity center migration model to track the spatial changes of heat island patches and used the geographical detector method to quantitatively analyze the combined impact of surface characteristics, meteorological conditions, and socio-economic factors on the urban heat island effect. Results show that the LST in Zhengzhou exhibits a fluctuating growth trend, closely related to the expansion of built-up areas and urban planning. High-temperature zones are mainly concentrated in built-up areas, while low-temperature zones are primarily found in areas covered by water bodies and vegetation. Notably, the Normalized Difference Built-up Index (NDBI) and the Normalized Difference Vegetation Index (NDVI) are the two most significant factors influencing the spatial distribution of land surface temperature, with explanatory power reaching 42.7% and 41.3%, respectively. As urban development enters a stable stage, government environmental management measures have played a positive role in mitigating the urban heat island effect. This study not only provides a scientific basis for understanding the spatiotemporal changes in land surface temperature in Zhengzhou but also offers new technical support for urban planning and management, helping to alleviate the urban heat island effect and improve the living environment quality for urban residents.

Defining and Verifying New Local Climate Zones with Three-Dimensional Built Environments and Urban Metabolism

The urban heat island (UHI) effect, where the temperature in an urban area is higher than in the surrounding rural areas, is becoming a major concern. The concept of a Local Climate Zone (LCZ) system was devised to provide an objective framework for UHI research, which allows for a microscale definition of the UHI effect within urban areas by considering ‘urban’ and ‘rural’ as a continuum versus a dichotomy. However, most LCZ types are classified only by surface structure and coverings, which seem irrelevant to climatological and microscale concepts. In addition, microclimate is influenced by urban metabolism related to human activities as well as structural effects, but the LCZ-classification system does not incorporate these functional concepts. Therefore, this study proposes a novel urban-classification system that addresses the limitations of the LCZ concept by quantifying structural and functional elements of the city at the pedestrian level using S-DoT sensors and semantic segmentation techniques. This study holds significance as it suggests a New-LCZ (N-LCZ) system to support the classification framework of highly valid urban types and follow-up studies related to the UHI. Moreover, the N-LCZ offers a regional urban-planning strategy for sustainable development through a more valid classification system.

Exploring the Cutting Process of Coaxial Phase Change Fibers under Optical Characterization Tests

Urban heat islands (UHI) are a growing issue due to urbanization, causing citizens to suffer from the inadequate thermal properties of building materials. Therefore, the need for climate-resistant infrastructure is crucial for quality of life. Phase change materials (PCMs) offer a solution by being incorporated into construction materials for thermoregulation. PCMs store and release heat as latent heat, adjusting temperatures through phase changes. Polymeric phase change fibers (PCFs) are an innovative technology for encapsulating PCMs and preventing leaks. This study produced PCFs via wet-spinning, using commercial cellulose acetate (CA, Mn 50,000) as the sheath and polyethylene glycol (PEG 2000) as the core. The PCFs were cut using a hot-cutting method at three different temperatures and washed with distilled water. Morphological analysis was conducted with a bright-field microscope, and chemical analysis was performed using Fourier transform infrared spectroscopy (FTIR) before and after controlled washing. Additionally, the washing baths were analyzed by UV-visible spectroscopy to detect PEG. The PCFs displayed a well-defined core-shell structure. Although some PEG 2000 leakage occurred in unsuccessful cuts, cuts at 50 °C showed sealed ends and less material in the baths, making it viable for civil engineering materials.

Global scale assessment of urban precipitation anomalies

Urbanization has accelerated dramatically across the world over the past decades. Urban influence on surface temperatures is now being considered as a correction term in climatological datasets. Although prior research has investigated urban influences on precipitation for specific cities or selected thunderstorm cases, a comprehensive examination of urban precipitation anomalies on a global scale remains limited. This research is a global analysis of urban precipitation anomalies for over one thousand cities worldwide. We find that more than 60% of the global cities and their downwind regions are receiving more precipitation than the surrounding rural areas. Moreover, the magnitude of these urban wet islands has nearly doubled in the past 20 y. Urban precipitation anomalies exhibit variations across different continents and climates, with cities in Africa, for example, exhibiting the largest urban annual and extreme precipitation anomalies. Cities are more prone to substantial urban precipitation anomalies under warm and humid climates compared to cold and dry climates. Cities with larger populations, pronounced urban heat island effects, and higher aerosol loads also show noticeable precipitation enhancements. This research maps global urban rainfall hotspots, establishing a foundation for the consideration of urban rainfall corrections in climatology datasets. This advancement holds promise for projecting extreme precipitation and fostering the development of more resilient cities in the future.

Seasonal variation in vegetation cooling effect and its driving factors in a subtropical megacity

The urban heat island (UHI) effect has become a global issue, attracting widespread attention in recent years. Urban vegetation is an effective way to mitigate UHI through evapotranspiration (ET). However, the seasonal variation in vegetation cooling effect and its driving factors have not been well investigated. Therefore, the seasonal UHI intensity (UHII) on typical clear days in 2021 was calculated for Shenzhen based on the land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The slope between UHII and vegetation coverage was then used to characterize the vegetation cooling effect. Results showed that: (1) there is a significant negative linear correlation between UHII and vegetation coverage, with slopes mostly less than −1 and coefficients of determination (R2) larger than 0.4. (2) The slopes varied seasonally, indicating a larger vegetation cooling effect during summer daytime. A 10 % increase in vegetation coverage can reduce the daytime UHII by 0.16 °C in January and 0.59 °C in June, while at nighttime, the cooling effect varied between 0.12 °C in January and 0.27 °C in June. The daytime and nighttime UHII for the whole year can be reduced by 0.43 °C and 0.24 °C, respectively. (3) The seasonal variation in vegetation cooling effects during the daytime can be largely explained by that of ET, which is mainly driven by leaf area index (LAI).