Urban Heat Research Articles

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).

Methodology to assess the impact of urban vegetation on the energy consumption of residential buildings. Case study in a Mediterranean city

The global growth of urban areas is unstoppable, and this growth is accompanied by an intensification of urban heat island effects, exacerbating the challenges of climate change and sustainable urban development in warm climates. In this context, understanding the intricate dynamics of these phenomena and their implications on the thermal behaviour of buildings becomes paramount. This study focuses on València, a Spanish city characterized by a Mediterranean climate, where the interplay between ground temperature variations, vegetation levels, and the thermal demands of buildings is investigated.Land surface temperature measurements derived from satellite data, specifically from the Landsat-8 mission, provide a valuable lens through which to assess the heat island effect. These measurements are harmonized with data collected from local weather stations to establish a robust foundation for evaluating the thermal dynamics of the urban environment. European standards, coupled with Geographic Information System technologies, enable the simulation of temperature variations, and facilitate a nuanced analysis of their impact on the thermal demands of a building.Moreover, recognizing the crucial role played by the urban climate in the influencing of heating and cooling needs, this study explores nature-based solutions implemented in València. By leveraging satellite-derived temperature and vegetation data over an extended period, it is possible to identify actions and elements that contribute positively to mitigating UHI effects and improving the overall climatic conditions. Results indicate that vegetation has a notable impact on local temperature, with distinct patterns observed in different seasons. The research incorporated the simulation of climate scenarios, introducing varying levels of vegetation. Results demonstrated a substantial reduction in cooling demand, particularly during the summer months. Buildings with a lower exterior surface-to-volume ratio exhibited a more pronounced reduction in energy consumption.

Examining the suitability of the local climate zones (LCZ) framework in informal urban settlements: Insights from Kabul, Afghanistan

To better investigate the Urban Heat Island (UHI) effect, a standardized framework known as Local Climate Zones (LCZ) has been developed and widely applied to numerous cities. However, cities from least-developed countries with heterogeneous typologies are underrepresented in the LCZ literature. This study assesses the applicability of the LCZ framework in the slum-dominant built-up environment of Kabul. Using a combined method involving GIS and remote sensing, we classified natural and built-type LCZs and analyzed LCZ-LST fluctuations. The analysis revealed that four new subclasses cover 23 % of the built type LCZs: LCZ 35 (mid/high-rise buildings within compact lowrise layouts) and LCZ 65 (midrise buildings among open lowrise areas) have the lowest LSTs at 34.36 °C and 34.42 °C in July, respectively. In contrast, LCZ 73 (two/three-story buildings in lightweight configurations), and LCZ 9F (sparse buildings on bare soil or sand) have higher LSTs at 37.2 °C and 38.6 °C in July, respectively. These subclasses showed distinct zone parameter thresholds compared to standard LCZs. In most built-type LCZs, Average Building Height (ABH) and Pervious Surface Fraction (PSF) negatively influenced LST, while impervious surfaces and Sky View Factor contributed to higher LST. Based on the findings, LCZ-specified strategies (Vegetation, urban form, and using high-albedo materials) for LST mitigation are proposed. Furthermore, we provide planning, design, and policy recommendations aimed at mitigating urban heat, with potential applicability to other cities facing rapid urbanization and growth of informal settlements. The findings can inform action toward urban climate change adaptation.

Enhanced Cooling Efficiency of Urban Trees on Hotter Summer Days in 70 Cities of China

Increasing the urban tree cover percentage (TCP) is widely recognized as an efficient way to mitigate the urban heat island effect. The cooling efficiency of urban trees can be either enhanced or attenuated on hotter days, depending on the physiological response of urban trees to rising ambient temperature. However, the response of urban trees’ cooling efficiency to rising urban temperature remains poorly quantified for China’s cities. In this study, we quantify the response of urban trees’ cooling efficiency to rising urban temperature at noontime [∼1330 LT (local time), LT=UTC+8] in 17 summers (June, July, and August) from 2003–19 in 70 economically developed cities of China based on satellite observations. The results show that urban trees have stronger cooling efficiency with increasing temperature, suggesting additional cooling benefits provided by urban trees on hotter days. The enhanced cooling efficiency values of urban trees range from 0.002 to 0.055°C %−1 per 1°C increase in temperature across the selected cities, with larger values for the low-TCP-level cities. The response is also regulated by background temperature and precipitation, as the additional cooling benefit tends to be larger in warmer and wetter cities at the same TCP level. The positive response of urban trees’ cooling efficiency to rising urban temperature is explained mainly by the stronger evapotranspiration of urban trees on hotter days. These results have important implications for alleviating urban heat risk by utilizing urban trees, particularly considering that extreme hot days are becoming more frequent in cities under global warming.

Spatiotemporal Evolution and Influencing Factors of Heat Island Intensity in the Yangtze River Delta Urban Agglomeration Based on GEE

Urban agglomerations significantly alter the regional thermal environment. It is urgent to investigate the evolution and influence mechanisms of urban agglomeration heat island intensity from a regional perspective. This study is supported by Google Earth Engine long-term MODIS data series. On the basis of estimating surface urban heat island intensity (SUHI) in the Yangtze River Delta urban agglomeration from 2001 to 2020 based on the suburban temperature difference method, the causes of heat islands in the urban agglomeration were analyzed by using geographical detector analysis. Additionally, the heat island proportion (PHI) and SUHI indicators were used to compare and analyze the changing characteristics of the urban heat island effect of ten representative cities. The research reveals the following: (1) The average SUHI of the study area increased from 0.11 °C in 2001 to 0.29 °C in 2020, with an average annual increase rate of 0.009 °C. (2) According to the results of the geographical detector analysis, SUHI was influenced by several driving factors exhibiting obvious seasonal variations. (3) SUHI difference between cities is significant in the summer (1.52 °C), but smallest in the winter; the PHI difference between cities is larger in the autumn (46.7%), while it is smaller in the summer. The research findings aim to effectively serve the formulation of collaborative development plans for the Yangtze River Delta urban agglomeration.

Laboratorial investigation on optical, thermal and pavement performance of biomimetic dark reflective coatings with composite structure for pavement cooling

The surface temperature of asphalt pavement in summer can reach up to 70 °C, which leads to poor outdoor thermal comfort and exacerbates the urban heat island effect. Reflective coatings can effectively reduce pavement temperature, but their intrinsic light color with high reflectance causes safety issues such as glaring. In this study, based on the biomimetic idea of chameleon skin structure, composite pavement coatings for cooling and anti-glare were developed. Their optical properties, thermal behavior, adhesion and skid-resistance performances were investigated. The results showed that near-infrared reflectance of black and grey double-layer reflective coatings could reach 0.66 and 0.70, respectively (58 % higher than single-layer coatings). The optimal mass fraction of perylene black in the upper black/grey coating was 2.94 % and 0.74 %, respectively. The double-layer dark coatings could decrease the temperature by 14 °C at the depth of 3 cm below road surface, which achieved cooling effect close to that of white single-layer reflective coatings. The adhesion between coating and stone was generally higher than the cohesion of asphalt, therefore, opening traffic for a period of time or carrying out micro-milling before coating could improve the abrasion resistance. Due to increase in the thickness of the double-layer coating, the microscopic texture of road surface was reduced, thereby reducing skid-resistance. However, it still met the standard requirements. This study intends to provide a reference for developing pavement coatings that balance cooling and visual safety to mitigate the heat island effect, and improve the sustainability of transportation infrastructure.

Investigating Variations in Anthropogenic Heat Flux along Urban–Rural Gradients in 208 Cities in China during 2000–2016

Anthropogenic heat emissions, which are quantified as anthropogenic heat flux (AHF), have attracted significant attention due to their pronounced impacts on urban thermal environments and local climates. However, there remains a notable gap in research regarding the distinctions in the distribution of anthropogenic heat emissions (AHEs) along urban–rural gradients. To address this gap, the present study introduces a new concept—the anthropogenic urban heat island (ArUHI)—where the AHF within urban areas is higher than that in background areas. To quantitatively describe the magnitude and spatial extent of the ArUHI effect, two metrics—namely, ArUHI intensity (ArUHII) and ArUHI footprint (ArUHIFP)—are introduced. We conducted a comprehensive study across 208 cities in China to investigate the spatiotemporal patterns of AHF variations along urban–rural gradients during the period of 2000–2016. In addition, we explored how the complex interactions between land cover and building form components affect changes in the AHF along urban–rural gradients. Additionally, we analyzed how economic zones and city sizes alter the ArUHI intensity and ArUHI footprint. The results showed that 97% (201/208) of Chinese cities exhibited a significant ArUHI effect from 2000 to 2016. The modeled ArUHI intensity value exhibited a substantial increase of nearly fivefold, increasing from 5.55 ± 0.19 W/m2 to 26.84 ± 0.99 W/m2 over time. Regarding the spatial distribution of the ArUHI footprint, the analysis revealed that, for the majority of cities (86% or 179 out of 208), the ArUHI footprint ranged from 1.5 to 5.5 times that in urban areas. City sizes and economic zones yielded significant influences on the ArUHI intensity and ArUHI footprint values. Building forms were significantly positively correlated with AHF, with R2 values higher than 0.94. This study contributes to the understanding of ArUHI effects and their driving factors in China, providing valuable insights for urban climate studies and enhancing our understanding of surface urban heat island mechanisms.