Search Results (31)

To elucidate features of the recent urban thermal–humidity climate, this study interrogates high-density observational data (2018–2023) from Xining, a key urban area on the Tibetan Plateau (TP), focusing on recent changes and extremes. Results show that the summer urban heat island intensity (UHII) has intensified in recent years, marked by a surging frequency of extreme heat island days and increased variability, as exemplified by the maximum hourly UHII increasing from 3.95 °C to 6.60 °C during 2018–2023. Conversely, the summer urban dry island intensity (UDII) exhibited a clear weakening, yet this is accompanied by a dramatic increase in transient extreme events, characterized by a sharp rise in weak dry island occurrences and the emergence of urban moist islands. Furthermore, the hourly UHII is dominantly modulated by atmospheric humidity and temperature conditions, and these influences displayed a pronounced diurnal asymmetry, being strongest at night while weak or even reversed during the pre-noon hours. These findings underscore the escalating thermal risks and complex humidity dynamics in this highland city, providing critical insights for urban planning and climate adaptation strategies in similar environments. Full article

The urban heat island (UHI) effect in Andean cities is a critical yet understudied phenomenon, where complex topography and rapid urbanization uniquely alter local climates. This research analyzes the spatiotemporal evolution of the surface UHI and its linkage to urban morphology in Ayacucho, Peru, through a 40-year multi-temporal analysis (1986–2016) using Landsat images. We developed a synthetic Urban Heat Island Index (UHII) through Principal Component Analysis (PCA), integrating land surface temperature (LST), spectral indices, and urban morphological parameters. Our results identify a critical transition in 2006, with the emergence of persistent heat spots driven by unplanned expansion. The surface UHI intensity reached urban-rural differences of 4.31 °C (day) and 5.82 °C (night), showing a positive trend. Urban morphology was a key determinant, with high-density blocks exhibiting a minimum nocturnal LST 3.53 °C higher than low-density areas. Statistical trend tests confirmed a significant intensification, while a strong negative correlation with vegetation indices (R² = 0.97) underscored the vital mitigation role of green infrastructure. This study provides academics with a robust methodological framework for UHI analysis in complex terrains. For public and private urban managers, it offers spatially explicit evidence to prioritize actionable strategies, such as integrating green infrastructure and regulating urban form, to enhance climate resilience in Andean cities. Full article

Global warming and urbanization have exacerbated the urban heat island (UHI) effect, threatening human settlements and public health. Existing studies have primarily focused on analyzing urban thermal environment characteristics throughout the year or in specific seasons; however, research examining the urban thermal environment at different stages within a season is scarce. This study employed Local Climate Zone (LCZ) classification and focused on Shenyang, a representative city in China’s severe cold regions. Based on field measurements and multi-source meteorological data, we investigated the differences in thermal environment across seven LCZs throughout summer and at different summer stages. The result show that the UHI effect in Shenyang significantly intensified at nighttime and weakened during the daytime. Built-type LCZs 2 and 4 exhibited the highest nighttime urban heat island intensities (UHIIs), with maximum values of 7.6 °C and 5.4 °C, respectively. The duration of the daytime urban cold island effect in built-type LCZs increased significantly in mid-summer and late-summer. Land cover-type LCZ A exhibited the urban cold island effect only during the daytime throughout the summer. The UHII remained relatively stable across all LCZs during mid-summer. This study provides empirical support for developing targeted heat risk mitigation strategies for cities in severe cold regions. Full article

Due to intensive urbanization, global warming, and increasing energy demands, the impact of urban heat islands is becoming more significant. This study investigates the contribution of vehicular emissions to air pollution and its effects on urban heat island intensity in a selected area of Belgrade, Serbia, between March and September 2015, using a combination of experimental measurements and numerical simulations. Furthermore, this study presents the results of the research on the impact of assessment of traffic-induced air pollution on the appearance of thermal islands in the urban environment, as well as the characterization of thermal islands and their quantification. This study quantifies the effects of traffic-related emissions and urban meteorological parameters on the intensity of the urban heat island by combining field measurements with a validated three-dimensional numerical model and shows that higher traffic density increases pollutant concentrations and cooling energy demand in buildings. The study includes experimental measurements of traffic intensity and modeling of gas emissions from major roads. Using long-term and short-term field measurements, concentrations of carbon dioxide and other pollutants were analyzed with meteorological parameters and their cumulative impact to assess their impact on local air quality. A three-dimensional numerical model for simulating the dispersion of pollutants has been developed, confirmed and validated by experimental data. The results highlight a direct correlation between traffic density and pollutant concentrations, emphasizing the need for strategic urban planning and sustainable transport policies to mitigate the effects of air pollution. A validated numerical model was used to simulate dynamic changes in temperature fields and carbon dioxide concentrations caused by vehicular emissions. The findings reveal that the Urban Heat Island Intensity (UHII) for the selected area in Belgrade reached peaks of up to 12 °C during the summer measurement period, with typical values in July ranging from 5 °C to 9 °C. Furthermore, the validated numerical model demonstrated that the removal of urban trees would lead to a local air temperature increase of 1.5 °C to 3 °C, quantifying the significant cooling potential of green infrastructure. These results highlight a direct correlation between traffic density, pollutant concentrations, and the intensification of urban heat islands, emphasizing the need for strategic urban planning. Furthermore, the findings reveal that increased traffic not only elevates air pollutant levels but also enhances the intensity of urban heat islands, leading to higher cooling energy demands in buildings. These insights are vital for developing effective mitigation strategies to improve the sustainability of urban environments and living conditions. These findings provide a clear directive for urban planners: the integration and preservation of green infrastructure is a highly effective UHI mitigation strategy, capable of reducing local temperatures by 1.5–3 °C. Furthermore, the results strongly support the implementation of targeted traffic management policies in dense urban cores as a dual strategy to improve air quality and reduce local thermal loads. Full article

Taiwan, located in a subtropical region, has experienced continuous warming in recent years, making the Urban Heat Island (UHI) effect one of its most pressing environmental challenges. Importantly, UHI is not confined to Taipei, the most populous city, but is also present in other metropolitan areas. This study investigates UHI effects in the five largest cities in Taiwan and examines climate-related news attention using web crawling. Cross-city comparisons are further conducted through Urban Heat Island Intensity (UHII) and correlation analysis. The results reveal that Taipei records the highest number of UHI-related news reports, particularly during summer, and its UHII is about 1.5 °C to 3 °C higher than in the other four cities. In addition, UHII in Taipei shows a marked increase between 2021 and 2023, suggesting a worsening impact on citizens’ living conditions. Meanwhile, news coverage in Taipei dominates nationwide attention, creating a spatially uneven distribution of media focus. This imbalance may undermine efforts to promote UHI mitigation and adaptation strategies in cities outside Taipei. Overall, this study highlights that UHI is not solely a problem of Taipei but a widespread issue across Taiwan’s urban areas. The findings provide useful references for policymakers and government agencies, emphasizing the need for equitable attention and broader public engagement through media channels to raise awareness and foster comprehensive climate adaptation actions. Full article

With accelerating urbanization and global climate warming, Urban Heat Islands (UHIs) pose serious threats to urban development. Existing UHI research mainly focuses on inland regions, lacking systematic understanding of coastal city heat island mechanisms. We selected eight Chinese coastal cities with different backgrounds, quantitatively assessed urban heat island intensity based on summer 2023 Landsat 8 remote sensing data, established block-LCZ spatial analysis units, and employed a combination of machine learning models and causal inference methods to systematically analyze the regional differentiation characteristics of Urban Heat Island Intensity (UHII) and the influence mechanisms of multi-dimensional driving factors within land–sea interaction contexts. The results revealed the following: (1) UHII in the study area presents obvious spatial differentiation, with the highest value occurring in Hong Kong (2.63 °C). Northern cities generally had higher values than southern ones. (2) Different Local Climate Zone (LCZ) types show significant differences in thermal contributions, with LCZ2 (compact midrise) blocks presenting the highest UHII values in most cities, while LCZ G (water) and LCZ A (dense trees) blocks exhibit stable cooling effects. Nighttime light (NTL) and distance to sea (DS) are dominant factors affecting UHII, with NTL marginal effect curves generally presenting hump-shaped characteristics, while DS shows different response patterns across cities. (3) Causal inference reveals true causal driving mechanisms beyond correlations, finding that causal effects of key factors exhibit significant spatial heterogeneity. The research findings provide a new cognitive framework for understanding the formation mechanisms of thermal environments in Chinese coastal cities and offer a quantitative basis for formulating regionalized UHI mitigation strategies. Full article

Spatially uneven urbanization shapes various urban-lake spatial patterns; however, the effect of pattern evolution on lake breeze front (LBF) penetration via thermal and aerodynamic mechanisms in inland multi-lake megacities remains unclear. Therefore, sensitivity experiments were conducted to examine LBF changes over the past 40 years in Wuhan, China—where lakes are located on the periphery of built-up areas or integrated with urban fabrics—using the Weather Research and Forecasting (WRF) model under high-temperature and weak-wind conditions. Moreover, we quantified the contributions of thermal (lake-land surface temperature differences (LSTD), urban heat island intensity (UHII)), and aerodynamic factors (lake-land surface roughness differences (LSRD)) to LBF penetration. The results showed that for lakes entirely within urban fabrics, the thermal and roughness characteristics at lake-land interfaces dominated LBF penetration. Specifically, urban expansion towards lakeshores without connections promoted LBF penetration due to the stronger positive benefits of the LSTD. However, urban expansion bordering lakeshores inhibited LBF penetration, as the inhibitory effects of LSRD outweighed those of LSTD. When lakes remained on the periphery of built-up areas, higher UHII and the UHII-weighted center moving towards suburban lakes accelerated the LBF movement into built-up areas. Based on these findings, we propose adaptive strategies for urban growth boundaries to facilitate the natural infiltration of LBFs into urban environments. Full article

This study explores the spatiotemporal distribution and formation mechanisms of urban heat islands (UHIs) in Nanjing during summer, utilizing temperature data from 82 automatic weather stations (AWSs) distributed across five concentric zones. The results demonstrate the substantial impact of urbanization on UHI patterns, with industrial and densely populated areas exhibiting higher UHI intensity (UHII), while regions with natural landscapes such as mountains and water bodies display lower temperatures. The analysis reveals that the most pronounced night-time UHI effect occurs in the highly urbanized central zones, whereas the weakest effect is observed during midday. Transitional UHI phases are identified around sunrise and sunset, with increased long-wave radiation post-sunset amplifying the UHI effect. Additionally, this study underscores the directional characteristics of UHI distribution in Nanjing. Notably, Hexi New Town has emerged as a new high-temperature hotspot due to rapid urbanization, while Jiangning New Town and Xianlin Sub-City maintain lower temperatures owing to their proximity to agricultural and forested areas. By selecting representative AWSs from different zones, this study introduces a novel and practical method for calculating UHII. Although the approach has limitations in precision, it provides an accessible tool for UHI analysis and can be adapted for use in other cities. This research offers valuable insights into the influence of urban development on local climate and presents a practical framework for future UHI studies and urban planning strategies aimed at mitigating UHI effects. Full article

The data derived from Local Climate Zone (LCZ) field measurements can contribute to the construction of regional climate datasets with urban heat island (UHI) effects and accurately present urban heat island intensity (UHII) characteristics in different areas, thereby improving the accuracy of building energy consumption simulations. This study focuses on Shenyang, a severe cold-region city, as the research area. By mapping the LCZs in the central city of Shenyang and selecting eight different types of LCZ plots for field temperature measurement, the UHI effect of various LCZs in Shenyang was analyzed. Air temperature and UHII were used to evaluate the UHII characteristics of LCZs under typical meteorological conditions. Additionally, this study investigated the temperature dynamics and heating/cooling rates of each LCZ under typical meteorological days. The results reveal significant differences in UHII characteristics among LCZ types, closely related to their surface structure and land cover characteristics. These findings further validate the effectiveness of the LCZ classification method in severe cold regions. The data obtained in this study can be used as high-precision climate model parameters for urban energy consumption models and building energy efficiency models, thus making simulation results more consistent with local characteristics and enabling more accurate energy consumption predictions. Full article

With the acceleration of urbanization, the urban heat island (UHI) effect has become a major environmental challenge, severely affecting the quality of life of residents and the ecological environment. Quantitative analysis of the factors influencing urban heat island intensity (UHII) is crucial for precise urban planning. Although extensive research has investigated the causes of UHI effects and their spatial variability, most studies focus on macro-scale analyses, overlooking the spatial heterogeneity of thermal characteristics within local climate zones (LCZs) under rapid urbanization. To address this gap, this study took the central urban area of Chengdu, constructing a LCZ map using multisource remote sensing data. Moran’s Index was employed to analyze the spatial clustering effects of UHI across different LCZs. By constructing Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models, the study further explored the influencing factors within these climate zones. The results showed that: (1) Chengdu’s built and natural environments had comparable proportions, with the scattered building zone comprising the highest proportion at 22.12% in the built environment, and the low vegetation zone accounting for 21.8% in the natural environment. The UHII values in this study ranged from 10.2 °C to −1.58 °C, based on specific measurement conditions. Since UHII varied with meteorological conditions, time, seasons, and the selection of rural reference points, these values represented dynamic results during the study period and were not constant. (2) Chengdu’s urban spatial morphology and UHII exhibited significant spatial heterogeneity, with a global Moran’s I index of 0.734, indicating a high degree of spatial correlation. The highest local Moran’s I value was found in the proportion of impervious surfaces (0.776), while the lowest is in the floor area ratio (0.176). (3) The GWR model demonstrated greater explanatory power compared to the OLS model, with a fit of 0.827. The impact of spatial morphological factors on UHII varied significantly across different environments, with the most substantial difference observed in the sky view factor, which has a standard deviation of 13.639. The findings provide precise recommendations for ecological spatial planning, aiming to mitigate the UHI effect and enhance the quality of life for urban residents. Full article

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. Full article

In the context of an increasingly extreme climate, Urban Heat Island (UHI) mitigation of communities through ventilation has recently attracted more attention. To explore the impact mechanisms of different morphological renovation schemes on its wind and thermal environment, this paper selected the Laozheng Community as a case study and: (1) analyzed measured data to quantitatively investigate the UHI within the community; (2) established the CIM-WTEPS system to construct community information models and to conduct wind environment parametric simulation for seven micro-renovation schemes across three levels; (3) performed correlation analyses between morphology indicators and wind environment indicators; (4) conducted the thermal environment parametric simulation of the community under different schemes. The results reveal that: (1) the Laozheng Community exhibits the Urban Heat Island Intensity (UHII) of up to 6 °C; (2) apart from the “ Hollowing “ scheme, which deteriorates the community wind environment, all other schemes optimize it, potentially increasing the average wind speed by up to 0.03m/s and in the renovated area by up to 0.42 m/s; (3) building density is highly correlated with the average wind speed and the proportion of calm wind area, with correlation coefficients of −0.916 (p < 0.01) and 0.894 (p < 0.01), respectively; (4) the adding of shading facilities can enhance the proportion of areas with lower Universal Thermal Climate Index (UTCI) without adversely affecting the optimization effects of the wind environment, achieving an maximum increase of 3.1%. This study provides a reference for optimizing the community’s microclimate through morphological micro-renovations and detailed operations, aiding designers in better controlling community morphology for in future community renewal and design planning, thereby creating a more hospitable outdoor environment. Full article

Urban heat islands (UHIs) aggravate urban heat stress and, therefore, exacerbate heat-related morbidity and mortality as global warming continues. Numerous studies used surface urban heat island intensity (SUHII) to quantify the change in the UHI effect and its drivers for heat mitigation. However, whether the variations in SUHII among cities can demonstrate the physical difference and fluctuation of the urban thermal environment is poorly understood. Here, we present a comparison study on the temporal trends of SUHII and LST in urban and nonurban areas in 13 cities of the Beijing–Tianjin–Hebei (BTH) megaregion in China and further identify different types of changes in SUHII based on the temporal trends of land surface temperature (LST) in urban and nonurban areas from 2000 to 2020. We also measured the effect of the changes in four socioecological factors (i.e., population density, vegetation greenness (EVI), GDP, and built-up area) on the trends of SUHII to understand the dynamic interaction between the UHI effect and socioecological development. We found the following. (1) Nine out of thirteen cities showed a significant increasing trend in SUHII, indicating that the SUHI effects have been intensified in most of the cities in the BTH megaregion. (2) The spatial pattern of summer mean SUHII and LST in urban areas varied greatly. Among the 13 cities, Beijing had the highest mean SUHII, but Handan had the highest urban temperature, which suggests that a city with stronger SUHII does not necessarily have a higher urban temperature or hazardous urban thermal environment. (3) Four types of changes in SUHII were identified in the 13 cities, which resulted from different temporal trends of LST in urban areas and nonurban areas. In particular, one type of increasing trend of SUHII in seven cities resulted from a greater warming trend (increasing LST) in urban than nonurban areas (SUHII↑₁), and another type of increasing trend of SUHII in Beijing and Chengde was attributed to the warming trends (increasing LST) in urban areas and the cooling trends (decreasing LST) in nonurban areas (SUHII↑₂). Meanwhile, the third type of increasing trend of SUHII in Zhangjiakou was due to a greater cooling (decreasing LST) trend in nonurban areas than in urban areas (SUHII↑₃). In contrast, three cities with a decreasing trend of SUHII were caused by the increase in LST in urban and nonurban areas, but the warming trend in nonurban areas was greater than in urban areas (SUHII↓₁). (4) Among the relationship between the trend of SUHII (Trend_SUHII) and the changes in socioecological factors (Trend_{population density}, Trend_{GDP per captica}, Trend_EVI, and Trend_{build-up area}), a significantly positive correlation between Trend_SUHII and Trend_EVI indicated that the change in SUHII was significantly related to an increased rate of EVI. This is mainly because increased vegetation in nonurban areas would result in lower temperatures in nonurban areas. Full article

With the global warming effect and the rapid growth of global urbanization, the concept of urban heat islands (UHIs) has become one of the most important environmental issues in the world. Early studies on UHIs mostly focused on highly developed, large cities and found that urban heat island intensity (UHII) can be as high as 4~7 °C. In recent years, it has also been found that the UHI of medium-sized cities can also reach 4–6 °C. Previous studies have also found that planting, street orientation, and aspect ratio individually have a great impact on the thermal environment of streets, but there are not many studies that comprehensively discuss the synergistic effects of these factors. Therefore, this study takes a tropical, medium-sized city, Chiayi City, as a case study to use the ENVI-met numerical simulation tool to comprehensively compare and analyze the influence of the trees and geometric characteristics of streets on the microclimate and comfort in the streets. As a result, in a tropical, with sea winds (west winds), medium-sized city, by comparison of 12 street schemes with different roadside tree situations (planting or not), orientations (E–W, N–S), and aspect ratios (0.3, 0.7, 1.0), the improvement benefits and possible mechanisms of air temperature, wind speed, MRT, PET, SET, absolute humidity, etc. at the pedestrian street level (H = 1.4 m) were obtained and show that the cooling effect of trees was deeply affected by the street orientation and geometry. An analysis of changes at different heights was also obtained. Finally, design strategy suggestions, such as the street orientation, should be prioritized to be parallel to the prevailing wind; modifying tree shapes or building forms on streets perpendicular to the prevailing wind for creating cool and comfortable streets in future tropical, medium-sized cities were proposed. Full article

The heating and cooling energy consumption levels of urban buildings account for a large and rapidly growing proportion of the total end-use energy consumption of society. The urban heat island (UHI) effect is an important factor influencing the spatiotemporal variations in the heating and cooling energy consumption levels of buildings. However, there is a lack of research on the impact of the UHI on the heating and cooling energy consumption of buildings in cities of different sizes in the Beijing–Tianjin–Hebei urban agglomeration, which is the most urbanized region in northern China. We selected rural reference stations using the remote sensing method, and applied an hourly data set from automatic weather stations, to examine the impact of the UHI on the typical residential building heating and cooling loads in three cities of varied sizes in the Beijing–Tianjin–Hebei urban agglomeration through building energy simulation. The main conclusions were as follows. As the UHI intensity (UHII) increased, the heating load difference between urban and rural areas decreased, while the cooling load difference between urban and rural areas increased in the cities. The average daily heating loads in the urban areas of Beijing, Tianjin, and Shijiazhuang were 8.14, 10.71, and 2.79% lower than those in their rural areas, respectively, while the average daily cooling loads in the urban areas were 6.88, 6.70, and 0.27% higher than those in their rural areas, respectively. Moreover, the absolute hourly load differences between urban and rural areas were significantly larger during the heating periods than during the cooling periods, with the former characterized by being strong at night and weak during the day. During the peak energy load period, the contribution of the UHI to the peak load of residential buildings varied between the cities. During the stable high-load period, from 18:00 to 07:00 the next day in the heating periods (from 18:00 to 05:00 the next day in the cooling periods), the hourly loads in the urban areas of Beijing, Tianjin, and Shijiazhuang were 3.15 (2.48), 3.88 (1.51), and 1.07% (1.09%) lower (higher) than those in their rural areas, respectively. Our analysis highlights the necessity to differentiate the energy supplies for the heating and cooling of urban buildings in different sized cities in the region. Full article