Search Results (1,561)

Land use change is closely related to land surface temperature (LST). Based on remote sensing data from 2001 to 2020, this study analyzed the spatiotemporal variations and driving mechanisms of daytime and nighttime LST in the Urumqi Metropolitan Area (UMA) by combining traditional methods with the eXtreme Gradient Boosting (XGBoost)–SHAP coupled model. Although the average LST trend in the region was one of warming, the pixel-level significance analysis indicated that statistically significant warming (p < 0.05) is concentrated mainly in the urban core (2.65% of the area), while the majority of the region (70%) showed a non-significant warming trend. LST displayed significant spatial clustering, with Moran’s I remaining above 0.990, indicating a positive spatial autocorrelation in spatial distribution. With the advancement of urbanization, the proportion of impervious surfaces increased from 0.87% to 1.14%, while wastelands consistently accounted for approximately 50% of the total area. Different land use types showed distinct effects on the urban heat island (UHI) phenomenon: water bodies, grasslands, and forests played cooling roles, whereas barren land and impervious areas were the main heat contributors. The XGBoost-SHAP analysis further revealed that the importance ranking of driving factors has evolved over time. Among these factors, Elevation dominates, while the influence of population-related factors increased significantly in 2020. This study provides a scientific basis for regulating the thermal environment of cities in arid regions from the perspective of land use. This study provides a scientific basis for regulating the thermal environment of arid-region cities from the perspective of land use. Full article

Urbanization in Cyprus has accelerated significantly over the past 35 years, driven by population growth, infrastructure development, and the expansion of urban centres. This rapid urban transformation has contributed to notable changes in the local climate, primarily through the intensification of the Urban Heat Island (UHI) effect—a phenomenon where urban areas experience significantly higher temperatures than surrounding rural regions. As global climate change continues to influence regional weather patterns, understanding and mitigating local climatic variations such as UHI becomes increasingly critical for sustainable development and public health. In Cyprus, the cities of Nicosia, Limassol, Larnaca, and Paphos have witnessed considerable land use changes, with a growing contrast between densely built urban cores and less developed surrounding areas. This contrast results in uneven energy absorption, reduced vegetation cover, and altered surface temperatures, further exacerbating the effects of climate change at the local level. Full article

Heatwaves are intensifying across Mediterranean cities, where the Urban Heat Island (UHI) effect amplifies thermal stress. This study updates the spatial characterization of the Surface Urban Heat Island (SUHI) in Tarragona using multi-sensor remote sensing data within a Local Climate Zone (LCZ) framework. Land surface temperature, albedo, and the Normalized Difference Vegetation Index (NDVI) were analyzed during heatwaves from 2015–2025 to assess spatial patterns and drivers of urban heating. Results reveal a daytime urban cool island associated with low albedo and scarce vegetation, and a nocturnal SUHI caused by heat retention in dense built-up areas. High-resolution mapping identifies industrial and commercial zones as hotspots, while vegetated and water-covered areas act as cooling sites. These findings clarify the spatial dynamics and key biophysical controls of SUHI and provide an actionable basis for prioritizing locally tailored adaptation strategies in Mediterranean coastal cities. Full article

Urban heat island (UHI), a significant environmental issue caused by urbanization, is a pressing challenge in modern society. To mitigate it, urban thermal policies have been implemented globally. However, despite differences in topographical and environmental characteristics between cities and within the same city, these policies are largely uniform and fail to reflect contexts, creating notable drawbacks. This study analyzed three cities in Korea with high land surface temperatures (LSTs) to identify factors influencing LST by applying Extreme Gradient Boosting (XGBoost) with Shapley Additive explanations (SHAP) and Geographically Weighted Regression (GWR). Each variable was derived by calculating the average values from May to September 2020. LST was the dependent variable, and the independent variables were chosen based on previous studies: Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), ALBEDO, Population Density (POP_D), Digital Elevation Model (DEM), and SLOPE. XGBoost-SHAP was used to derive the relative importance of the variables, followed by GWR to assess spatial variation in effects. The results indicate that NDBI, reflecting building density, is the primary factor influencing the thermal environment in all three cities. However, the second most influential factor differed by city: SLOPE had a strong effect in Daegu, characterized by surrounding mountains; POP_D had greater influence in Incheon, where population distribution varies due to clustered islands; and DEM was more influential in Seoul, which contains a mix of plains, mountains, and river landscapes. Furthermore, while NDBI and ALBEDO consistently contributed to LST increases across all regions, the effects of the remaining variables were spatially heterogeneous. These findings highlight that urban areas are not homogeneous and that variations in land use, development patterns, and morphology significantly shape heat environments. Therefore, UHI mitigation strategies should prioritize improving urban form while incorporating localized planning tailored to each region’s physical and socio-environmental characteristics. The results can serve as a foundation for developing strategies and policy decisions to mitigate UHI effects. Full article

Two prototype moss-based green roof systems were developed and evaluated using a newly cultivated strain of Racomitrium japonicum (Dozy & Molk.) to investigate their feasibility in mitigating rooftop heat and enhancing carbon sequestration under actual urban conditions. Flat and sloped-type green roof systems (2 m × 2 m each) were developed and installed on a rooftop to investigate their performance in summer (from June to August 2025). The moss-based systems reduced rooftop surface temperature by an average of 6–10 °C during daytime and retained approximately 1.5–2.5 °C of heat at night, thereby contributing to cooling and thermal buffering. The moss layer effectively reduced solar radiation heating of the underlying soil. Despite exposure to intense sunlight and high summer temperatures, the moss maintained a consistent growth rate of 3–5 mm per month. The annual carbon sequestration capacity of the prototype system was estimated at approximately 0.3 kg C/m².year, which is comparable to values reported for other vegetation types. These findings indicate that moss-based green roofs incorporating the newly cultivated moss strain have practical potential for urban heat island mitigation and carbon capture. Full article

Rio de Janeiro’s favelas house over 20% of the city’s population in just 5% of its territory, with Rio das Pedras emerging as a critical case study: ranking as Brazil’s fifth most populous favela and its most vertically intensified. This study quantifies how uncontrolled vertical growth in informal settlements disrupts microclimate dynamics, directly impacting thermal comfort. Using high-resolution geospatial analytics, we integrated digital surface models (DSMs) derived from LiDAR and photogrammetric data (2013, 2019, and 2024) with microclimatic simulations to assess urban morphology changes and their thermal effects. A spatiotemporal cadastral analysis tracked vertical expansion (new floors) and demolition patterns, while ENVI-met simulations mapped air temperature anomalies across decadal scenarios. Results reveal two key findings: (1) rapid, unregulated construction has significantly altered local airflow and surface energy balance, exacerbating the urban heat island (UHI) effect; (2) microclimatic simulations consistently recorded elevated temperatures, with the most pronounced impacts in densely built zones. These findings underscore the need for public policies to mitigate such negative effects observed in informal settlement areas. Full article

Urban trees play a critical role in mitigating climate change by capturing atmospheric CO₂ and providing multiple co-benefits, including cooling urban environments, reducing building energy demand, and enhancing citizens’ physical and psychological well-being. This study presents the Co Carbon Trees Measurement project, a citizen science initiative implemented in the city of Viladecans, Spain, involving 658 students, local administration, and academia, three components of the EU mission’s quadruple helix governance model. Over one year, 1274 urban trees were measured for trunk diameter and height to quantify annual CO₂ sequestration using a direct measurement approach combining field data collection with a mobile application for a height assessment and a flexible measuring tape for diameter. Results indicate that carbon fixation increases with tree size, displaying a parabolic function with larger trees sequestering significantly more CO₂. A range between 10 and 20 kg of CO₂ is sequestered by the urban trees in the period 2024–2025. The study also highlights the broader benefits of urban trees, including shading, mitigation of the urban heat island effect, and positive impacts on mental health and social cohesion. While the total CO₂ captured in Viladecans (≈810 tons/year) is small relative to city emissions (≈170,000 tons/year), the methodology demonstrates a scalable, replicable approach for monitoring progress toward climate neutrality and integrating urban trees into planning and climate action strategies. This approach positions green infrastructure as a central component of sustainable and resilient urban development. Full article

Climate change and rising temperatures in cities due to the urban heat island (UHI) effect are causing increased heat stress and driving the development of efficient, sustainable outdoor cooling systems. The aim of this article was to analyze the integration of adiabatic air cooling systems with photovoltaic (PV) installations in the context of improving thermal comfort and energy autonomy. The study was conducted on the example of a bus station in Rzeszow (Poland), considering two system variants: indirect evaporative cooling and direct evaporative cooling. To assess the impact of comfort parameters on the number of hours of system operation, energy consumption, and operating costs, four upper thermal comfort limits were considered: 22 °C, 22.9 °C, 24 °C, and 25 °C. The results indicate that increasing the upper limit of thermal comfort reduces the operating time of the system and significantly reduces the demand for cooling—for example, increasing the thermal comfort range from 22.9 °C to 24 °C reduces useful energy by 41%. Assuming a thermal comfort range of 25 °C, the direct evaporative cooling system achieves full energy autonomy and is fully powered by photovoltaics. Life cycle analysis (LCA) and life cycle cost (LCC) confirmed the environmental and economic benefits of using higher thermal comfort values. The study highlights the potential of adiabatic cooling systems, in conjunction with a local photovoltaic installation, as an adaptive solution that improves thermal comfort in urban spaces with minimal energy consumption from the grid. Full article

The article presents the development and laboratory validation of a current optimization algorithm designed for voltage-source systems. The algorithm was implemented in a real laboratory setup using a synchronous generator driven by a DC motor to model a fragment of a power system. During tests, transient states were intentionally inducted to evaluate the algorithm’s performance. The proposed optimization method effectively reduced instantaneous current peaks by over 60% and the overall RMS current by approximately 4%, leading to lower power losses and decreased conductor temperatures. These improvements resulted in nearly 8% minimization of power losses and a noticeable reduction in heat generation during transient and fault conditions. The solution is particularly suitable for islanded networks with renewable and unstable energy sources. Full article

Enhancing climate resilience is imperative for cities to mitigate the effects of global warming and the rising frequency of extreme weather events. This paper develops an evaluation index system for urban climate resilience in Hebei Province, based on data from 11 cities within the province. It evaluates the levels of climate resilience and identifies their limiting factors using the entropy weight method, an urban climate resilience assessment model, and an obstacle degree model, with a focus on four dimensions: ecological resilience, economic resilience, social resilience, and infrastructure resilience. The results indicate that (1) spatial variations in climate resilience across cities in Hebei Province are minimal, with the majority of cities exhibiting climate resilience levels within the moderate resilience category. (2) The majority of regions display low ecological and infrastructure resilience (0.1–0.3), while economic resilience is distributed across three tiers, with regional variations; social resilience remains moderately resilient (above 0.3). (3) Among the social resilience factors, C₃ and C₈ exhibit the highest obstruction levels, emerging as key barriers. (4) In order to effectively respond to climate change risks and challenges in a scientific manner, differentiated implementation of climate response strategies, the core of which lies in identifying the dominant vulnerability dimensions of different cities and accurately applying policies, such as Shijiazhuang, Baoding, Xingtai, Handan, and other cities with fragile ecological resilience, should comprehensively deepen the construction of sponge cities to alleviate urban flooding and the heat island effect. Full article

This study aims (1) to study the trend and characteristics of monthly air temperature, monthly rainfall, and potential evapotranspiration (PET) in Thailand over the mid-21st century (2022–2060) period, and (2) to create a climate pattern map using the New Thornthwaite Climate Classification in Thailand over the same period under RCP4.5 and RCP8.5 scenarios using CSIRO-Mk3 in the CMIP5 dataset with Empirical Quantile Mapping (EQM) statistical downscaling. Spatial analyses of temperature and PET reveal significant warming trends, with temperatures rising by approximately 0.033 °C/year and PET rising by about 10 mm/year, especially in the Bangkok Metropolitan Region due to the urban heat island effect, with temperature values under RCP8.5 remaining consistently higher than those under RCP4.5. Rainfall projections show relatively stable spatial patterns across both scenarios, with higher concentrations along the Andaman coast, the eastern peninsula, and northeastern Thailand; these are areas influenced by the southwest monsoon and tropical cyclones. Central Thailand, however, exhibits persistently low rainfall, likely due to rain-shadow effects. PET patterns mirror early 21st-century observations, with the highest values projected in central Thailand and increasing trends under both scenarios, suggesting heightened drought risks. By 2060, The New Thornthwaite Climate Classification indicates that Moist climate zones are projected to disappear nationwide, with Semi-arid and Dry climates dominating under both RCP4.5 and RCP8.5 scenarios. Annual mean temperature will rise by 0.033 °C/year and PET by ~10 mm/year, while rainfall trends remain nearly stable. The classification’s reliance on minimal parameters—temperature, precipitation, and PET—provides a practical tool for climate monitoring and policy development. Full article

Rising urban temperatures driven by the Urban Heat Island (UHI) effect highlight the need for architectural strategies that enhance thermal comfort while promoting environmental sustainability. In Budapest’s District 7, characterized by diverse multi-family historical buildings, existing studies predominantly address energy consumption for heating, leaving a gap in passive cooling research. The categorization of typologies derived from the Tabula database, the ZBR strategy, and architectural surveys of the old Jewish quarter is based on heating potential. While historic courtyards offer natural shading and ventilation possibilities, passive cooling strategies remain fragmented. To address this, the paper introduces the “Adaptive Block,” a mid-rise, modular typology integrating courtyard ventilation, dynamic shading, high-albedo surfaces, and low-conductivity insulation. Climate Consultant software is used to analyze passive cooling strategies based on climate data from a local meteorological station, the Budapest Meteorological Center station (WMO ID: 12840), which is an official national station. This serves as a preliminary step to guide future energy simulations by narrowing down the most effective design interventions. The Climate Consultant tool was applied not as a final performance simulation but as a Passive Strategy Pre-Assessment. This pre-assessment bridges regional climate data with building-scale adaptation by identifying which passive cooling options are climatically justified before typology-specific constraints are introduced. By combining the most promising adaptive features from existing typologies, the Adaptive Block presents a scalable framework that supports urban climate resilience while respecting architectural heritage. The findings contribute to adaptive urban design and invite further exploration of its applicability in other existing urban contexts. Full article

Rapid urban expansion and increasing population density intensify the loss of open spaces, exacerbate flooding frequency and runoff pollution, increase the urban heat island effect, and deteriorate ecological resilience and human well-being. This study presents Gazelle Valley Park (GVP) in Jerusalem (Israel), a unique large-scale ecohydrological infrastructure within a dense Mediterranean city. GVP was established in 2015 following a public-led campaign and comprises a multifunctional nature-based solution designed to collect and circulate stormwater through a series of vegetated ponds, enhancing filtration, aeration, and pollutant removal, while sustaining a wetland ecosystem. Its design follows international ecological standards and embodies the principle “from nuisance to resource”, transforming urban runoff into an asset that supports rich biodiversity while offering recreational, cultural, and educational activities. During the dry summer, reclaimed wastewater is introduced in order to support a perennial aquatic habitat, which introduces various challenges due to increased salinity, oxygen demand, and contaminants. Hydrometric and geochemical monitoring demonstrates strong correlations between rainfall and runoff and point at the role of sedimentation and vegetation in reducing pollutant loads. The park benefits from its holistic operation, where hydrology, ecology, education, and public engagement are integrated, thus making the whole greater than the sum of its parts. Full article

Rapid urbanization elevates land surface temperature (LST) through complex urban spatial relationships, intensifying the urban heat island (UHI) effect. This necessitates efficient methods to analyze surface urban heat island (SUHI) factors to help develop mitigation strategies. In this study, we propose an efficient global–local regression (EGLR) framework by integrating XGBoost-SHAP with global–local regression (GLR), enabling accelerated estimation of LST. In a case study of Wuhan, the EGLR reduces the computation time of GLR by 44.21%. The main contribution of computational efficiency improvement lies in the procedure of Moran eigenvector selecting executed by XGBoost-SHAP. Results of validation experiments also show significant time decrease of the EGLR for a larger sample size; in addition, transplanting the framework of the EGLR to two machine learning models not only reduces the executing time, but also increases model fitting. Furthermore, the inherent merits of XGBoost-SHAP and GLR also enables the EGLR to simultaneously capture nonlinear causal relationships and decompose spatial effects. Results identify population density as the most sensitive LST-increasing factor. Impervious surface percentage, building height, elevation, and distance to the nearest water body are positively correlated with LST, while water area, normalized difference vegetation index, and the number of bus stops have significant negative relationships with LST. In contrast, the impact of the number of points of interest, gross domestic product, and road length on LST is not significant overall. Full article

Urbanization markedly influences the microclimatic conditions in semi-arid regions by elevating land surface temperatures (LST) and contributing to ecological degradation. This study examined the spatial and temporal evolution of LST and urban heat island (UHI) effects in Benguerir, Morocco, over a 30-year period (1994–2024), employing high-resolution satellite imagery and in situ sensor data. Urban expansion was quantified using thermal bands from Landsat imagery, the Normalized Difference Built-up Index (NDBI), and the Built-up Index (BU), whereas thermal comfort was evaluated through the Universal Thermal Climate Index (UTCI) and Predicted Mean Vote (PMV) using air temperature and humidity data collected via spatial sensor and the Sniffer Bike mobile sensor network. These urban transformations have intensified the UHI effect, resulting in a 29.34 °C increase in mean LST to 41.82 °C in 2024 across built-up areas. Statistical modeling revealed strong linear relationships between LST and urban indices, with R² values ranging from 0.93 to 0.96, and correlation coefficients around 0.98 (all p-values < 0.001), indicating a reliable model fit. Furthermore, the analysis of thermal comfort trends underscores urbanization’s impact on human well-being. In 1994, 34.2% of the population experienced slight warmth and 65.8% experienced hot conditions. By 2024, conditions had shifted dramatically, with 76.7% experiencing hot conditions and 16.2% exposed to very hot conditions, leaving only 7.1% in the slight warmth category. These findings highlight the urgent need for adaptive urban planning strategies. The implementation of urban greening initiatives, the use of reflective materials, and the integration of data-driven planning approaches are essential to mitigate thermal stress and enhance urban resilience. Leveraging climate modeling and spatial analytics can support the identification of high-risk zones and inform targeted interventions to effectively address the escalating UHI phenomenon. Full article