Search Results (4,595)

Type 2 Diabetes (T2D) is a prevalent metabolic disease with a strong association with cardiovascular complications. This study evaluated glycemic control and lipid profiles (total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides) in patients with T2D, based on glycated hemoglobin and fasting glucose levels, through a cross-sectional analysis of 4814 individuals (mean age: 66.2 ± 16.07 years with normal distribution; 51.5% male) from the Hospital Universitario Lucus Augusti in Northwest Spain. The aim was to assess the metabolic differences and potential influences of age, sex, and geographic setting. We observed that patients with T2D had lower low-density lipoprotein cholesterol, but higher triglycerides and high-density lipoprotein cholesterol levels compared to patients without T2D. A positive correlation was found between age and fasting glucose levels (r = 0.182; p < 0.05), with the highest glucose concentrations occurring in postmenopausal women. No significant differences were observed between rural and urban participants. These findings support the integration of targeted nutritional strategies and education programs in the clinical management of T2D, particularly in older adults. Full article

Urban wastewater is composed of nutrients such as nitrogen and phosphorus, organic matter, heavy metals, pathogens, and micropollutants. If untreated, these contribute to eutrophication and environmental degradation. Microalgae-based bioremediation offers a sustainable solution, showing promise for pollutant removal and high-value bioproduct generation. This study evaluates the efficacy of Galdieria sulphuraria ACUF 427 in treating urban wastewater, with a focus on nutrient removal and phycocyanin production at different optical densities (OD 2, OD 4, and OD 6). Nutrient removal rates (RRs) were analysed for ammonium nitrogen (N-NH₄⁺), ammonia nitrogen (N-NH₃), phosphate phosphorus (P-PO₄³⁻), and chemical oxygen demand (COD). The RR for N-NH₄⁺ increased with optical density, reaching 7.49 mg/L/d at an optical density of 6. Similar trends were observed for N-NH₃ and P-PO₄³⁻, with peak removal at OD 6. COD removal remained high across all ODs, though differences between OD 4 and OD 6 were not statistically significant. Significant variations (p < 0.05) in nutrient removal were noted across the ODs, except for COD between OD 4 and OD 6. Biomass growth and phycocyanin production were significantly higher in the wastewater compared to the control (Allen Medium), with the most effective performance observed at an optical density (OD) of 6. Maximum growth rates were 0.241 g/L/d at OD 6, 0.178 g/L/d at OD 4, and 0.120 g/L/d at OD 2. These results highlight the potential of G. sulphuraria as an agent for wastewater bioremediation and the production of high-value compounds, particularly at elevated cell densities, where we achieved superior nutrient removal and biomass production. Full article

Climate change poses significant threats to urban tree health and survival worldwide. This study evaluates climate suitability risks for 12 common tree species in Wuhan, a Chinese metropolis facing escalating climate challenges. We analyzed risk dynamics and interspecific variations across three periods, the baseline (1981–2022), near future (2023–2050), and distant future (2051–2100), quantifying climate risk as differences between local climate conditions and species’ climatic niches. We further examined how species’ geographic distribution and functional traits influence these climate risks. The results revealed significant warming trends in Wuhan during the baseline period (p < 0.05), with projected increases in temperature and precipitation under future scenarios (p < 0.05). The most prominent risk factors included the precipitation of the driest month (PDM), annual mean temperature (AMT), and maximum temperature of the warmest month (MTWM), indicating intensifying drought–heat stress in this region. Among the studied species, Cedrus deodara (Roxb.) G. Don, Platanus acerifolia (Aiton) Willd., Metasequoia glyptostroboides Hu & W.C.Cheng, and Ginkgo biloba L. faced significantly higher hydrothermal risks (p < 0.05), whereas Koelreuteria bipinnata Franch. and Osmanthus fragrans (Thunb.) Lour. exhibited lower current risks but notable future risk increases (p < 0.05). Regarding the factors driving these interspecific variation patterns, the latitude of species’ distribution centroids showed significant negative correlations with the risk values of the minimum temperature of the coldest month (MTCM) (p < 0.05). Among functional traits, the wood density (WD) and xylem vulnerability threshold (P50) were negatively correlated with precipitation-related risks (p < 0.05), while the leaf dry matter content (LDMC) and specific leaf area (SLA) were positively associated with temperature-related risks (p < 0.05). These findings provide scientific foundations for developing climate-adaptive species selection and management strategies that enhance urban forest resilience under climate change in central China. Full article

Through their open space layout, rich green configuration and low floor area ratio (FAR), low-density commercial blocks show significant advantages in creating high-quality outdoor thermal comfort (Universal Thermal Climate Index, UTCI) environment, reducing regional energy consumption load (building energy consumption, BEC) potential, providing pleasant public space experience and enhancing environmental resilience, which are different from traditional high-density business models. This study proposes a workflow for morphological design of low-density commercial blocks based on parametric modeling via the Grasshopper platform and the NSGA-II algorithm, which aims to balance environmental benefits (UTCI, BEC) and spatial efficiency (FAR). This study employs EnergyPlus, Wallacei and other relevant tools, along with the NSGA-II algorithm, to perform numerical simulations and multi-objective optimization, thus obtaining the Pareto optimal solution set. It also clarifies the correlation between morphological parameters and target variables. The results show the following: (1) The multi-objective optimization model is effective in optimizing the three objectives for block buildings. When compared to the extreme inferior solution, the optimal solution that is closest to the ideal point brings about a 33.2% reduction in BEC and a 1.3 °C drop in UTCI, while achieving a 102.8% increase in FAR. (2) The impact of design variables varies across the three optimization objectives. Among them, the number of floors of slab buildings has the most significant impact on BEC, UTCI and FAR. (3) There is a significant correlation between urban morphological parameters–energy efficiency correlation index, and BEC, UTCI, and FAR. Full article

Suburban forest patches can have important conservation value for birds. This is a hopeful trend because the extent of urbanization is increasing, many avian populations are declining, and urban areas are where most people interact with wildlife. There is evidence that, despite an increased density of potential predators, the breeding success of birds in urban or suburban forest patches is comparable to that in rural areas. However, extremely limited data exists on the fledgling life stage of birds in urban or suburban areas, even though it is known that the fledgling stage strongly influences population growth rates. We used radio telemetry to look at the survival, movement, and habitat use of fledgling Wood Thrushes (Hylocichla mustelina) originating from nests in suburban forest patches and in larger swaths of rural, undeveloped forests in western Massachusetts. We tracked 168 fledglings over four field seasons and found that survival was similar for rural and suburban fledglings. Fledglings had lower mortality as they aged. Force-fledging and being left outside the nest after radio-tagging had a negative effect on survival, and we developed techniques to minimize its occurrence. We also found that rural fledglings moved farther from their natal nests, at any given age, than suburban fledglings. Fledglings in both suburban and rural sites selected denser understory growth, and the use of non-forested land cover increased as they aged. Full article

This study investigates the spatio-temporal characteristics and driving mechanisms of ecological quality in the mountain–river–sea regional system using the Remote Sensing Ecological Index (RSEI) model, moderate-resolution imaging spectroradiometer (MODIS) data, and the Google Earth Engine (GEE) platform. The analysis, conducted at both the grid and county scales using spatial autocorrelation and geodetector, showed a notable improvement in ecological quality, with the average RSEI value rising from 0.549 in 2000 to 0.627 in 2022. The distribution pattern reveals superior quality in the northwest and inferior quality in central urban cores and coastal zones. Ecological quality exhibited significant spatial clustering, with high–high clusters in karst mountains and low–low clusters in urban and industrial zones. Geodetector analysis identified GDP and population density as dominant factors at the grid scale, and GDP and elevation at the county scale. By quantifying spatio-temporal variations and driving mechanisms of ecological quality across scales, this study provides a solid scientific foundation for regional ecological conservation and sustainable development. Full article

The intensification of urban heat in high-density cities has raised growing concerns for public health, infrastructural resilience, and environmental sustainability. As large-scale, multi-functional open spaces, sports stadiums play an underexplored role in shaping urban thermal patterns. This study investigates the spatial and temporal thermal characteristics of eight representative stadiums in central Shanghai and the Pudong New Area from 2018 to 2023. A dual-framework approach is proposed: the Stadium-based Urban Island Regulation (SUIR) model conceptualizes stadiums as active cooling agents across micro to macro spatial scales, while the Multi-source Thermal Cognition System (MTCS) integrates multi-sensor satellite data—Landsat, MODIS, Sentinel-1/2—with anthropogenic and ecological indicators to diagnose surface temperature dynamics. Remote sensing fusion and machine learning analyses reveal clear intra-stadium thermal heterogeneity: track zones consistently recorded the highest land surface temperatures (up to 37.5 °C), while grass fields exhibited strong cooling effects (as low as 29.8 °C). Buffer analysis shows that cooling effects were most pronounced within 300–500 m, varying with local morphology. A spatial diffusion model further demonstrates that stadiums with large, vegetated buffers or proximity to water bodies exert a broader regional cooling influence. Correlation and Random Forest regression analyses identify the building volume (r = 0.81), NDVI (r = −0.53), nighttime light intensity, and traffic density as key thermal drivers. These findings offer new insight into the role of stadiums in urban heat mitigation and provide practical implications for scale-sensitive, climate-adaptive urban planning strategies. Full article

There is a growing global emphasis on reducing environmental pollution through innovative clean energy technologies, with photovoltaic systems gaining prominence as a sustainable solution. This study presents an integrated approach, combining advanced architectural modeling and dynamic energy simulation to evaluate the utilization of rooftop photovoltaic panels on a high-density higher educational building in Saudi Arabia. Utilizing detailed modeling involving Autodesk Revit and energy simulation through DesignBuilder to Level of Detail 3, the research provides unprecedented accuracy, validated against actual energy consumption data with a remarkable 92.28% precision. Notably, approximately 60% of the rooftop area is identified as suitable for photovoltaic installation, demonstrating a significant capacity to generate 1,028,494.50 kWh annually, covering 61.7% of the building’s energy needs. Financial analysis reveals robust economic benefits, including annual savings of USD 74,938.84, a payback period of under 7 years, and lifetime savings exceeding USD 1.87 million over 25 years. Seasonal variations and surplus energy during winter months are also detailed, highlighting the system’s resilience. Importantly, this study aligns with Saudi Arabia’s “Vision 2030” by showcasing the feasibility and strategic importance of rooftop photovoltaic solutions in urban educational settings within hot-climate regions, offering a pioneering contribution to sustainable urban energy planning. Full article

As China’s urbanization deepens, the spatial structure of residential areas and land use patterns has undergone profound transformations, with the differentiation of housing prices emerging as a key indicator of urban spatial dynamics and socioeconomic stratification. This study examines the spatial and temporal evolution of residential housing prices in Qingdao’s main urban area over a 20-year period, using data from three representative years (2003, 2013, and 2023) to capture key stages of change. It employs Local Indicators of Spatial Association (LISA) spatial and temporal path and leap analyses, as well as Geographically and Temporally Weighted Regression (GTWR) modeling. The results show that Qingdao’s housing price patterns exhibit distinct spatiotemporal heterogeneity, characterized by multi-level transitions, leapfrog dynamics and strong spatial dependence. The urban center and coastal zones demonstrate positive synergistic growth, while some inland and peripheral areas show negative spatial coupling. Evident is the spatial restructuring from a monocentric to a polycentric pattern, driven by shifts in industrial layout, policy incentives, and transportation infrastructure. Key driving factors, such as community attributes, locational conditions, and amenity support, show differentiated impacts across regions and over time. Business agglomeration and educational resources are primary positive drivers in central districts, whereas natural environments and commercial density play a more complex role in peripheral areas. These findings provide empirical evidence to inform our understanding of housing market dynamics and offer insights into urban planning and the design of equitable policies in transitional urban systems. Full article

The intensification of the urban thermal environment has brought attention to urban land surface temperature (ULST). Complex building geometry and manmade material lead to significant thermal radiation directionality (TRD) of the urban canopy, and the TRD effect directly influences the accuracy of ULST retrieval algorithms. Therefore, it is essential to understand and eliminate the TRD effect to achieve high-accuracy ULST. In this context, the hemispherical brightness temperature maximum–minimum discrepancy (BTD) was quantitatively analyzed via different spectral bands, component temperature thresholds, urban geometries, and component temperature differences. Meanwhile, the DART simulations database was used to systematically evaluate 1 single-kernel- and 30 dual-kernel-driven models (KDMs), which were combined from 5 base-shape kernels (RossThick, Vinnikov, uea, RossThin, and LSF) and 6 hotspot kernels (RL, Roujean, Vinnikov, LiSparseR, LiDense, and Chen). Results show that the BTD discrepancy (ΔBTD) can reach up to 0.91 K with different band emissivities, whereas the ΔBTD is over 10 K with different component temperature differences. The building density and ratio between building heights and road widths (H/W) also exhibit their importance over urban regions. In addition, the RossThick–/Vinnikov–Roujean dual-kernel KDMs demonstrate better performance with an overall RMSE of 1.12 K. The RL-series KDMs can describe the hotspot distribution well, but the uea-series KDMs outperform at the solar principal plane (SPP) and cross-solar principal plane (CSPP). Specifically, the performance of all KDMs is sensitive to the H/W and component temperature thresholds, and urban geometry can affect the TRD RMSE with increasing H/W and a depletion of high building density. The quantitative TRD analysis and comparison provide a comprehensive reference for understanding the distribution of thermal radiation, which is also a reliable basis for developing the new TRD model over urban regions. Full article

This study presents a multi-objective optimization framework for enhancing environmental performance in high-density residential complexes, addressing the critical balance between sunlight access, visual openness, and ground-level privacy. Applied to Helio City Phase 3 in Seoul—a challenging case with 2026 units surrounded by adjacent blocks—the research developed a sequential three-stage optimization strategy using computational design tools. The methodology employs Ladybug simulations for solar analysis, Galapagos genetic algorithms for view optimization, and parametric modeling for privacy assessment. Through grid-based layout reconfiguration, tower form modulation, and strategic conversion of vulnerable ground-floor units to public spaces, the optimized design achieved 100% sunlight standard compliance (improving from 64.31%), increased average visual openness to 66.31% (from 39.48%), and eliminated all privacy conflicts while adding 30 residential units. These results demonstrate that computational optimization can significantly surpass conventional planning approaches in addressing complex environmental trade-offs. The framework provides a replicable methodology for performance-driven residential design, offering quantitative tools for achieving regulatory compliance while enhancing residents’ experiential comfort in dense urban environments. Full article

The decarbonization of the energy sector drives the implementation of building-integrated and building-applied photovoltaic (BIPV–BAPV) systems. However, these systems face space and design limitations in urban environments. This study proposes an innovative methodology for the design and sizing of urban photovoltaic systems, considering diverse distributions and introducing metrics that link performance to occupied area. The methodology was applied to a university building in southern Spain, comparing the performance of rooftop photovoltaic (RTPV) and facade-applied photovoltaic (FAPV) systems. FAPV showed a larger useful area, resulting in similar self-sufficiency indices (RTPV: 22%, FAPV: 21%) and a 5% higher total emission reduction compared to the RTPV system. The proposed metrics demonstrate that FAPV outperforms RTPV both in final yield (49 vs. 21 kWh/kWp·m²) and total emission reduction (3.1 vs. 1.3 kgCO2eq/kWp·m²) normalized by installed power and occupied area. These complementary metrics are crucial for evaluating and selecting optimal photovoltaic configurations with varying generation densities and efficiencies, driving urban decarbonization and the creation of Zero Energy Buildings (ZEBs). Full article

This study investigates long-term urban air quality and population-level exposure in 33 European capital cities between 2010 and 2024. Using over 3.5 million hourly observations retrieved from official monitoring networks, city-level Air Quality Index (AQI) values were calculated and analyzed for exceedance frequency, seasonal dynamics, and spatial disparities. To account for public health relevance and sustainability implications, the analysis incorporated population-weighted exposure indicators reflecting both pollution severity and urban demographic scale. The results reveal substantial differences in air quality across the continent: cities such as Oslo and Reykjavik consistently maintain low AQI levels, while Sarajevo, Lisboa, and Madrid experience frequent exceedances. Notably, Paris shows the highest cumulative population exposure despite moderate pollution intensity, highlighting how urban density amplifies public health burdens. The use of harmonized AQI and exposure-adjusted metrics enables standardized comparisons across cities and supports sustainability-oriented urban planning. By quantifying unequal exposure burdens across Europe’s capitals, this study contributes to the evidence base for Sustainable Development Goal 11, emphasizing the need for data-informed air quality policies that address both environmental risks and population vulnerability. Full article

Addressing the need to optimize human settlement quality in arid and semi-arid regions under rapid urbanization, this study innovatively constructs an evaluation framework integrating greenness, thermal conditions, impervious surfaces, water bodies, and air transparency. Focusing on 12 prefecture-level cities in Inner Mongolia, Northern China, it systematically reveals the spatial differentiation characteristics and driving mechanisms of human settlement quality. Findings indicate the following: (1) Regional human settlement quality exhibits a spindle-shaped structure dominated by the medium grade (Excellent: 18.13%, High: 23.34%, Medium: 46.48%, Low: 12.04%), with Ulanqab City having the highest proportion of Excellent areas (25.26%) and Ordos City the lowest proportion of Low-grade areas (6.20%), reflecting a critical transition period for regional quality enhancement. (2) Spatial patterns show pronounced east-west gradients and functional differentiation: western arid zones display significant blue-green space advantages but face high-temperature stress and rigid water constraints, eastern humid zones benefit from superior ecological foundations with weaker heat island effects, the core Hetao Plain experiences strong heat island effects due to high impervious surface density, while industrial cities confront prominent air pollution pressures. Consequently, implementing differentiated strategies—strengthening ecological protection/restoration in High/Low-grade zones and optimizing regulation to drive upgrades in Medium-grade zones—is essential for achieving three sustainable pathways: compact development, blue-green space optimization, and industrial upgrading, providing vital decision-making support for enhancing human settlement quality and promoting sustainable development in ecologically fragile cities across northern China. Full article

Air-to-air (A2A) communication plays a vital role in low-altitude unmanned aerial vehicle (UAV) networks and demands accurate channel modeling to support system analysis and design. A key challenge in A2A channel modeling lies in extracting reliable cluster characteristics, which are often limited due to the scarcity of measurement data. To overcome this limitation, a cluster characteristic analysis method is proposed for UAV A2A channels in built-up environments. First, we reconstruct virtual urban environments, followed by the acquisition of A2A channel data using ray tracing (RT) techniques. Then, a kernel power density (KPD) clustering algorithm is applied to group the multipath components (MPCs). To enhance the modeling accuracy of intra-cluster angular offsets in both elevation and azimuth domains, a Wasserstein generative adversarial network with gradient penalty (WGAN-GP) is further introduced for generative modeling. A comprehensive analysis is conducted on key cluster characteristics, including the intra-cluster number of MPCs, intra-cluster delay and angular spreads, number of clusters, and angular distributions. The numerical results demonstrate that the proposed WGAN-GP-based approach achieves superior angular fitting accuracy compared to conventional empirical distribution methods. Full article