Search Results (3,871)

Amid global urban transition from sprawling expansion to stock-oriented regeneration, exploring the spatiotemporal heterogeneity and mechanisms of urban spatial vitality in old urban areas is crucial for advancing sustainable urban renewal and enhancing human well-being. This study builds a built environment index system, taking the old urban areas of Wuwei City, China, as a case study, and employs the MGWR model to analyze spatial vitality and its drivers. Results show: (1) Diverse functional elements exhibit significant spatiotemporal variations, with basic living facilities having stable impacts, while cultural and catering facilities show morning local agglomeration and nighttime region-wide driving effects, respectively. (2) Regarding accessibility, the road network is a key spatial factor. It shows a positive statistical association with regional vitality during the day, but may correlate with traffic and environmental stress at night. This indicates a potential trade-off between commercial activity and residential comfort across different time periods. (3) Spatial quality elements show strong spatial stability. Specifically, floor area ratio and open space ratio exhibit positive statistical associations with vitality, while building density and height tend to show negative correlations. This may reflect structural bottlenecks imposed by high-density development on sustainable living spaces. (4) Strategies like micro-functional layouts, day-night differentiated traffic networks, and spatial chassis optimization are proposed to provide quantitative evidence for sustainable stock-oriented regeneration, balancing heritage conservation with modern urban vitality. Full article

Urban heat islands pose increasing risks to human settlements, yet the differential mechanisms by which grey–green spaces regulate diurnal and nocturnal land surface temperature across local climate zones remain insufficiently understood. This study addresses this gap through a Hangzhou case study, integrating a ten-indicator grey–green space system with two local spatial identification approaches—K-means clustering and an LCZ-inspired simplified scheme—and a Random Forest-SHAP framework. The LCZ-inspired scheme outperformed K-means clustering, with a mean diurnal–nocturnal Test R² of 0.4344 across twelve models, compared to 0.2977 for K-means. Diurnal and nocturnal LST were driven by systematically different factors: building density dominated daytime LST in most LCZ types (22.0% to 27.8%), while canopy height dominated nighttime LST (22.7% to 30.2%), revealing a systematic shift from building-dominated daytime to vegetation-dominated nighttime. This shift did not occur in compact built-up areas, suggesting that built-up density may be a threshold condition for the shift. Key variables exhibited nonlinear threshold effects with saturation points varying by LCZ type: canopy height cooling saturated at approximately 4 m in LCZ2 but required 17–21 m in LCZ3 and LCZA. These SHAP-based patterns and turning points should be regarded as exploratory, sample-dependent associations evaluated within the training data; their spatial stability across held-out regions was not assessed. Factor interactions were interval-dependent rather than globally fixed. Spatial cross-validation confirmed that random splitting substantially overestimated model performance, highlighting the necessity of spatially explicit validation. The methodological framework provides a replicable approach for urban thermal environment research and offers LCZ-specific threshold hypotheses for thermal regulation planning in subtropical megacities, subject to further spatial and cross-city validation. Full article

Osmotic energy conversion (blue energy), serving as a sustainable marine renewable energy source, converts Gibbs free energy originating from salt concentration differences into electric power by virtue of ion-selective nanofluidic membranes. Conventional commercial ion-exchange polymer membranes suffer from inherent limitations, including low transmembrane flux, insufficient ion permselectivity, severe interfacial concentration polarization, poor salt tolerance, and unsatisfactory long-term structural stability. These drawbacks greatly restrict the energy conversion efficiency and large-scale engineering application of reverse electrodialysis (RED). Conductive polymers (CPs), mainly including polypyrrole (PPy), polyaniline (PANI), polythiophene (PTh), and their derivatives, possess the distinctive merits of tunable surface charge density and polarity, outstanding electronic conductivity, facile nanochannel structural regulation, and reversible redox responsiveness, making them ideal building blocks for advanced nanofluidic membranes for high-efficiency osmotic energy conversion. This review summarizes recent progress in the fabrication of conductive polymer-based nanofluidic membranes, comprehensively compares the osmotic output performance of typical CP material systems, and discusses the core metrics of osmotic energy conversion output performance. By providing an overview of these developments, this review aims to offer insights into the future development of conductive polymer-based nanofluidic membranes for osmotic energy conversion. Full article

Accurate prediction of building energy consumption is critical for sustainable urbanization, while dynamic occupant interactions with the building envelope remain a major source of uncertainty. Prevailing cross-scale building energy models often rely on simplified or uniform behavioral assumptions that cannot adequately represent the spatial and temporal heterogeneity of occupant actions such as window opening and curtain use. This study proposes an AI-augmented framework that integrates field-observed occupant behavior, machine-learning prediction, and physics-based building energy simulation. Time-series observations of window and curtain states were collected from 1609 rooms across 12 residential buildings in a high-density neighborhood in Hong Kong. Environmental and contextual associations were first examined at the aggregated behavioral level, after which Random Forest models were used to generate dynamic behavior schedules. These schedules were subsequently integrated into EnergyPlus to evaluate how different levels of occupant behavior representation affect simulated cooling energy demand and computational cost. Compared with the Detailed Scenario, the Template Scenario produced 20.5% higher simulated cooling energy, while the Average Scenario showed an 8.7% relative difference with 20.6% less simulation time. An additional controlled analysis showed that removing surrounding buildings increased simulated cooling energy by 1.7–9.3%, demonstrating the direct physical influence of inter-building shading. Overall, the proposed framework provides a practical pathway for incorporating context-dependent occupant behavior into urban building energy modeling and for evaluating the trade-offs between behavioral modeling detail and computational efficiency. Full article

Plant-derived residues are promising renewable feedstocks for bio-based building materials, but their suitability depends on structural, thermophysical, fire-related, and mineral characteristics. This study characterises ten plant residues—corn stalk (CS), hemp stalk (HS), luffa (Lu), olive branches (OB), olive pit (OP), Posidonia oceanica (PO), rice husk (RH), rice straw (RS), sunflower stalk (SS), and wheat straw (WS)—to establish a first-stage screening framework for lightweight construction applications. The raw materials were assessed through morphological, density-related, microstructural, thermophysical, thermogravimetric, and microscale combustion analyses, while their calcined fractions were examined by ash-yield determination, X-ray fluorescence, and X-ray diffraction. Apparent bulk density varied by approximately a factor of 30, from 0.0275 g cm⁻³ for RS to 0.8279 g cm⁻³ for OP, while thermal conductivity ranged from 0.0436 to 0.1204 W/(m·K). Most residues remained within the range associated with lightweight insulation, whereas OP showed the highest conductivity. Peak heat release rate (PHRR) ranged from 45.7 W g⁻¹ for PO to 145.5 W g⁻¹ for Lu, with SS also showing low heat-release parameters. Ash yield varied from 1.66% to 26.23%, accompanied by silica-rich, calcic, alkali-rich, amorphous, and crystalline mineral profiles. The results provide preliminary criteria for categorising and prioritising residues for lightweight insulation-oriented applications or mineral-related valorisation, as a basis for future composite development and application-level validation. Full article

Large-scale and recurrent Sargassum beaching events along the coastlines of Brazil, Mexico, and the Caribbean pose significant environmental, social, and economic challenges due to biomass accumulation and decomposition. Meanwhile, valorization of underutilized waste streams into composite materials can advance circular economy strategies. Building upon previous findings on Sargassum-based particleboards, this study investigated increased pressing temperature and residual high-density polyethylene (HDPE) incorporation as strategies to improve dimensional stability. Medium-density particleboards were manufactured from Sargassum biomass and sugarcane bagasse, with and without residual HDPE, using bio-based castor oil polyurethane resin. The panels were characterized regarding physical, mechanical, and thermal properties to assess their suitability for non-structural applications. HDPE-containing formulations showed reduced 24 h thickness swelling from 21% to 15%, while exhibiting an overall reduction in mechanical performance, particularly in bending and internal bond strength properties. Despite this trade-off, the developed particleboards demonstrated potential for furniture and indoor building applications while simultaneously valorizing marine, agro-industrial, and plastic residues. These findings support Sargassum biomass as a sustainable feedstock for particleboard production and indicate that residual HDPE can improve 24 h thickness swelling performance, contributing to circular economy strategies and low-impact material development for applications across the built environment sector. Full article

Accurate estimation of regional forest carbon storage is essential for assessing forest carbon sink capacity and supporting climate change mitigation. This study developed a UAV-LiDAR-assisted multi-source remote sensing approach to estimate forest AGB and carbon storage in Fuzhou City. UAV-LiDAR data acquired close to satellite overpasses were used to generate temporally matched plot-scale AGB samples through individual-tree segmentation, tree height–DBH estimation, and allometric equations. After screening, 204 samples were retained. Four predictor combinations (Landsat, SAR, Landsat + SAR, and Landsat + SAR + other factors) were combined with SWR and CatBoost to build eight AGB models after RF-RFE feature selection. The optimal model was applied to analyze forest carbon storage changes from 2015 to 2023. CatBoost generally outperformed SWR, with lower RMSE, MAE, and rRMSE. The CatBoost model integrating Landsat, SAR, and other factors performed best (RMSE = 19.83 t·hm⁻², MAE = 17.02 t·hm⁻², rRMSE = 21.73%). Forest carbon storage increased from 32.43 × 10⁶ t in 2015 to 36.76 × 10⁶ t in 2023, alongside increases in forest area and carbon density. These findings suggest the potential of UAV-LiDAR for temporally matched AGB sampling and regional forest carbon storage estimation in subtropical areas, contributing to relevant SDGs. Full article

This article investigates the numerical simulation of heat-and-aerodynamic cycles in the ventilated air gap of a multilayer composite wall façade system in a hot climate using ANSYS 19/2 Fluent. Standard normative techniques rely on averaged, stationary boundary conditions and account for neither the height-wise inequality of solar exposure nor the dependence of air density and viscosity on barometric pressure and temperature, resulting in significant errors in predicting the actual heating of such structures. The model was calibrated on the authors’ own full-scale, in situ measurements of temperature, air speed and solar exposure in the ventilated gap of a nine-storey building, from which linear height-dependent surface-temperature relations were derived and used as boundary conditions for 3D models of façades 25 and 60 m tall. Thirty-two finite-volume experiments were performed under free convection (Boussinesq approximation), varying gap width (5 and 10 cm), inlet width (20 and 40 cm), barometric pressure (690 and 770 mmHg) and external air temperature (20 and 40 °C). Façade height proved the dominant factor (air speed up to 1.8 times higher, temperature 3–12.1 °C higher), followed by gap width (speed lower by 1.7 times, temperature by 3–5 °C), whereas pressure and inlet width altered the results by no more than 6%. Discrepancies with the standard calculation reached 10 °C in temperature and a two-fold difference in flow speed, confirming the need for verified CFD simulation when designing ventilated composite wall façades in hot climates. Full article

Waveguide crossings are fundamental building blocks of high-density photonic integrated circuits and on-chip optical routing systems. However, realizing a high-performance, compact waveguide crossing on a lithium niobate-on-insulator (LNOI) platform remains challenging because conventional designs often rely on larger device dimensions to meet stringent performance requirements. Furthermore, narrow single-mode waveguides provide strong mode confinement but are more sensitive to fabrication-induced sidewall roughness due to stronger interaction between the guided mode and the waveguide sidewalls. In contrast, increasing the waveguide width can reduce the sensitivity to sidewall roughness but may introduce higher-order modes. Here, we propose and experimentally demonstrate an inverse-designed waveguide crossing on the LNOI platform. To enable greater flexibility in manipulating light within a compact footprint, the waveguide crossing is optimized using particle swarm optimization (PSO) combined with finite-difference time-domain (FDTD) simulations to enhance TE₀-mode transmission. Meanwhile, to reduce sidewall-induced scattering while preserving predominantly TE₀ mode transmission, 2 μm wide multimode input and output waveguides are adopted. The fabricated crossing occupies a footprint of 14.55 μm × 14.55 μm and exhibits an insertion loss below 0.1 dB and crosstalk below −29 dB over the wavelength range of 1480–1640 nm. The demonstrated device provides a favorable trade-off among insertion loss, crosstalk, operating bandwidth, footprint, and fabrication simplicity compared with representative previously reported LNOI waveguide crossings. The PSO-assisted framework is extendable to other LNOI devices, enabling dense photonic integration. Full article

The city center of Kahramanmaraş suffered considerable damage as a result of the Mw 7.7 Pazarcık and Mw 7.6 Elbistan earthquakes, which took place on 6 February 2023. The present study examines the impact of urban development, groundwater conditions, and paleo-drainage systems on the pattern of earthquake damage in the Dulkadiroğlu and Onikişubat districts, which make up the urban center of Kahramanmaraş. Geological, hydrogeological, geomorphological, urban development, and building damage data were combined and analyzed using a GIS environment. Kernel Density Estimation (KDE) and spatial overlay analyses were carried out in order to show the spatial concentration of the damage. The results show that severely damaged or collapsed buildings were not distributed at random; rather, they were found in regions featuring largely young geological units, shallow groundwater levels, and former stream channels. In several areas where rapid urban expansion has occurred over the past thirty years, there is a clear spatial relationship between high damage densities and paleo-drainage systems. These findings reveal a spatial relationship between severe building damage and areas characterized by alluvial deposits, reconstructed paleo-drainage corridors, and potentially shallow groundwater conditions. Although the available data do not allow the damage to be directly attributed to site amplification or other geotechnical mechanisms, the observed spatial patterns identify areas where local ground conditions warrant further geotechnical and seismological investigation. Full article

Reference building models can serve as a common baseline for research investigations and evaluations of design choices. Despite lighting being one of the largest single users of electricity in commercial buildings, lighting systems in reference buildings are commonly modeled as maximum building-type or space-type power densities defined in building energy codes. Further, energy use is typically estimated by modulating the lighting power over the course of a day via simple occupancy schedules that may not accurately portray human behavior or the performance of occupancy-based lighting controls. While this approach is suitable for some use cases, it is not adequate for exploring the impact of luminaire selection, space-specific control strategies, and occupant behavior. This paper presents the development of a high-fidelity reference model of a medium office building that includes interior architecture, an occupant distribution model, and a detailed lighting design intended to support more realistic evaluations of lighting control strategies and approaches to modeling occupant behavior. The model includes 13 market-representative LED luminaires, meets occupant lighting needs by complying with applicable recommended practices defined by the Illuminating Engineering Society (IES), and meets energy code power density and control strategy requirements in ANSI/ASHRAE/IES 90.1-2019. The luminaire-level connected load (26,037 W) of the lighting layout is lower than what would be estimated by simple building-type (34,304 W) and space-type (31,200 W) power density methods. The model includes 12 space types and 107 rooms with workstations for 268 occupants. The interior architecture varies on each of the three floors to introduce room and space-type diversity that further exposes the impact of design choices and occupant behavior. The model has already been used as a baseline for research on circadian lighting design strategies, lighting–HVAC data integration, and whole-building life-cycle assessments—demonstrating its utility as a common reference for a range of lighting research. Full article

Nb-containing TiAl alloys are among the most important lightweight intermetallics for high-temperature applications because they combine low density with useful strength, oxidation resistance and creep resistance. Their long-standing difficulty is equally clear: the ordered γ/α₂ matrix and lamellar hierarchy that support thermal stability also restrict plastic accommodation and manufacturing tolerance. This Perspective addresses a specific question: how can Nb–Ti–Al-related alloy design expand from stabilizing ordered TiAl matrices toward matrices and architectures that also enable scalable deformation and processing? The discussion is organized around three connected routes. High-Nb TiAl alloys established a durable service-stability platform; lamellar, colony, and orientation engineering then created deformation pathways within ordered matrices, and compositionally adjacent Zr–Ti–Nb–(Al)-concentrated BCC alloys introduced a different matrix-selection strategy in which chemical disorder and BCC stability are used to build processability at an earlier stage of design. These routes solve different parts of the same design problem rather than representing direct competitors. They indicate that future lightweight high-temperature alloys should be designed by linking composition selection, phase architecture, thermomechanical processing and environmental validation within a processability–stability framework. Full article

Significant research efforts have recently focused on nanomaterial processing for gas sensors and related sensing applications. However, the major challenges in the field involve the choice of material for the sensing layer of the sensor device element, together with the right structure, assembly, and morphology through which the full sensing properties of the material can be realised. Herein, we critically review the hierarchical nanostructures of V₂O₅ nanomaterial for application in gas sensing technology. Beyond the sheet structure, which serves as the fundamental building block of the V₂O₅’smolecular arrangement, nanostructures ranging from nanobelts to nanowires, nanorods, nanoribbons, nanofibres, nanotubes, and thin films were discovered as preferred configurations and thermodynamically favourable structures, according to many synthesis processes. Ethanol (C₂H₅OH) and Nitrogen dioxide (NO₂) gases were identified as preferred molecules commonly detected by various V₂O₅ morphologies, with the nanotube structure showing preferential sensitivity and selectivity to C₂H₅OH. We also discuss perspectives from density functional theory (DFT) studies of V₂O₅ nanostructures and other (2D) materials structures for gas sensing applications. The studies highlight enhanced adsorption energy, increase conductivity, and band gap variation as a result of an upper shift in the Fermi level, all as a consequence of surface interaction between semiconductor crystal orientation and chemical molecules. Finally, our calculations of the optimised parameters for α-V₂O₅ orthorhombic structure showed good agreement with experimental and other theoretical data in the literature. The adsorption energy profile for NO₂ molecules revealed that the Ag-doped surface exhibits the most negative adsorption energy compared with the clean surface and other doped surfaces. Full article

Large university campuses need timely, privacy-conscious information about how indoor spaces are used in order to improve space management, energy efficiency, and operational responsiveness. Yet many indoor positioning solutions still depend on additional hardware such as Bluetooth Low Energy beacons, ultra-wideband anchors, or camera-based sensing, which increases deployment cost and maintenance complexity. This paper presents a lightweight campus occupancy analysis and indoor localization framework that reuses an existing Cisco Wireless LAN Controller (WLC) infrastructure as a sensing layer. The system retrieves received signal strength indicator (RSSI) observations from access points over secure SSH sessions, converts these observations into approximate distance estimates through a calibrated log-distance path loss model, and computes user positions using weighted non-linear least-squares multilateration (Mlat). In addition to point localization, the framework generates occupancy heatmaps, cumulative reliability curves, and access-point-density sensitivity analyses based on a 50 m × 50 m evaluation scenario with 500 randomized samples. To support privacy-preserving deployment, the service layer exposes only zone-level occupancy information and omits personally identifiable network identifiers. The results indicate that Wi-Fi-based localization can provide cost-effective and scalable occupancy intelligence with sufficient accuracy for campus-wide density monitoring and smart building applications.$\times$ Full article

Urban vitality matters for urban regeneration, yet built-environment–vitality associations vary spatially and by variable. We examined 2621 regular 500 m grid cells across Changchun’s built-up area. PCA combined 2024 population, 2024 nighttime light, and 2018 mean building height into a composite Urban Vitality index. Five built-environment indicators—Functional Density, POI Diversity, Mean NDVI, Transit Proximity, and Commercial Proximity—were analyzed using Global Moran’s I, ordinary least squares (OLS), geographically weighted regression (GWR), and multiscale geographically weighted regression (MGWR). PC1 explained 82.15% of the variance, and Urban Vitality showed strong spatial autocorrelation (Moran’s I = 0.8332). Model fit increased from OLS (R² = 0.7767) to GWR (R² = 0.9225) and MGWR (R² = 0.9296). MGWR bandwidths were localized for Functional Density (61), POI Diversity (62), and Mean NDVI (71), but broader for Transit Proximity (2548) and Commercial Proximity (2619). Adjusted local inference identified significant positive associations for Functional Density, POI Diversity, and Transit Proximity, significant negative associations for Mean NDVI, and no significant local association for Commercial Proximity. Although sensitivity analyses generally preserved fit and median directions, excluding building height changed the Transit Proximity bandwidth from 2548 to 70 neighbors, indicating that its estimated association scale was sensitive to vitality-index specification. Commercial Proximity also remained sensitive to indicator operationalization. The findings identify where local diagnostic follow-up is warranted, while intervention effects remain outside the scope of the analysis. Full article