Search Results (1,200)

To address the scientific gap concerning optimal urban wind turbine morphology, this work presents an experimental performance comparison between two small-scale wind turbine designs: a conventional three-blade horizontal-axis wind turbine (HAWT) and a duct-equipped Ayanz-inspired screw-blade turbine. Both configurations were tested in a controlled wind tunnel under steady and transient wind conditions, including synthetic gusts designed to emulate urban wind patterns. The analysis focuses on power output, aerodynamic efficiency (via the power coefficient C_p), dynamic responsiveness, and integration suitability. A key novelty of this study lies in the full-scale experimental comparison between a non-conventional Ayanz screw-blade turbine and a standard three-blade turbine, since experimental data contrasting these two geometries under both steady and gusty urban wind conditions are extremely scarce in the literature. Results show that while the three-blade turbine achieves a higher C_ppeak and greater efficiency near its optimal operating point, the Ayanz turbine exhibits a broader performance plateau and better self-starting behavior under low and fluctuating wind conditions. The Ayanz model also demonstrated smoother power build-up and higher energy capture under specific gust scenarios, especially when wind speed offsets were low. Furthermore, a methodological contribution is made by comparing the C_p vs. tip speed ratio λ curves at multiple wind speeds, providing a novel framework (plateau width analysis) for realistically assessing turbine adaptability and robustness to off-design conditions. These findings provide practical insights for selecting turbine types in variable or urban wind environments and contribute to the design of robust small wind energy systems for deployments in cities. Full article

The adaptive reuse of industrial heritage is increasingly recognized as an effective low-carbon strategy that reduces resource consumption, lowers embodied carbon emissions, and supports sustainable urban transitions. Developing appropriate reuse strategies, however, requires a robust understanding of heritage value. As material evidence of China’s modern industrialization, railway-associated industrial heritage possesses the characteristics of linear cultural heritage. Yet systematic and multi-scalar value assessments from a linear heritage perspective remain limited. Focusing on the Guanzhong Section of the Longhai Railway—one of the most representative industrial development axes in Northwest China—this study establishes a two-level value assessment framework and conducts a comprehensive evaluation of fourteen textile industrial heritage units. At the individual level, five dimensions—historical significance, architectural features, structural integrity, authenticity, and rarity—were assessed through field investigation, and type-specific weights were introduced to correct structural imbalances between quantity and value across building categories. At the unit level, the Analytic Hierarchy Process (AHP) was employed to determine the weights of spatial–functional integrity, process completeness, railway connectivity, industrial landscape characteristics, and the integrated individual-level value. The results show that factory workshops and warehouses consistently exhibit the highest value, whereas structures and residential buildings, despite their numerical dominance, contribute relatively little. Spatially, a clear west–east gradient emerges: high-value units cluster in Baoji and Xi’an, medium-value units in Xianyang, and low-value units mainly in Weinan and surrounding counties. The findings indicate that textile industrial heritage along the Guanzhong Section forms a railway-linked linear cultural heritage system rather than isolated sites. The proposed evaluation framework not only supports heritage identification and conservation planning but also provides a theoretical basis for promoting low-carbon adaptive reuse of existing industrial buildings. Full article

Population activity drives urban development, and high-spatiotemporal-resolution population distribution provides critical insights for refined urban management and social services. However, mixed population activity patterns and spatial heterogeneity make simultaneous high-temporal- and -spatial-resolution estimation difficult. Therefore, we propose the High-Spatiotemporal-Resolution Population Distribution Estimation Based on the Strong and Weak Perception of Population Activity Patterns (SWPP-HSTPE) method to estimate hourly population distribution at the building scale. During the weak-perception period, we construct a Modified Dual-Environment Feature Fusion model using building features within small-scale grids to estimate stable nighttime populations. During the strong-perception period, we incorporate activity characteristics of weakly perceived activity populations (minors and older people). Then, the Self-Organizing Map algorithm and spatial environment function purity are used to decompose mixed patterns of strongly perceived activity populations (young and middle-aged) and to extract fundamental patterns, combined with building types, for population calculation. Results demonstrated that the SWPP-HSTPE method achieved high-spatiotemporal-resolution population distribution estimation. During the weak-perception period, the estimated population correlated strongly with actual household counts (r = 0.72) and outperformed WorldPop and GHS-POP by 0.157 and 0.133, respectively. During the strong-perception period, the SWPP-HSTPE model achieves a correlation with hourly population estimates that is approximately 4% higher than that of the baseline model, while reducing estimation errors by nearly 2%. By jointly accounting for temporal dynamics and population activity patterns, this study provides valuable data support and methodological insights for fine-grained urban management. Full article

The paper examines the phenomenon of urban envelopes, a conceptual parallel to building envelopes, which is considered an emerging theme in studies of the built environment. The term ‘envelope’ refers to various physical and non-physical occurrences in the built environment that delimit, enclose, or demarcate spatial configurations. In the first part of the paper, six distinct types of urban envelopes are identified: physical, programmatic, technological, ecological, environmental, and representational. These are defined based on a systematic literature review to clarify their form, role, and meaning in the context of contemporary cities. All six urban envelope types are formalised using ontology-building methods in Protégé and visualised through WebVOWL, producing domain-agnostic RDF/OWL models that support semantic interoperability. The results provide a concise definition of urban envelopes, which are becoming increasingly relevant in their non-physical representations, such as spaces of control (surveillance of public urban spaces), dynamic environmental and ecological phenomena (pollution, heat islands, and more), temporal or dynamic definitions of space use, and many others in the context of contemporary smart city development. The analysis of possible alignment with existing smart city-related ontologies is presented. By providing the methodology for linking urbanistic principles with data-driven smart city frameworks, the paper provides a unified methodological foundation for incorporating such emerging spatial phenomena into formal urban models. Full article

As urbanization and extreme weather conditions intensify, the comprehensive performance requirements for building waterproofing systems are becoming more demanding. Single-layer waterproof membranes often struggle to meet usage requirements in complex environments, leading to the gradual rise of composite waterproof systems. This paper selects three different types of waterproof membranes, ultra-thin reinforced self-adhesive polymer-modified bitumen waterproof membrane, polymer self-adhesive waterproof membrane, and polymer-modified bitumen root penetration-resistant waterproof membrane, and conducts a systematic study on their compatibility and durability. Through tensile performance, low-temperature flexibility, and peel compatibility tests, combined with thermal oxidative aging experiments at different aging times, the mechanical behavior, low-temperature adaptability, and interfacial bonding characteristics of the membranes were analyzed. The results show that the three membranes differ significantly in tensile performance. The root penetration-resistant membrane has the highest strength but is more brittle, the polymer self-adhesive membrane has lower strength but better stability, and the ultra-thin reinforced membrane performs better initially but lacks durability. In terms of low-temperature flexibility, the root penetration-resistant membrane demonstrates superior crack resistance and aging resistance. These divergent aging responses are closely related to differences in reinforcement structure, polymer modification, and the thermal–oxidative sensitivity of the bituminous adhesive layers. Peel compatibility tests show that the peel strength of the composite membranes of the ultra-thin reinforced and polymer self-adhesive membranes is significantly improved, indicating a good synergistic effect and compatibility. Overall, different waterproof membranes exhibit distinct compatibility mechanisms and aging patterns in composite applications, providing a scientific basis for the design and optimization of composite waterproof systems. Full article

Road transport systems are central to sustainable mobility and the energy transition because they account for a large share of final energy use and remain heavily dependent on fossil fuels. With more than 90% of transport energy still supplied by petroleum-based fuels, improving energy efficiency and reducing emissions in road networks has become a strategic priority. This review compares Australia, Hong Kong, and the United Kingdom to examine how road-design standards and emerging digital technologies can improve energy performance across planning, design, operations, and maintenance. Using Australia’s Austroads Guide to Road Design, Hong Kong’s Transport Planning and Design Manual (TPDM), and the UK’s Design Manual for Roads and Bridges (DMRB) as core reference frameworks, we apply a rubric-based document analysis that codes provisions by mechanism type (direct, indirect, or emergent), life-cycle stage, and energy relevance. The findings show that energy-relevant outcomes are embedded through different pathways: TPDM most strongly supports urban operational efficiency via coordinated/adaptive signal control and public-transport prioritization; DMRB emphasizes strategic-network flow stability and whole-life carbon governance through managed motorway operations and life-cycle assessment requirements; and Austroads provides context-sensitive, performance-based guidance that supports smoother operations and active travel, with implementation varying by jurisdiction. Building on these results, the paper proposes an AI-enabled benchmarking overlay that links manual provisions to comparable energy and carbon indicators to support cross-jurisdictional learning, investment prioritization, and future manual revisions toward safer, more efficient, and low-carbon road transport systems. Full article

This study advances the reconceptualization of Open municipal markets (OMMs) as networked ecosystems that connect food producers, vendors and citizenship across rural and urban contexts, sustaining short food supply chains and reinforcing territorial resilience through the interplay of mobility and embeddedness. Aimed at understanding OMMs as components of a broader, networked and adaptable food ecosystem, the research introduces a new methodology that builds on existing scholarship framing markets as relational and mobile spaces. It contributes to the literature by integrating these perspectives into an ecosystemic lens. By applying a mobility-based approach, the research shifts attention from static views of markets to their dynamic and circulatory nature, highlighting their role in fostering more sustainable and socially rooted food systems. Focusing on 105 OMMs in the Province of Girona (Spain), the research combines spatial analysis and data analysis of 300 surveys completed by 300 stallholders to examine how mobility practices shape market dynamics. The paper provides a new methodology of market stallholders and types of markets as well as four key indicators (recurrence, variety, closeness and rootedness) to assess stallholder activity and territorial embeddedness. These findings reveal that stallholders, particularly producers, connect rural production with urban consumption through flexible and multi-scalar circuits. The paper advocates for ecosystem-based urban food planning that harnesses stallholder mobility to strengthen territorial cohesion and food sovereignty, positioning OMMs as strategic public facilities for resilient and socially responsible food systems. Full article

The urban heat island (UHI) effect, intensified by rapid urbanization, necessitates the precise identification and mitigation of thermal sources and sinks. However, existing studies often overlook landscape connectivity and rarely analyze integrated source–sink networks within a unified framework. To address this gap, this research combines source–sink theory with the local climate zone classification to examine the spatiotemporal patterns of thermal characteristics in Fuzhou, China, from 2016 to 2023. Using morphological spatial pattern analysis, the minimum cumulative resistance model, and a gravity model, we identified key thermal source and sink landscapes, their connecting corridors, and barrier points. Results indicate that among built-type local climate zones, low-rise buildings exhibited the highest land surface temperature, while LCZ E and LCZ F were the warmest among natural types. Core heat sources were primarily LCZ 4, LCZ 7, and LCZ D, accounting for 19.71%, 13.66%, and 21.72% respectively, whereas LCZ A dominated the heat sinks, contributing to over 86%. We identified 75 heat source corridors, mainly composed of LCZ 7 and LCZ 4, along with 40 barrier points, largely located in LCZ G and LCZ D. Additionally, 70 heat sink corridors were identified, with LCZ A constituting 96.39% of them, alongside 84 barrier points. The location of these key structures implies that intervention efforts—such as implementing green roofs on high-intensity source buildings, enhancing the connectivity of cooling corridors, and performing ecological restoration at pinpointed barrier locations—can be deployed with maximum efficiency to foster sustainable urban thermal environments and support climate-resilient city planning. Full article

Timely and accurate urban change detection is vital for sustainable urban development, infrastructure management, and disaster response. Traditional two-dimensional approaches often overlook vertical and structural variations in dense urban areas. This study proposes a three-dimensional (3D) change detection framework that integrates high-resolution optical imagery and Digital Surface Models (DSMs) from two time points to capture both horizontal and vertical transformations. The method is based on a deep learning architecture combining a ResNet34 encoder with a UNet++ decoder, enabling the joint learning of spectral and elevation features. The research was carried out in two stages. First, a binary classification model was trained to detect areas of change and no-change, allowing direct comparison with conventional methods such as Principal Component Analysis (PCA), Change Vector Analysis (CVA) with thresholding, K-Means clustering, and Random Forest classification. In the second stage, a multi-class model was developed to categorize the types of structural changes, including new building construction, complete destruction, building height increase, and height decrease. Experiments conducted on a high-resolution urban dataset demonstrated that the proposed CNN-based framework significantly outperformed traditional methods, achieving an overall accuracy of 96.58%, an F1-score of 96.58%, and a recall of 96.7%. Incorporating DSM data notably improved sensitivity to elevation-related changes. Overall, the ResNet34–UNet++ architecture offers a robust and accurate solution for 3D urban change detection, supporting more effective urban monitoring and planning. Full article

Urban resilience has emerged as a crucial objective for achieving sustainable urban development. However, its practical integration into planning remains limited. This study evaluates the extent to which resilience thinking is integrated into Chengdu’s urban planning system by combining policy-theoretical analysis with empirical evidence. Drawing on a framework of nine resilience attributes, we conduct content analysis of Chengdu’s three types of statutory plan documents (Socioeconomic Development Plan, Urban and Rural Plan, and Land Use Plan) and a questionnaire survey of 70 expert planners. The results reveal that resilience is reflected implicitly in the plans through engineering-oriented attributes such as robustness, efficiency, and connectivity. In contrast, social and ecological attributes like inclusion, redundancy, and innovation are largely absent. Planners demonstrate moderate awareness of resilience, yet associate it predominantly with rapid response and infrastructure robustness rather than long-term adaptation or community capacity-building. These findings indicate the dominant top-down, growth-centric planning logic that constrains the adoption of broader socio-ecological resilience concepts. This paper concludes with policy recommendations for institutionalizing resilience in Chinese urban planning through legal mandates; multi-sectoral coordination; and participatory, adaptive planning frameworks. Full article

As urban architecture continues to emphasize integration with natural environments, the concept of waterfront buildings and blue–green spaces has been widely applied in the site selection of large urban structures. While existing research has extensively explored architectural types such as waterfront landscapes and sports venues, systematic studies on waterfront concert halls, as an important category of cultural architecture, remain limited. Specifically, the interaction mechanisms between such halls and their aquatic environments, as well as their impact on users’ psychological satisfaction, have not been thoroughly investigated. This study takes waterfront concert halls as representative cultural buildings and examines 1267 users from 12 typical waterfront concert halls across eight cities in China. A theoretical model was constructed with water visibility, water accessibility, water interactivity, and water integration as independent variables, biophilia and a sense of nature’s presence as parallel mediators, and user satisfaction as the dependent variable. Data were analyzed using covariance based structural equation modeling CB-SEM. The findings reveal that (1) water visibility, water accessibility, and water integration positively influence user satisfaction; (2) biophilia mediates the relationship between water visibility, water accessibility, water interactivity, water integration, and user satisfaction; (3) a sense of nature’s presence also mediates the relationship between these water-related variables and user satisfaction. This study empirically demonstrates the dual pathway psychological mechanism through which water elements influence user satisfaction, providing a new perspective for the design of waterfront cultural architecture. The research suggests that architects can enhance users’ biophilic instincts and sense of nature’s presence through specific design strategies, such as strengthening water visibility, optimizing waterfront circulation, and enriching water interaction experiences. These findings offer theoretical support for shifting contemporary architectural practice from physical space creation to environmental well-being promotion, while also establishing a practical foundation for developing human-centered evaluation systems for built environments. Full article

Against the backdrop of accelerating population aging, urban green spaces have become primary venues for elderly daily activities, with their winter thermal comfort emerging as a critical determinant of senior wellbeing. However, existing studies lack quantitative guidelines on how plant characteristics affect thermal comfort, limiting age-friendly design. Thirty representative landscape space sites (waterfront, square, dense forest, and sparse forest) in Beijing’s Zizhuyuan and Taoranting Parks were analyzed through microclimate measurements, 716 questionnaires, and scoring evaluations, supplemented by PET field data and ENVI-met simulations. A scoring system was developed based on tree density, plant traits (height, crown spread), and spatial features (canopy closure, structure, enclosure, and evergreen coverage). Key findings: (1) Sparse forests showed the best overall thermal comfort. Square building spaces were objectively comfortable but subjectively poor, while waterfront spaces showed the opposite. Dense forests performed worst in both aspects. (2) Wind speed and humidity were key drivers of both subjective and objective thermal comfort, and differences in plant configurations and landscape space types shaped how these factors were perceived. (3) Differentiated optimal scoring thresholds exist across the four landscape space types: waterfront (74 points), square building (52 points), sparse forest (61 points), and dense forest (88 points). (4) The landscape space design prioritizes sparse forest spaces, with moderate retention of waterfront and square areas and a reduction in dense forest zones. Optimization should proceed by first controlling enclosure and shading, then adjusting canopy closure and evergreen ratio, and finally refining tree traits to improve winter thermal comfort for the elderly. This study provides quantitative evidence and optimization strategies for improving both subjective and objective thermal comfort under diverse plant configurations. Full article

The rapid growth of electric vehicles has intensified the spatial mismatch between the layout of charging infrastructure and user demand, resulting in a structural contradiction in which “local oversupply” and “local shortages” coexist. To systematically diagnose and optimize this issue, this study develops an innovative analytical framework for a “residential area–charging infrastructure” collaborative service network and conducts an empirical analysis using Hongshan District in Wuhan as a case study. The framework integrates actual facility utilization data, complex network analysis, and spatial clustering methods. The findings reveal that the collaborative service network in the study area is overall sparse, exhibiting a distinct “core–periphery” structure, with noticeable patterns of resource concentration and isolation. Residential areas can be categorized into three types based on their supply–demand characteristics: efficient-collaborative, transitional-mixed, and low-demand peripheral areas. The predominance of the transitional-mixed type indicates that most areas are currently in an unstable state of supply–demand adjustment. A key systemic mechanism identified in this study is the significant “collaborative reinforcement effect” between facility utilization rates and network centrality. Building on these insights, we propose a hierarchical optimization strategy consisting of “overall network optimization—local cluster coordination—individual facility enhancement.” This ultimately forms a comprehensive decision-support framework for “assessment—diagnosis—optimization,” providing scientific evidence and new solutions for the precise planning and efficient operation of urban charging infrastructure. Full article

Urban waterfront spaces are key venues for residents’ physical activity, and their spatial environment significantly impacts usage efficiency. Existing studies predominantly employ linear models and focus on single waterfront types, making it difficult to reveal differences across various types and the nonlinear mechanisms of influencing factors. To address this, this study investigates three types of waterfront spaces in Shenzhen—riverfront, lakeshore, and seafront spaces—integrating multi-source data and machine learning techniques to systematically analyze the differential impacts of the same elements on physical activity. The results indicate: (1) In terms of transportation accessibility, public transport is the most important factor for riverfront and lakeshore spaces, while road network accessibility is most critical for seafront spaces. (2) Regarding natural landscapes, the dominant factors are normalized difference vegetation index (NDVI) for riverfront spaces, green view index for lakeshore spaces, and distance to the shoreline for seafront spaces. (3) For facility services, the core factors are building density (riverfront), number of sports facilities (lakeshore), and number of leisure facilities (seafront). (4) The study further reveals nonlinear relationships and threshold effects of multiple elements. For instance, a turning point in physical activity intensity occurs when the distance to a subway station reaches 2–2.5 km. The green view index shows a threshold of 30% in the overall model, while dual-threshold phenomena are observed in the lakeshore and seafront models. (5) Synergistic effects between elements vary by waterfront type: in riverfront and seafront spaces, activity is more vibrant when areas are close to subway stations and have a low sky view index, whereas the opposite pattern is observed in lakeshore spaces. A combination of a high green view index and greater distance to the shoreline promotes activity in lakeshore spaces, while a high green view index combined with proximity to the shoreline has the most significant promotional effect in riverfront and seafront spaces. This study provides a scientific basis for health-oriented, precise planning and design of urban waterfront spaces. Full article

In the context of new-type urbanization and high-quality development, this study aims to construct a multi-objective synergistic land-use mechanism to tackle the “growth-equity-ecology” trilemma in the Chengdu–Chongqing Urban Agglomeration (CCUA). By building an economic–social–ecological benefit evaluation index system and applying TOPSIS with entropy weighting, the coupling coordination degree (CCD) model, and the spatial Durbin model (SDM), we systematically explore the spatiotemporal patterns of land-use benefit synergies and their driving mechanisms. The results reveal the following: (1) From 2015 to 2023, CCUA’s land-use CCD generally improved but showed marked core–periphery polarization. Chongqing’s economic agglomeration worsened regional gaps, while Sichuan’s intra-regional policies boosted internal balance; cross-jurisdictional collaboration eased border disparities but failed to stop overall polarization. (2) Spatial clustering identified hotspots in Chongqing’s main urban and suburban areas and cold spots in eastern Sichuan, reflecting the coexistence of factor agglomeration and cross-border policy synergy. (3) Road network expansion directly hindered CCD, and neighboring ecological protection triggered resource-competition spillovers, emphasizing the key role of cross-regional governance in balancing the “ecology-development” trade-off. This study puts forward spatially differentiated strategies and cross-jurisdictional coordination mechanisms to optimize land-use structures and advance sustainable development in urban agglomerations. Full article