Search Results (2,118)

Preservation and revitalization of historic districts are critical for quality urban development and renewal. Accurately assessing what drives district vitality is essential for sustainable historic area development. Current research often uses cross-sectional data and single models, limiting understanding. This study uses Xigong District, Luoyang, and integrates multi-source data—street view imagery, points of interest, road networks, and nighttime lighting—from 2014 to 2021. MGWR and XGBoost models create a dynamic framework for analyzing how the built environment affects street vitality over time. Results: (1) Spatial effects: Physically, green exposure, functional mix, and road network access are highly spatially sensitive. Morphological indicators—commercial frontage, street continuity, complexity, and building texture—show reduced local variation over time. Perceptually, the influence of abstract color narrows each year, and subjective preference broadens. (2) Nonlinear effects: Green exposure and openness dominate but show negative inhibition and diminishing returns. Morphological, functional, and road network indicators have moderate explanatory power with clear thresholds. Perceptual importance shifts from abstract color to architectural texture, which now rises while color influence steadies. Renewal should go beyond basic greening and surface color. Instead, focus on refined, threshold-based control of form and function, and preserve authentic historic texture. This approach enables scientific, sustainable vitality. Full article

The basic renovation of old urban communities is an important livelihood project for urban renewal, but there are many problems in the decision-making of renovation schemes, such as strong dependence on experience, lack of quantitative basis for multi-objective trade-off, and difficulty in describing residents’ risk attitude. Combining Case-Based Reasoning (CBR) and utility theory, this paper constructs a set of intelligent decision support models driven by data and knowledge. First of all, through literature analysis and expert investigation, a decision-making index system is established, which includes four dimensions and 16 quantitative indicators: policy and financial support, residential conditions and needs, residents’ consensus and social coordination, and implementation management and long-term maintenance. Secondly, the framework representation method is used to describe the reconstruction case, a hybrid retrieval strategy combining inductive retrieval and nearest-neighbor retrieval is designed, and the subjective and objective data combination weights are calculated by using AHP and the entropy method. On this basis, a loss utility function and risk aversion coefficient based on accident and public opinion data (a = 0.02) are introduced to modify the similarity calculation results to describe the risk avoidance behavior of decision-makers. Through 40 real renovation projects, a case base is built, and two types of target cases, “typical inclusive” (F5) and “key renovation” (F35), are selected for empirical verification. The results show that the model can effectively retrieve similar cases, and the similarity ranking changes in line with risk aversion expectations after utility correction. Taking F5 as an example, by reusing and revising the reconstruction scheme of a similar case, targeted suggestions are generated, which give consideration to safety, economy and operability. This model provides a new quantifiable and reusable method for scientific decision-making in basic renovation of old residential areas. Full article

With the rapid electrification of urban transportation and increasing penetration of renewable energy, maintaining frequency stability in smart-city multi-microgrids (MMG) systems increasingly depends on coordinated vehicle-to-grid (V2G) flexibility. However, existing load frequency control strategies typically treat electric vehicles (EVs) as homogeneous resources and overlook the impacts of charging-infrastructure diversity, user mobility constraints, and extreme weather conditions on regulation availability. To address these challenges, this study proposes a weather-adaptive intelligent load frequency control strategy for smart-city MMG considering heterogeneous charging stations and energy requirements of EV users. Fast and slow charging infrastructures are modeled separately to reflect their distinct regulation characteristics, while time-varying charging and discharging margins are derived from travel demand, parking duration, and state-of-charge preferences and further adjusted under extreme weather scenarios. Based on these dynamic constraints, an enhanced multi-agent soft actor–critic (MA-SAC) controller coordinates micro gas turbines and charging stations for distributed frequency regulation. Simulations demonstrate MA-SAC outperforms PID, Fuzzy, and MA-DDPG methods, achieving a 98.51% frequency excellent rate normally and 91.47% during extreme weather. It reduces maximum deviations by up to 80% versus PID, while preserving user travel requirements. The proposed framework provides a practical pathway for integrating electrified mobility into resilient smart-city MMG frequency regulation. Full article

The Gulf Cooperation Council (GCC) countries consistently rank among the highest per capita CO₂ emitters globally, yet rigorous empirical analysis of the structural drivers of these emissions in the post-Paris Agreement era remains scarce. This study investigates the determinants of CO₂ emissions per capita across six GCC economies—Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates—over the period 2015–2022, using pooled ordinary least squares (OLSs) and country fixed effects (FEs) panel regression models with country-clustered standard errors. The focal explanatory variable is energy use per capita, complemented by GDP per capita, trade openness, urbanization, foreign direct investment (FDI), and industry value added as controls. A quadratic income term explicitly tests the environmental Kuznets curve (EKC) hypothesis. Results consistently show that energy use is the dominant driver of emissions. The EKC hypothesis is supported in the FE framework. The implied turning point of approximately USD 85,500 per capita (constant 2015 USD) is already exceeded by Qatar (panel mean: USD 114,835) and approached by the UAE (USD 71,434), while Bahrain (USD 55,681), Kuwait (USD 51,531), Saudi Arabia (USD 61,232), and Oman (USD 38,591) remain on the EKC’s rising slope, consistent with their continued emissions’ growth trajectories. Urbanization exerts a significant positive within-country effect on emissions. Trade openness reduces emissions in cross-sectional specifications, while FDI is systematically insignificant. These findings support energy efficiency reforms, renewable energy expansion, and low-carbon urban planning as the most effective policy levers for GCC decarbonization. Full article

Perceived street vitality directly reflects residents’ assessments of the attractiveness of the street environment; it is not only an important focus of urban vitality research but also closely related to human-centred sustainable urban development. However, limited data availability and the complexity of urban environments have constrained fine-grained spatial analysis at the city scale. To address this issue, this study quantified perceived street vitality by collecting street-view imagery, extracting streetscape features, and integrating these data with questionnaire survey results. After comparing multiple models, a geographically weighted machine learning model was employed to identify key visual predictors, model-estimated marginal associations, interaction patterns, and spatial heterogeneity related to perceived street vitality. The results show that areas with high perceived street vitality are mainly located along street segments with abundant greenery and open spaces, whereas low-value areas are concentrated in densely built and enclosed environments. Among the various streetscape elements, buildings, vegetation, and sky are the key visual elements most strongly associated with perceived street vitality. A model incorporating these elements accounted for 67.2% of the variance in perceived street vitality. Notably, the strength of these associations varied significantly across different areas. This study provides empirical evidence and evidence-based support for sustainable urban renewal, the optimisation of street-space layouts in high-density urban areas, and the improvement in street environmental quality. Full article

This study examines the long- and short-run determinants of green employment in Saudi Arabia over the period 1990–2024 using an Autoregressive Distributed Lag (ARDL) bounds testing framework within an error-correction model. Six macroeconomic and structural variables are analyzed: renewable energy capacity, GDP growth, domestic credit, urbanization, foreign direct investment, and the Vision 2030 policy regime shift. Supplementary analyses test the Environmental Kuznets Curve (EKC) hypothesis and map causal relationships using pairwise Granger causality tests. The bounds test indicates long-run cointegration among the variables (F = 8.45, exceeding the 5% I(1) critical bound of 3.61). The model explains 89% of the variation in log green employment (R² = 0.89) and passes standard diagnostic tests for serial correlation, heteroskedasticity, normality, and parameter stability. Three correlates of long-run green employment are identified. The post-2016 dummy used to capture the Vision 2030 regime shift is associated with the largest coefficient in the long-run equation (θ = 1.75, p = 0.008), although this estimate should be interpreted with caution because the dummy absorbs all post-2016 changes, including policy effects, the rapid expansion of renewable capacity, broader institutional reforms, and possibly changes in measurement practices. Renewable energy capacity is the primary continuously measurable driver (θ = 0.145, p = 0.018), with Toda–Yamamoto modified Wald tests indicating a bidirectional predictive relationship between investment and employment. Urbanization exerts a significant positive long-run effect (θ = 0.098, p = 0.001). The error correction term (δ = −0.520, p < 0.001) implies equilibrium reversion with a half-life of approximately one year. The EKC hypothesis is not supported in the Saudi context, suggesting that active decarbonization policy—rather than income-driven structural change alone—is needed for environmental improvement. The findings carry implications for Vision 2030 implementation and for other resource-dependent economies undertaking structural green transitions. Full article

Streets are major public spaces in high-density cities, and their visual environments are closely related to shaping emotional experience and wellbeing. However, existing studies often examine macro-scale urban form and pedestrian-level streetscape perception separately, while paying limited attention to nonlinear relationships and spatial heterogeneity. This limits the evidence available for fine-grained urban renewal in high-density contexts. Focusing on the area within Shanghai’s Outer Ring, this study develops a large-scale street-view dataset of 512,764 Baidu Street View images. Six perceptual dimensions—safety, lively, beautiful, wealthy, boring, and depressing—are estimated using a perception model trained on Place Pulse 2.0 and integrated into a composite Psychological and Emotional Index (PEI). XGBoost–SHAP is used to examine nonlinear relationships and threshold effects between perceptions and environmental indicators, while MGWR is employed to capture spatial nonstationarity and scale-dependent effects. The results show significant spatial heterogeneity and positive spatial autocorrelation across the six perceptual dimensions and the PEI. Compared with traditional morphological indicators, visual features showed stronger explanatory power and clearer threshold effects. Population density acts as a globally stable negative factor, whereas visual entropy and mixture show strong local sensitivity. These findings provide a data-driven basis for identifying context-specific priorities in urban renewal and spatial governance in high-density cities. Full article

Urban heating systems continue to rely heavily on fossil fuels, driving significant CO₂ emissions and underscoring the need for scalable renewable alternatives. This study evaluates a solar-assisted aquifer thermal energy storage (ATES) system for sustainable urban heating, operating within a relatively deep aquifer. A numerical model of the Mannville aquifer is developed to simulate charge–discharge cycles in a relatively deep open-loop ATES system, examining subsurface temperature evolution, storage efficiency, and long-term thermal stability under Canadian climatic conditions. Modeling results indicate that such aquifers act as an effective thermal buffer for solar energy storage operations, smoothing seasonal temperature fluctuations and stabilizing heat production. Surplus solar thermal energy injected during low-demand periods significantly reduces long-term temperature decline and preserves thermal availability for winter extraction. Balancing contributions from solar and aquifer storage maintains system efficiency during peak demand while improving overall thermal management. The integrated approach enhances renewable energy utilization, reduces reliance on conventional heating systems, and strengthens the resilience of urban energy networks. Our findings demonstrate that coupling solar thermal input with geothermal heat storage in relatively deep aquifers offers a practical pathway for advancing sustainable urban heating in cold-climate regions. The modeling framework provides a foundation for optimizing seasonal storage strategies and guiding the design of hybrid solar–geothermal systems for large-scale urban applications. Full article

The urban housing sector plays a significant role in global energy consumption and carbon emissions, making the sustainable transformation of domestic buildings essential to achieving climate goals. Urban housing is also linked to the energy transition, social equity, public health, and environmental resilience. The UK’s Warm Homes Plan (WHP) is seen as a key policy initiative that aims to improve energy efficiency and living conditions, and to promote the transition to a low-carbon future. This study provides an integrated review of retrofit assessment, policy mechanisms, and socio-environmental factors in the context of urban housing decarbonization. This study adopts a structured critical review approach to analyze retrofit strategies, low-carbon heating systems, renewable energy integration, and smart control technologies. The study highlights that retrofit assessment is not limited to technical performance but also includes social acceptability, affordability, and urban infrastructure compatibility. Furthermore, case study comparisons show that decarbonization outcomes are improved when technical measures are integrated with effective governance, stakeholder engagement, and local policy support. This study presents an integrated conceptual framework that links technical retrofit measures, policy coordination, and socio-environmental indicators. The results show that isolated technical solutions are insufficient for decarbonizing urban housing. Rather, a multi-dimensional planning approach is necessary to enable a sustainable, resilient, and socially inclusive housing transition. Full article

As a form of living heritage, Historic Urban Landscapes (HULs) have long been limited by the static perspectives and reductionist tendencies of conventional conservation and research approaches. Although the geological and archaeological concept of “stratification” offers a methodological basis for understanding the diachronic evolution of heritage, its unidimensional temporal lens fails to capture the inherent complexity and systemic nature of historic urban landscapes. To address this gap, this study proposes a “multidimensional stratification” theoretical framework through theoretical critique and paradigm reconstruction. The framework introduces innovations at the ontological, epistemological, and methodological levels, positing that the evolution of historic urban landscapes emerges from the nonlinear interaction and dynamic interweaving of four core dimensions: time, space, society, and value. It further systematizes five intrinsic attributes of such landscapes: authenticity, integrity, continuity, adaptability, and dynamism. Building on this foundation, the paper constructs a systematic analytical pathway—elements–processes–patterns–modes–drivers–characteristics—that enables dynamic analysis from micro-level identification to macro-level generalization, offering a scalable tool for HUL conservation and regeneration. To demonstrate the framework’s applicability, the historic urban area of Shenyang—a nationally designated historical and cultural city—is selected as a case study. Its urban landscape comprises four core districts: the Shengjing City District, the South Manchuria Railway Concession District, the Commercial Port District, and the Tiexi Industrial District, representing historical strata from the Qing dynasty capital, modern colonial planning, commercial opening, to industrial heritage. Using the multidimensional stratification approach, this study elucidates the spatial complexity, temporal nonlinearity, social dynamism, and value pluralism embedded in Shenyang’s historic urban area. Corresponding conservation strategies grounded in holism, dynamism, and differentiation are proposed. The research not only advances the theoretical understanding of HUL but also provides a novel paradigm—integrating holistic, dynamic, and operational perspectives—for the conservation, renewal, and regenerative practice of historic urban landscapes worldwide. Full article

Global urbanization is shifting from incremental expansion to stock optimization, and old residential communities have become important spatial units for low-carbon transition. However, in existing built environments, traditional process-based inventory methods face practical constraints, including missing original drawings, complex site conditions, and severe vegetation obstruction. As a result, systematic accounting of buildings, landscapes, and natural carbon sinks remains difficult. This study integrates life cycle assessment (LCA), BIM reverse modeling, 3D point clouds, DesignBuilder simulation, inventory-based accounting, and i-Tree Eco to construct a life cycle carbon emission accounting framework for old residential communities. The framework links current-condition data reconstruction, quantity take-off, operational energy simulation, landscape inventory accounting, and vegetation carbon sequestration assessment. It is applied to Nanyuan Xincun in Hefei to quantify the community-scale carbon source–sink structure. The results show that Nanyuan Xincun presents a clear operation-led emission pattern, with the operation and maintenance phase accounting for 82.52% of total positive emissions. Within architectural engineering, operation and maintenance accounts for 82.91%, while material production accounts for 13.28%. Landscape engineering shows a more mixed structure, with operation and maintenance accounting for 52.95% and material production accounting for 36.49%. Vegetation carbon sequestration analysis shows that mature trees and shrubs are the main ecological carbon assets. Annual sequestration reaches 16.95 t-CO₂e/a, and trees and shrubs contribute 92.85% of total vegetation carbon storage. Under current vegetation conditions, annual sequestration is equivalent to 32.99% of annual landscape operation emissions, indicating considerable ecological compensation potential. Based on these findings, this study proposes four optimization pathways: operational energy reduction, low-carbon material substitution, construction and demolition waste recycling, and mature tree protection. These pathways provide data support for refined carbon management and low-carbon renewal in existing communities. Full article

The Copenhagen 10-step method is a set of policies that originated in the 1950s to reduce vehicle traffic in Copenhagen, which was heavily impacted by traffic. These policies are incorporated into a different dynamic on a global scale every day and are adopted while maintaining relevance. These policies, advocated in the context of climate change and carbon emission targets, as well as livability and health-focused urbanization, justice, and accessibility in transportation, are criticized for potentially negatively affecting low-income groups and commercializing urban transformation. Furthermore, they require adaptation because their applicability is seen as limited in terms of localization. In this context, the adaptability of the method to different social and spatial contexts has become a critical research topic, particularly in local studies, where application is more important and the order of implementation becomes of great importance. Within the scope of this study, a Copenhagen 10-step prioritization study was conducted specifically for the Küçükçekmece Kanarya Neighborhood, where low-to-middle socioeconomic groups live, and which has been declared a risky area in terms of building stock. Accordingly, a two-phase study was conducted. In the first phase, transportation and planning experts were asked to prioritize the 10 steps, and the timing of each implementation was determined based on the resulting ranking. In the second phase, accessibility analyses for the region were conducted using GIS (Geographical Information Systems)-based spatial data, such as accessibility, slope, and the distribution of urban facilities. Subsequently, these two phases were combined to create a simple prioritization framework for the areas of greatest concern in Kanarya, as well as for urban renewal, transportation, and government investment plans. According to the SWARA results, increasing bicycle use (C10) was the most important criterion at 17.2%, followed by making the bicycle the primary mode of transportation (C9) at 13.8% and adapting the city to seasonal changes (C8) at 11.5%. This study, which is significant for its focus on a specific region at the local implementation level, presents a straightforward model—based on concrete findings—for prioritizing sustainable transportation and urbanization policies in socioeconomically vulnerable areas. In doing so, it contributes to aligning theoretical approaches with practical field applications. Full article

As global efforts to decarbonize the transportation sector intensify, integrating renewable energy sources into electric vehicle (EV) infrastructure has become a critical challenge, particularly under strong temporal mismatches between generation and demand. This study evaluates the potential of urban rooftop photovoltaic (PV) systems in Israel to support full electrification of the private vehicle fleet using a planning-oriented modeling framework that links energy supply, transport demand, and seasonal variability. Current annual fleet demand is estimated at 14 TWh, based on both internal combustion vehicle replacement and EV-specific consumption. A three-stage modeling framework is applied. First, national vehicle data are used to estimate total electricity demand. Second, rooftop PV generation potential is calculated using a monthly irradiance model, rooftop availability data, and system-level efficiency factors. Under these assumptions, residential rooftop PV could generate up to 81 TWh per year, corresponding to approximately 44 km² of usable rooftop area. Third, temporal matching between supply and demand is evaluated, with explicit focus on intra-annual variability rather than only annual energy balance. Winter irradiance declines to approximately 45% of summer levels, while maintaining continuous charging requires approximately 38 GWh of energy storage. These results show that system feasibility is constrained by winter minimum generation rather than annual energy balance. The findings highlight that large-scale rooftop PV-based electrification is primarily limited by a temporal mismatch between generation and demand. This shifts the evaluation of PV-EV integration from a static annual energy perspective to a temporal system-design problem. This underscores the importance of integrating storage, grid flexibility, and system-level planning when evaluating the role of distributed PV in supporting electrified transport. Full article

Food markets represent a public good essential for urban supply and as intergenerational spaces supporting the small-scale economy, yet they face growing challenges in adapting to sustainability regulations and circular economy requirements. This study examines the current state of sustainability in Madrid’s municipal markets through interviews and questionnaires administered to market managers, analyzing building characteristics, renewable energy systems, passive savings strategies, and energy costs across different market typologies. Results reveal that in December 2025, only 9% of markets had solar thermal installations, while merely 11% were planning photovoltaic solar panel projects—figures insufficient to meet current EU energy efficiency mandates. The findings demonstrate a significant gap between existing infrastructure and the requirements of the Directive (EU) 2023/1791, which supersedes previous directives. These results indicate an urgent need for accelerated implementation of renewable energy systems in market buildings to achieve sustainability targets. The study contributes baseline data for developing intervention strategies that can reduce energy consumption and align Madrid’s market network with European decarbonization goals for 2030 and 2050. Full article

Historic districts are important built environments in which architectural form and cultural meaning shape residents’ place-based identity and engagement with conservation under urban renewal. However, empirical evidence on which features of the historic environment most strongly support local identity and conservation participation in migrant-intensive, fast-growing cities remains limited. This study investigates the relationships among architectural heritage, religious elements, cultural activities, local identity, sense of belonging, and conservation participation in five historic districts in Shenzhen, China. Using a residents’ questionnaire survey, we applied hierarchical multiple regression and mediation analysis to examine these relationships. The results indicate that architectural heritage is the strongest predictor of local identity, whereas religious atmosphere and cultural activities show comparatively weak effects. Local identity is positively associated with conservation participation, with only limited mediation through sense of belonging. The findings indicate that in migrant-intensive urban settings, architectural distinctiveness plays a stronger role in shaping local identity than religious or other cultural practices. Overall, the study argues that architectural heritage should be seen not only as a physical fabric to be preserved, but also as a resource that can strengthen local identity, participation, and socially sustainable urban renewal. Full article