Search Results (3,828)

The contemporary approach to assessing the housing conditions of households requires taking into account not only the physical characteristics of dwellings but also the quality of their surroundings. From a sustainability perspective, the quality of the external residential environment constitutes a key dimension of sustainable living conditions, closely linked to environmental well-being, spatial equity, and the objectives of sustainable urban and territorial development in the European Union (EU). Despite the growing awareness of the importance of the living environment for residents’ well-being, this issue remains insufficiently represented in analyses addressing the territorial variations in household housing conditions in the EU countries. The scientific literature reveals a lack of comprehensive comparative studies that would link subjective assessments of external residential environmental quality with the level of urbanisation, enabling a more complete evaluation of the living environment and its spatial variability. The aim of the study was therefore to assess the perceived external residential environmental quality of households in EU countries, taking into account the level of urbanisation—differences between urban, town, and rural areas. The study aimed to test the hypothesis that “The external residential environmental quality in EU countries significantly varies depending on the level of urbanisation and regional affiliation, with the highest quality observed in rural areas, particularly in Western European countries.” The study was conducted based on data from the Eurostat database, which were processed using descriptive statistics, inferential statistics, and taxonomic methods. The results of the study confirmed that the external residential environmental quality of households in EU countries significantly differs depending on the level of urbanisation and regional affiliation. The highest level of residential environment quality for households is observed in rural areas of Northern and Eastern European countries. The greatest challenges occur in large cities, particularly in Western Europe, indicating the need to intensify efforts to improve the quality of the living environment in these areas. Full article

Reducing energy demand and carbon emissions in residential buildings requires more than technological upgrades; it demands a nuanced understanding of occupant behaviour. Residential energy use is shaped by both physical design and human actions, yet behavioural factors remain underexplored, contributing to the energy performance gap. This study addresses this issue by developing and validating a behavioural framework grounded in the Theory of Planned Behaviour (TPB) to examine how attitudes, social norms, perceived control, and environmental awareness influence energy-related decisions. Data were collected through an online survey of 310 households in metropolitan Sydney and analysed using Stata v17 software employing principal component analysis and regression modelling. Results reveal that environmental awareness is the most significant predictor of pro-environmental intention, which strongly correlates with actual behavioural outcomes. While attitudes and perceived control were generally positive, subjective norms and awareness remained moderate, limiting behavioural change. The proposed framework demonstrates strong validity and reliability, offering a practical tool for policymakers, designers, and educators to integrate behavioural insights into sustainable building strategies. By prioritising awareness campaigns and normative interventions, stakeholders can complement technical retrofits with behavioural measures, accelerating progress towards low-carbon housing and benefiting both households and the broader community. Full article

Designing and communicating physical activity guidelines takes considerable resources; thus, understanding the awareness and adoption of such guidelines by different population groups is important. A national cross-sectional survey (N = 972; aged 19+ years living in Wales) was delivered as part of a population panel using a multi-method approach (online, telephone and face-to-face). The survey measured the awareness and adoption of the 2019 UK physical activity guidelines and recommendations and socio-demographics, including age, sex, residential deprivation and disability status. Around a fifth (21.7%) of participants had heard of the physical activity guidelines. Almost a third (30.7%) reported knowing the moderate physical activity recommendation, with 13.3% knowing the vigorous physical activity recommendation and 13.4% knowing the muscle-strengthening recommendation. There were no significant socio-demographic differences in knowing the moderate recommendation (p > 0.05); however, females were less likely than males to report knowing the vigorous recommendation (p = 0.009), and participants with a disability were less likely than those without a disability to report knowing the muscle-strengthening recommendation (p = 0.026). Having heard of the physical activity guidelines increased the likelihood of knowing each of the three recommendations (all p < 0.001). Additionally, for both moderate-to-vigorous physical activity and muscle-strengthening recommendations, a positive relationship was found between knowing the recommendation and reporting meeting the recommendation (p = 0.008 and p = 0.002, respectively). The awareness of both the physical activity guidelines and their recommendations was low. The development of communication strategies to aid knowledge mobilisation should be considered. Socio-demographic differences in awareness should be considered when designing interventions in line with proportionate universalism principles. Full article

With the rapid growth of residential electric vehicles, synchronized charging during peak periods can induce severe load ramping and exceed distribution network capacity limits. To mitigate these issues, governments have promoted a unified build-and-operate community model that enables centralized coordination of community charging and ensures real-time responsiveness to grid dispatch signals. Targeting this emerging operational paradigm, a dual-dimensional compensation mechanism for real-time electric vehicle (EV) demand response is proposed. The mechanism integrates two types of compensation: power regulation compensation, which rewards users for providing controllable power flexibility, and state-of-charge (SoC) loss compensation, which offsets energy deficits resulting from demand response actions. This dual-layer design enhances user willingness and long-term engagement in community-level coordination. Based on the proposed mechanism, a bi-level optimization framework is developed to realize efficient real-time regulation: the upper level maximizes the active response capacity under budget constraints, while the lower level minimizes the aggregator’s total compensation cost subject to user response behavior. Simulation results demonstrate that, compared with conventional fair-share curtailment and single-compensation approaches, the proposed mechanism effectively increases active user participation and reduces incentive expenditures. The study highlights the mechanism’s potential for practical deployment in unified build-and-operate communities and discusses limitations and future research directions. Full article

Accurate, high-frequency carbon emission forecasting is crucial for urban climate mitigation and achieving sustainable development goals. However, generalized models often result in lower prediction accuracy by overlooking the unique “sector specificity” of urban emission systems, namely, the different temporal patterns driven by distinct physical and economic factors across sectors. This study establishes a decision-support framework to select optimal forecasting models for distinct sectors. Using daily multi-sector carbon emission and meteorological data from Hangzhou, we evaluated 12 models across statistical, machine learning, and deep learning classes. Our three-stage design identified the best model for each sector, quantified the contribution of meteorological drivers, and assessed multi-step forecasting stability. The results indicated the lack of universality in generalized models, as no single model performed best across all sectors. A hybrid CNN-LSTM model outperformed other candidates for ground transport (R² = 0.635), while LSTM showed better performance for industry (R² = 0.866) and residential (R² = 0.978) sectors. Integrating meteorological factors only improved accuracy in weather-sensitive sectors (e.g., residential) and acted as noise in others (e.g., aviation). We conclude that a sector-specific strategy is more robust than a one-size-fits-all approach for carbon emission forecasting. By resolving the specific driving mechanisms of each sector this decision-support framework provides the granular data foundation necessary for precise urban energy dispatch and targeted emission reduction policies. Full article

Identifying area functions around urban rail transit (URT) stations is crucial for optimizing urban planning and infrastructure allocation. Traditional methods relying on static land-use data fail to capture dynamic human–environment interactions, while emerging mobility datasets suffer from spatial granularity limitations. This study bridges this gap by integrating spatiotemporal patterns of dockless bike sharing (DBS) with Point of Interest (POI) configurations to characterize station functions. Taking Beijing as a case study, we develop a cluster analysis framework that synthesizes DBS density fluctuations, parking distribution shifts between day/night periods, and POI features. Cluster results reveal functionally distinct station groups with statistically significant differences in both DBS usage patterns and POI distributions. Critically, high-density urban cores exhibit concentrated bicycle usage aligned with mixed POI agglomerations, while suburban zones demonstrate commuter-oriented fluctuations with evening residential surges. This alignment between DBS-derived activity signatures and POI-based land-use features provides actionable insights: planners can optimize bicycle parking in residential clusters, calibrate last-mile connections in employment cores, and adapt infrastructure to localized functional transitions—ultimately enhancing URT-integrated sustainable development. Full article

The large-scale development of mineral resources has led to a sharp increase in the amount of tailings and waste rock accumulated in tailings ponds and waste disposal sites, forming a large number of high-risk tailings dams and high-pile waste disposal sites. In recent years, frequent incidents of tailings dam breaches and landslides in high-pile dumping sites have posed a serious threat to the lives and property of downstream residential areas. Therefore, studying the collaborative storage technology of waste rock and tailings is of great significance. By conducting physical model experiments on tailings dams of a similar scale and using the SEEP/W module in GeoStudio 2022.1 software for numerical simulation, the influence of the built-in waste-rock inclusions on the permeability characteristics of the dam body and the depth of the saturation line is analyzed. The results showed that the seepage flow increased with the decrease in fine particle content in the waste-rock inclusions, with the highest seepage flow in the C-grade waste-rock inclusions and the most significant decrease in the saturation line, and the seepage volume decreased with the increase in the spacing between waste-rock inclusions. The depth of the saturation line is negatively correlated with the distance between the centers of the waste-rock inclusions; that is, the smaller the distance (200 mm), the greater the depth of the saturation line. The research results can provide a reference for ensuring the safety and stability analysis of tailings dams. Full article

Green infrastructure and nature-based solutions (NBSs) are, especially in urban areas, one of the key elements in building a friendly living environment that contributes to healthy longevity. This paper presents a novel method for assessing the accessibility of recreational urban green space (RUGS) at the level of individual residential buildings. We designed and piloted a new total accessible recreational urban green space area (TARUGS) index, based on real pedestrian network distances, considering spatial accessibility weighted by the total area of green space available within an approximate 15-min walk. Calculations were carried out individually for each residential building and each individual RUGS, using GIS technologies, including network analysis. The developed methodology allows for the detection of local inequalities in access to all city RUGSs. It enables the inclusion of additional socioeconomic variables in an in-depth spatial equity analysis. The RUGS accessibility ranking of buildings provides a practical tool to support urban intervention planning, as well as the design of solutions that respond to the real needs of residents and environmental challenges. Availability analyses were performed for 108,618 buildings and 146 RUGS. Areas with the highest and clearly insufficient access to RUGS in Warsaw were identified. Over 40,400 buildings were classified as having no access to RUGS (class 0), which accounts for 37% of all residential buildings, while 21,700 buildings were classified as having the best access (class 4), which accounts for 20% of all residential buildings. The districts of Wilanów and Włochy have the worst accessibility, while Wawer and Mokotów have the best. The proposed building-level methodology quantitatively reveals spatial inequalities in access to RUGS, enabling data-driven, equitable planning decisions while highlighting the need to integrate broader accessibility modes, subjective user experiences, and data improvements for a comprehensive assessment of spatial justice. The framework demonstrates how advanced geospatial data analysis, integrating GIS technologies, open data, and network-based innovative solutions, could enhance urban policy-making, improve the design of equitable public spaces, and support resilient land management strategies. Full article

Urban Heat Islands (UHIs) are urbanized areas that experience significantly higher temperatures than their surroundings, contributing to thermal discomfort, increased air pollution, heightened public health risks, and greater energy demand. In Bhutan, where urban expansion is concentrated within narrow valley systems, the formation and intensification of UHIs present emerging challenges for climate-resilient urban development. Thimphu, in particular, is experiencing rapid urban growth and densification, making it highly susceptible to UHI effects. Therefore, the aim of this study was to evaluate and simulate UHI conditions for Thimphu Thromde. We carried out the simulation using a GIS, multi-temporal Landsat imagery, and an Artificial Neural Network model. Land use and land cover classes were mapped through supervised classification in the GIS, and surface temperatures associated with each class were derived from thermal bands of Landsat data. These temperature values were normalized to identify existing UHI patterns. An Artificial Neural Network (ANN) model was then applied to simulate future UHI distribution under expected land use change scenarios. The results indicate that, by 2031, built-up areas in Thimphu Thromde are expected to increase to 72.82%, while vegetation cover is projected to decline to 23.52%. Correspondingly, both UHI and extreme UHI zones are projected to expand, accounting for approximately 14.26% and 6.08% of the total area, respectively. Existing hotspots, particularly dense residential areas, commercial centers, and major institutional or public spaces, are expected to intensify. In addition, new UHI zones are likely to develop along the urban fringe, where expansion is occurring around the current hotspots. These study findings will be useful for Thimphu Thromde authorities in deciding the mitigation measures and pre-emptive strategies required to reduce UHI effects. Full article

This research proposes a hierarchical adaptive approach to urban renewal that seeks to reconcile heritage preservation with contemporary functional demands in historic urban environments. Focusing on cultural and sports public facilities in the northwestern urban–rural interface of Rome, the research identifies critical mismatches between facility typologies, user groups, and mobility patterns, including fragmented connectivity, child-exclusionary environments, and unsafe pedestrian–vehicular interactions. A three-tiered intervention framework is developed, comprising minimal intervention for heritage-preserved structures, semi-intervention for high-use contemporary facilities, and full intervention for generic or underutilized buildings and undeveloped land. Using field surveys, GIS-based spatial analysis, and visualized performance metrics, the study evaluates how vertical functional superposition, independent pedestrian systems, and transitional connectors can enhance spatial legibility, accessibility, and social inclusiveness. The results show that hierarchical adaptive renewal improves pedestrian safety, strengthens functional integration between cultural–sports facilities and adjacent residential areas, and activates underused spaces while maintaining the integrity of Rome’s historic fabric. Beyond the case study, the framework offers a transferable model for other high-density historic cities seeking to balance heritage protection, everyday usability, and sustainable urban development. 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

Public health emergencies (PHEs) test the crisis response capacity of grassroots organizations like China’s Residential Committees (RCs). While existing research attributes this capacity to factors like resource mobilization or state-society relations, its deeper structural foundations in land regimes and spatial configurations remain underexplored, particularly in Global South urbanization contexts. To fill this gap, this study develops a “Grassroots Organizational Capacity” (GOC) analytical framework, which disaggregates capacity into four dimensions: information, implementation, mobilization and cooperation, and coercion. We then employ this framework in a comparative case study of urban (Jiayi) and rural (Hedong) neighbourhoods in Nanhai, China, during the 2022 lockdown. Drawing on semi-structured interviews with ten key stakeholders in 2022, the findings reveal divergent types of governance. In the rural case, collective land ownership and open spaces foster an “Embedded Autonomy” type, enabling a proactive response through dense social networks. In the urban case, state land dependency and spatial fragmentation lead to a “Reactive Co-Governance” type, which relies on top-down state intervention. This study’s contribution is to provide a case-based illustration of how land and space structures are actively associated with grassroots crisis response effectiveness, rather than serving as passive backdrops. Full article

This study examines the traditional villages of the Tujia and Miao ethnic groups in Xiangxi Prefecture, western Hunan, and clarifies their spatial distribution and residential cultures through ArcGIS-based spatial analysis combined with extensive field investigation. On the basis of a systematic comparative framework, it explores differences in village patterns, architectural forms, and folk belief systems between the two groups. The results indicate that (1) in terms of spatial distribution, Miao villages are mainly located to the south of the Wuling Mountains, while Tujia villages are concentrated to the north, with the mountainous ranges of Baojing and Guzhang counties forming a clear transitional belt; (2) regarding village layout, Miao villages are generally clustered with “mountain-backed and water-adjacent”, whereas Tujia villages tend to adopt a more dispersed and defensive pattern than “mountain-anchored and water-distanced”; (3) in dwelling form, both groups share similar basic spatial organization, yet Miao dwellings exhibit greater diversity in construction materials, including timber, stone, and rammed earth; (4) in terms of belief and ritual, distinct folk practices and symbolic systems are embedded in the spatial organization and decorative features of each group’s villages. These findings deepen the understanding of cultural diversity among ethnic minorities in western Hunan and provide a theoretical basis for authenticity-oriented conservation and the sustainable development of traditional villages in ethnic regions. Full article

The study examines the recent transformation of traditional agricultural landscapes in the transition zone between Sierra de las Nieves and the Western Costa del Sol (Andalusia, Spain), one of the European regions where urban development pressure has reached its peak in replacing agricultural land with residential and tourism uses. Through a diachronic analysis of historical orthophotos (1956–2025), statistical sources (Agricultural Census, SIGPAC), and fieldwork, land-use changes and their impact on ecological functionality and territorial resilience are quantified. Results reveal a widespread loss of agricultural land—exceeding 68% overall—particularly severe in Benahavís, where more than 70% of farmland has disappeared, largely converted to urban areas. In contrast, in Istán and Ojén, the predominant trend is the renaturalization of abandoned agricultural land. These dynamics illustrate a coastal–inland territorial model that epitomizes the Mediterranean “territorial consumption” process, in which tourism-driven urbanization fragments traditional agroforestry mosaics. The study concludes that, despite their regression, traditional agricultural landscapes continue to play a key role in water regulation, soil conservation, and wildfire risk mitigation. Their restoration and maintenance are proposed as a replicable strategy for climate change adaptation and for reconciling territorial sustainability with economic development in other Mediterranean regions under intense urban pressure. Full article

Rising residential land prices push up housing prices and worsen credit misallocation. These patterns emerge amid cyclical real estate fluctuations and heavy land-based public finance. Such pressures undermine macroeconomic stability and sustainable land-use. The land price circuit breaker is widely applied with a price cap and state dependence, yet its trigger mechanism and interaction with inflation targeting remain underexplored. This study addresses three core questions. First, how does the circuit breaker’s discrete trigger and rule-switching logic differ from traditional static price ceilings? Second, can the mechanism, via the collateral channel, restrain excessive land price hikes, improve credit allocation, and, thereby, stabilize land price dynamics and long-run macroeconomic performance? Third, how does the circuit breaker interact with inflation targeting, and through which endogenous channels does a strict target dampen housing prices and raise activation probability? This study develops a multi-sector DSGE model with an embedded land price circuit breaker. The price cap is modeled as an occasionally binding constraint. A dynamic price band and trigger indicator capture the policy’s switch between slack and binding states. The framework incorporates interactions among local governments, the central bank, developers, and households. It also links firms and the secondary housing market. Under different inflation-targeting rules, this study uses impulse responses, an event study, and welfare analysis to assess trigger conditions and macroeconomic effects. The findings are threefold. First, a strict inflation target increases the probability of a circuit breaker being triggered. It channels housing-demand shocks toward land prices and creates a “nominal anchor–relative price constraint” linkage. Second, once activated, the circuit breaker narrows the gap between land price and house-price growth. It weakens the procyclicality of collateral values. It also restrains credit expansion by impatient households. These effects redirect credit toward firms, improve corporate financing, reduce the decline in investment, and accelerate output recovery. Third, the circuit breaker limits new land supply and shifts demand toward the secondary housing market. This generates a supply-side effect that releases existing stock and stabilizes prices, thereby weakening the amplification mechanism of housing cycles. This study identifies the endogenous trigger logic and cross-market transmission of the land price circuit breaker under a strict inflation target. It shows that the mechanism is not merely a price-management tool in the land market but a systemic policy variable that links the real estate, finance, and fiscal sectors. By dampening real estate procyclicality, improving credit allocation, and stabilizing macroeconomic fluctuations, the mechanism offers new insights for sustainable land-use policy and macroeconomic stabilization. Full article