Search Results (1,367)

Understanding vegetation resilience gradient effects across hierarchical administrative borders is critical for cross-jurisdictional land management yet remains underexplored. This study integrates an AR(1) model with XGBoost-SHAP analysis to assess resilience and its drivers across provincial, municipal, and county borders in the Beijing–Tianjin–Hebei (BTH) region using NDVI data (2000–2025). The results show that (1) vegetation resilience across hierarchical border belts experienced an initial decline followed by recovery. A notable shift in resilience optimality was observed from city borders in 2005 to provincial borders by 2020. Gradient effects were stronger in northern city borders. The stable-fluctuating type dominated, followed by peak and valley types. (2) Precipitation, tree age, and altitude suppress gradient formation. Conversely, cross-boundary economic disparity, nighttime light differences, and land use composition tend to be associated with amplified gradient effects in a hierarchical manner: cropland and built-up expansion intensify gradients at provincial borders but reduce them at city borders, suggesting a potential role of governance coordination. (3) Based on these findings, a tiered governance framework is suggested—northern high-gradient provincial and city borders are proposed as priority areas for intensive interventions, while county borders (where gradient effects are weakest) may benefit from moderate, low-intensity interventions focused on maintaining land use continuity. At the provincial level, stronger inter-provincial coordination—through cross-boundary ecological compensation and harmonized environmental standards—may help mitigate gradient effects. Collectively, this study provides insights for cross-jurisdictional land governance in the BTH region and other analogous urban agglomerations. Full article

Environmental differences between climate zones may affect arthritis risk. This study aims to explore how winter HVAC use impacts arthritis symptoms in young older adults across four Chinese cities: Chongqing, Beijing, Guangzhou, and Kunming. We surveyed 3579 participants aged 60–74 and used partial least squares-structural equation modeling (PLS-SEM) to explore relationships between HVAC habits, indoor environmental exposure, and arthritis outcomes. Results reveal that distinct climate-specific HVAC usage patterns and their differing relationships with indoor environmental exposures and arthritis symptoms. In Beijing, widespread heating is linked to fewer symptoms (28.6%), while greater reliance on air conditioning or ventilation in humid southern cities corresponds to higher prevalence (33.3–44.9%). The favorable association between HVAC habits and arthritis outcomes was strongest in Beijing, whereas the adverse association between indoor environmental exposures and arthritis was strongest in Chongqing. Mediation analysis suggested that these associations were largely explained through indoor environmental conditions, particularly reduced cold exposure (72.32% in Chongqing) and reduced damp exposure (44.71% in Guangzhou). The strength of this indirect association varied across cities, ranking as Chongqing > Guangzhou > Beijing > Kunming. These findings highlight the importance of climate-responsive HVAC strategies and suggest that improving indoor environmental conditions may support healthier ageing in winter. Full article

The output of photovoltaic power generation exhibits significant randomness, volatility, and intermittency, and its uncertainty will have an impact on the planning assessment, dispatch decision-making, and real-time operation of the power system. To systematically understand the development status of modeling methods for the uncertainty of photovoltaic power generation, this paper conducts a review around the generation of annual scenarios and multi-timescale power prediction of photovoltaic power, and analyzes the correlations between photovoltaic output, influencing factors, and system applications from the perspective of statistical relationships and artificial intelligence. For the annual scale, the focus is on the generation methods of meteorological-driven scenarios for long-term sequences, including probability statistical methods, deep generation methods, constraint relations and engineering application evaluation issues; for the day-ahead scale, the historical power, meteorological variables and numerical weather forecasts are used to explore feature extraction, probability prediction and robust modeling methods; for the intraday scale, the signal decomposition, deep learning, regional collaborative modeling and multi-source perception methods for short-term power fluctuations perception are summarized. On this basis, further analysis is conducted on subsequent research directions such as multi-timescale collaborative modeling, multi-source heterogeneous information fusion, controllable generative modeling, extreme scenario characterization, and engineering closed-loop verification. This paper can serve as a reference for scenario generation, power prediction, and power system operation analysis under the condition of a high proportion of photovoltaic power integration. Full article

Decoupling economic growth from carbon emissions is central to the sustainable development of rapidly urbanizing economies, and urban agglomerations are the pivotal spatial units for delivering this transition under China’s dual-carbon goals, yet systematic cross-agglomeration comparisons that could inform differentiated sustainability policy remain scarce. Using panel data for 107 prefecture-level cities in five agglomerations—the Yangtze River Delta (YRD), Beijing–Tianjin–Hebei (BTH), Pearl River Delta (PRD), Chengdu–Chongqing (CY), and the middle reaches of the Yangtze River (MRYR)—across five benchmark years spanning 2005–2023, we combined a two-way fixed-effects environmental Kuznets curve (EKC) model, the Tapio decoupling model, and cross-sectional quadrant analysis to examine the growth–emission relationship in shape, decoupling dynamics, and spatial structure. All five agglomerations traced an inverted-U trajectory, with turning-point per capita gross domestic product (GDP) rising in the order CY < PRD < BTH < MRYR < YRD. Once fixed effects and structural controls were added, most quadratic terms became insignificant and reversed sign after the secondary-industry share and carbon intensity entered; only the PRD and BTH retained a significant nonlinear form. The net income effect is therefore largely monotonic, with the inverted U carried by industrial upgrading and energy-efficiency gains. Tapio decoupling followed a non-monotonic “improve-then-regress” path, with expansive negative decoupling re-emerging across all agglomerations during 2020–2023. Spatially, high-value clustering persisted in the YRD, weakened in the BTH after 2020, and concentrated on single cores in Chengdu and Wuhan. We accordingly propose sustainability-oriented low-carbon pathways differentiated jointly by agglomeration and quadrant. By showing that decoupling is stage-dependent and reversible rather than an automatic by-product of income growth, our findings indicate that durable progress toward regional sustainability hinges on structural transformation and coordinated governance tailored to each agglomeration’s stage of development. Full article

Fine-scale identification of urban building functions is essential for understanding urban spatial structure, socioeconomic organization, and sustainable urban development. However, large-scale building function mapping remains constrained by reliance on proprietary data, insufficient representation of geographical context, and limited cross-city generalization. To address these challenges, this study proposes a multi-source geographical knowledge fusion framework for fine-scale building function classification using exclusively open-source data. In addition to conventional morphological, POI-based, and spectral features, the framework systematically integrates open-source geographical environmental features to characterize accessibility, infrastructure relationships, ecological surroundings, and environmental conditions at the building level. Beijing is selected as the training area, while Tianjin is used for independent cross-city validation. Ten representative models, including deep learning, ensemble learning, and traditional machine learning methods, are systematically evaluated for classifying six building function types. Results show that the systematic integration of geographical environmental features improves classification performance and interpretability. Deep learning and ensemble models outperform traditional methods, with CNN achieving the highest accuracy of 87.07% in Beijing and 69.83% in Tianjin. Feature contribution analysis further indicates that geographical environmental features play a dominant role in functional discrimination, while POI features provide important socio-semantic information. Overall, this study provides a reproducible open-data framework for urban building function mapping, supporting sustainable urban planning, land-use optimization, infrastructure allocation, and smart city governance. Full article

Amid rapid urbanization, the Beijing–Tianjin–Hebei region has experienced substantial land use restructuring. This spatial evolution has created conflicts between development and conservation, challenging regional sustainability. Using 2005–2020 data, this research incorporates urban land use efficiency (ULUE) and the closeness centrality of spatial correlation network into the Patch-generating Land Use Simulation (PLUS) model to reveal driving mechanisms. It simulates 2035 land use patterns under four scenarios: Business as Usual (BAU), Food Security (FS), Ecological Security (ES), and Efficiency-Driven Optimization (EDO). The findings reveal: (1) Regional land use transitioned from rapid expansion to structural adjustment, with cultivated land acting as the primary source for new construction land. (2) ULUE and the closeness centrality of its spatial correlation network exhibited high feature importance in land use transitions, confirming that land allocation efficiency and network structures significantly reshape regional patterns. (3) Compared to BAU or single baseline constraints, the EDO scenario effectively limits inefficient county expansion and promotes compact core city development, balancing construction land control with cultivated and blue-green space preservation. For large urban agglomerations, a spatial governance pathway integrating efficiency-driven strategies and stock optimization is optimal for coordinating multi-dimensional spatial objectives. Full article

Envelope-parameter optimization for residential buildings is strongly climate-dependent, yet previous studies have mainly focused on single parameters or specific regions, limiting cross-climate comparison of parameter priorities. This study establishes a unified DeST-based residential building model to compare the effects of external wall insulation thickness and external surface solar absorptivity on heating load, cooling load, annual total load, and operational carbon emissions across five representative climate zones in China. Yinchuan, Beijing, Chengdu, Guangzhou, and Kunming were selected as case cities. Single-factor analysis, two-parameter coupling analysis, supplementary sensitivity analysis, and load-to-carbon translation were conducted under consistent building prototypes, operating boundaries, and evaluation indices. The results show that the effects of the two parameters differ markedly across climate zones, reflecting a transition in parameter dominance under different heating–cooling load structures. Over the tested ranges, insulation thickness changes annual total load by up to approximately 10%, whereas solar absorptivity changes it by only 0.17–1.91%. Mechanistically, insulation reduces winter heat loss but may suppress summer heat dissipation, while solar absorptivity directly affects exterior-surface solar heat gains. Further carbon analysis shows that load-optimal configurations do not necessarily correspond to carbon-optimal configurations. These findings provide quantitative support for climate-adaptive and low-carbon envelope design. Full article

Current research on the energy performance of tilted façades is largely confined to specific climatic contexts or individual case studies, with limited systematic investigation of the energy-saving mechanisms across different climate zones in China. Comparative analyses based on Chinese building energy-efficiency standards remain particularly insufficient. This study investigates four representative Chinese cities corresponding to major climate zones—Harbin, Beijing, Shanghai, and Guangzhou—as research cases. A parametric office-building model was developed using the Ladybug–Honeybee simulation platform to evaluate annual cooling and heating energy consumption under different window-to-wall ratios (WWRs = 0.2, 0.4, and 0.6) and south-facing façade tilt angles ranging from 0° to 25°. A simplified thermal calculation model incorporating envelope heat transfer and solar heat gain was further combined with multiple linear regression analysis to examine the driving factors behind energy-consumption variations across climate zones. The results indicate that the energy-saving effectiveness of tilted façades decreases with decreasing latitude. During the cooling season, high-latitude cities exhibit the greatest reduction in cooling demand, with Harbin showing a maximum energy saving exceeding 16%, whereas Guangzhou shows a reduction of only approximately 5%. During the heating season, the tilted façades lead to a certain increase in energy consumption, but this adverse effect also diminishes with decreasing latitude. In terms of annual overall energy performance, Beijing, Shanghai, and Guangzhou achieve total energy savings of approximately 4–5%, while Harbin in the severe cold zone shows limited overall benefits. An analysis of solar radiation characteristics reveals that tilted façades substantially reduce direct solar radiation (by approximately 90%), thereby decreasing total solar heat gain, a trend that aligns closely with the reduction in cooling energy consumption. Moreover, higher window-to-wall ratios are associated with greater energy-saving effects, indicating that outwardly inclined façades are more suitable for office buildings with relatively large glazed areas. Overall, the energy-saving potential of tilted façades is primarily influenced by solar radiation conditions and the balance between cooling and heating demands. Such façades demonstrate good application value in regions with relatively balanced cooling and heating demands or cooling-dominated climates, whereas their application in severe cold regions requires more comprehensive evaluation. This study establishes an analytical framework for assessing the energy performance of tilted façades across different climate zones in China, providing theoretical support and design guidance for climate-adaptive design and form-based energy optimization. Full article

Existing residential buildings constructed under earlier thermal-design standards often lack effective external solar control systems. Building envelope retrofits must extend beyond mere cooling load reductions; instead, they require a holistic evaluation of summer heat rejection, winter solar gain preservation, transmitted solar exposure, and retrofit-induced embodied carbon. This study develops a screening-level method for climate-adaptive passive shading retrofits. The workflow integrates hourly solar-position reconstruction, facade irradiance mapping, shading geometry interception, and a reduced-order 2R2C thermal network. NSGA-II is used to generate Pareto-optimal alternatives, CV-TOPSIS is applied to identify representative trade-off solutions, and a life-cycle-informed carbon payback check within an A1–A4 + B6 boundary is used to test whether operational carbon savings can offset the upfront carbon of shading components and glazing replacement. Five Chinese cities—Haikou, Shanghai, Beijing, Lhasa, and Urumqi—are selected to represent the transition from cooling- to heating-dominated climates. For comparative screening, the reduced-order model shows acceptable agreement with an EnergyPlus benchmark, with NMBE, CV(RMSE), and $R^2$ values of +2.11%, 28.25%, and 0.804, respectively. The selected solutions reveal strong climate dependence in both shading morphology and carbon performance. For instance, Haikou exhibits the largest annual electricity savings (2030.3 kWh/yr) and the shortest Carbon Payback Period (1.8 years). In Lhasa, by contrast, the CV-TOPSIS-selected compromise scheme reduces the transmitted solar exposure proxy but increases annual energy use by 706.1 kWh/yr, indicating that this selected compromise, rather than fixed shading in general, is not carbon-effective within the defined boundary. The proposed method supports climate-specific retrofit screening by jointly considering heating–cooling balance, solar radiation conditions, and regional grid carbon intensity. Full article

Since the late 1970s, during the period of reform and opening-up, China has emerged as one of the fastest-urbanizing countries in the world. The high speed of urbanization and three-dimensional (3D) morphological changes in urban buildings may lead to significant urban challenges, including air and light pollution, the urban heat island effect, and strained human-land relationships. It is therefore crucial to elucidate the pattern of urban 3D morphological change and to investigate the factors that influence these changes. This study proposed a novel method of filtering new buildings using the ALOS and GBH building height data, combined with statistical data and panel data, focusing on spatial-temporal variations and their driving factors of 3D building morphological changes between 2002 and 2020 for 11 prefecture-level cities and 2 municipalities in the Beijing–Tianjin–Hebei (BTH) region. Our findings indicate that the 3D morphological change mechanisms of the same types of cities in the BTH region are similar. The total population negatively impacts the height of newly constructed building areas, and the optimization of the industrial structure positively influences the height of newly developed land. Based on our findings, we propose actionable recommendations to foster sustainable urban development in the BTH region. Full article

The complete community paradigm, emphasising walkable, self-sufficient neighbourhoods, has gained significant global traction, yet the role of sports and physical activity spaces within such frameworks remains undertheorised, particularly in dense Chinese urban environments. This paper introduces the Chrono-Adaptive Sports Space Index (CASI), a preliminary evaluative framework whose diagnostic utility is demonstrated through three contrasting case studies. CASI integrates temporal usage dynamics, demographic composition, smart-city sensor data, and multi-generational programming flexibility to assess sports environments within China’s 15-Minute Complete Community (完整社区, Wánzhěng Shèqū) policy framework. Unlike existing frameworks that assess sports spaces through static metrics, CASI proposes that sports environments must be evaluated across four temporal dimensions: diurnal rhythms, weekly cycles, seasonal transitions, and demographic lifecycle shifts. The four sub-indices are weighted equally (25 points each) as a deliberate first-generation design choice reflecting the absence of pre-existing empirical benchmarks; this assumption requires empirical validation in future research. Through exploratory multi-case analysis of communities in Shanghai (Jing’an District), Chengdu (Tianfu New Area), and Beijing (Chaoyang District), this study provides preliminary evidence suggesting that temporally inert sports spaces may be associated with utilisation losses of 38–52% during off-peak periods and the systematic exclusion of elderly and child populations; these figures should be treated as indicative estimates pending broader empirical validation. A Chrono-Adaptive Design Protocol (CADP) is proposed as a conceptual, practice-informed protocol awaiting prospective empirical evaluation. This research is better characterised as a framework development and initial exploratory application study rather than a validation of a mature instrument. Its primary contribution is a new theoretical and diagnostic lens for complete community planning, together with an agenda for the empirical work needed to develop CASI into a broadly applicable assessment tool. The study’s limitations and a structured five-priority future research agenda are presented in a dedicated section following the Conclusions. Full article

Aging and deterioration of urban underground drainage pipelines frequently trigger road collapses, urban waterlogging and groundwater contamination, posing critical challenges to the operation, maintenance and disaster prevention of urban underground infrastructure. Conventional rehabilitation solutions, including cement-based linings and traditional polymer liners, suffer from inherent limitations such as reduced effective flow cross-sections caused by excessive lining thickness, unsatisfactory corrosion resistance and durability, and high construction disturbance. In this study, a modified polyurea (MPU) material was applied to the trenchless rehabilitation of drainage pipelines via spray-applied pipe lining technology. The mechanical properties and interfacial bonding performance of MPU were systematically characterized at the material scale; full-scale external pressure tests were conducted to investigate the effects of 3–8 mm thick MPU linings on the bearing capacity and failure characteristics of structurally damaged concrete pipes; and the anti-seepage repair performance for local perforation defects was evaluated through void-crossing testing. The results demonstrate that MPU lining can meet the engineering performance requirements for pipeline rehabilitation when applied with matched interfacial primer following standard construction procedures. Even the baseline bond strength tested without primer remains sufficient to ensure stable cooperative load bearing between the lining and the host concrete pipe. The 3–8 mm thick linings increase the cracking load of damaged pipes by 61.7–145.7% and the ultimate load by up to 162.2%, while transforming the failure mode from brittle fracture to ductile failure. For local perforation repair, the 3 mm thick MPU lining achieves a critical hydrostatic failure pressure of 1.23 MPa, maintaining favorable structural integrity and interfacial bonding stability under the test conditions. With a well-balanced combination of thin lining thickness, rapid curing and high structural strengthening efficiency, as well as favorable inherent corrosion resistance, the MPU lining provides novel material alternatives and fundamental experimental evidence for the green trenchless rehabilitation of aged underground pipelines and offers technical support for the safe operation and maintenance of urban underground infrastructure. Full article

With the growing potential correlation between chromium (Cr), molybdenum (Mo), and human health, public attention to these elements has increased markedly. In Beijing, the capital of China, research on the concentration levels of Cr and Mo is urgently needed. In recent years, soil geochemical surveys have been conducted in the Beijing region, with a scale of 1:100,000 in mountainous areas (yielding 8575 data points) and 1:50,000 in plain areas (yielding 29,551 data points). These surveys provide a robust dataset for elucidating the concentrations and distribution patterns of soil elements. In surface soil samples from Beijing (n = 38,126), the mean concentrations of Cr and Mo were 55.7 µg/g and 0.67 µg/g, respectively. Recently, scholars have proposed a 19-level fixed-value method for Mo concentrations. Based on this, the 19-level fixed-value method for Cr concentrations is proposed to facilitate cross-element comparisons. This method classifies the elemental concentrations from its detection limit to its cut-off grade of mineralization into 19 levels on 18 fixed values. With this method, the concentration levels of Cr and Mo in Beijing soils are both at the fifth level on their mean values, which belong to the background level. To compare the Cr and Mo concentrations in soils with other capital cities, statistical parameters of Cr from 20 capital cities and Mo from 11 capital cities were collected. The results show that the mean Cr concentration levels in the 20 cities range from 2 to 10, while the mean Mo concentration levels in the 11 cities range from 5 to 10. In these capital cities, the Cr level of Beijing is at the middle level, and the Mo level is at the low level, which indicates the cross-element comparison on the 19-level fixed-value method. Full article

Analyzing the impervious surface area (ISA) of China’s three major urban agglomerations and expansion pattern of representative cities is of great significance for formulating context-specific urban planning policies and enhancing the resilience of urban development. This research employs impervious surface expansion indicators to reveal the spatiotemporal dynamics of impervious surface area, and further applies the location centrality index (LCI) to investigate the expansion structures and patterns of five megacities. The results indicate that the ISA of China’s three major urban agglomerations expanded from 22,544.10 km² to 69,348.59 km² from 1985 to 2024; both the expansion rate and intensity have exhibited a distinct decelerating trend. However, significant regional variation exists in the peak expansion phases: the Guangdong–Hong Kong–Macao Greater Bay Area Urban Agglomeration (GBA) peaked during the Initial Exploratory Phase (1985–1995), whereas the Yangtze River Delta Urban Agglomeration (YRD) and Beijing–Tianjin–Hebei Urban Agglomeration (BTH) reached their peaks during the High-speed Development Phase (2005–2015). At the urban scale, LCI-based analysis of urban expansion across five megacities reveals that adjacency expansion type has become the predominant form of growth, exceeding 50% in most cities. These findings enhance our understanding of evolutionary trajectories of ISA within urban agglomerations and the expansion patterns of five megacities, providing a scientific basis for sustainable urban planning and urban resilience. Full article

In the context of accelerating artificial intelligence (AI) development, this study explores how AI Usage contributes to employee job performance and innovation performance by activating cognitive and HR system–level mechanisms. Adopting an integrative individual–organizational perspective, this study examines the mediating roles of AI self-efficacy and digital human resource management (HRM) practices in translating AI adoption into employee performance outcomes. Survey data were collected from firms located in major Chinese cities (Beijing, Shenzhen, Xi’an, and Zhengzhou), resulting in 750 valid responses for analysis. The results indicate that AI self-efficacy and digital HRM practices function as significant positive mediators, facilitating the conversion of AI adoption into enhanced work performance and innovation outcomes. Theoretically, this study advances knowledge management studies by highlighting the complementary roles of individual cognitive beliefs and HR systems in enabling AI-driven learning and capability development. Practically, the findings suggest that organizations should embed AI technologies in HR systems that foster learning, knowledge utilization, and continuous innovation. Full article