Search Results (91)

The urban–rural gradient of surface ozone concentration is closely associated with urban scale and has been widely reported in megacities globally. However, in the Sichuan Basin of southwestern China, a paradoxical asymmetric pattern between the ozone gradient and the physical urban footprint has emerged. By integrating multi-source satellite observations (e.g., TROPOMI), reanalysis data (ERA5-Land), and a concentric-ring spatial gradient analysis, we quantify a dipole-like urban surface ozone trap pattern in two megacities (Chengdu and Chongqing) from 2013 to 2019. We found that the urban–rural ozone gradients in Chongqing were substantially steeper than those in Chengdu, despite Chongqing’s smaller physical urban footprint. Specifically, in winter, the maximum daily average 8 h ozone level in the urban core drops to 27.5 μg m⁻³ in Chongqing and 47.9 μg m⁻³ in Chengdu, with outward radial increasing rates of 6.49% and 1.88% per 10 km, respectively. Conversely, the absolute nitrogen dioxide level in Chengdu is higher, highlighting an asymmetric titration behavior between the two cities. Regarding the chemical regime, analysis of the ratio (β) of nitrogen dioxide to formaldehyde reveals that Chongqing’s core operates under a more severe VOC-limited environment (β is 2.53 and radial gradient is −6.77% per 10 km) compared to Chengdu (β is 2.43 and gradient is −5.34% per 10 km). Furthermore, vertical cross-section analyses indicate that Chongqing’s deep-valley topography induces severe boundary layer compression and aerodynamic stagnation. Thus, rather than acting independently, these localized meteorological constraints function as crucial physical modulators that trap precursor emissions and exacerbate the non-linear chemical titration. This study elucidates how synergistic interactions between basin topography, physical urban footprints, and atmospheric chemistry shape localized ozone traps, providing a referable perspective for assessing complex urban atmospheric environments. Full article

To quantify the carbon footprint of cross-border bridges built by Chinese companies in Africa, based on the Janwani Bridge in Tanzania and the life cycle theory, it is divided into five stages: production, transportation, on-site construction, operational maintenance, and demolition and disposal. Using the emission factor method to construct carbon emission models for each stage, while considering cross-border supply chains and the addition of vegetation carbon sinks, we quantify the emissions for each stage. The research is based on the project design stage bill of quantities and construction organization data for prediction and estimation. The energy consumption parameters of construction machinery refer to the Chinese quota standards, and the energy consumption of lighting during the operation period is estimated according to the design parameters. The results show that the total carbon emissions of the life cycle of the bridge is about 41,668,548.20 kgCO₂e, with the production stage being the dominant position (87.48%), and cement and reinforcing steel contributing more than 95% of the emissions during this stage. The operational maintenance stage comes second (7.28%), mainly driven by lighting electricity (accounting for 73.65% of the total emissions in this stage), attributed to the local power grid dominated by fossil fuels. Sensitivity analysis shows that the key factors are ranked as cement > reinforcing steel > electricity > diesel. Considering the reality of insufficient supply of low-carbon materials and weak infrastructure in Africa, emission reduction measures are proposed from three aspects: optimizing concrete mix proportion, controlling construction machinery, and implementing intelligent lighting. The research contribution lies in incorporating the entire cross-border transportation chain and newly added vegetation carbon sinks into the LCA boundary of bridges, while considering the dual attributes of “technology output + localized operation”, and constructing a carbon emission accounting model adapted to the built-up areas of African cities. On this basis, the carbon emission characteristics of the life cycle were quantitatively analyzed, feasible emission reduction measures in the region were proposed, and the carbon reduction potential was calculated, providing scientific basis for low-carbon control of Chinese enterprises’ overseas bridges. Full article

Using truck GPS trajectory data, this study measures the intensity of economic spatial linkages in Hubei Province at both administrative and cross-administrative scales and examines the hierarchical structure and spatial pattern of its urban economic network. By comparing the results with existing regional plans, the study provides empirical support for regional coordination and spatial planning. Network centrality analysis, linkage intensity measurement, and community detection algorithms are integrated to construct a topological model of the urban economic network from three dimensions: urban node hierarchy, inter-city linkage intensity, and urban cluster structure. To overcome administrative boundary constraints, a 5 km × 5 km grid-based approach is applied to identify functionally connected urban economic communities. The results indicate that Hubei Province’s urban economic network exhibits a highly dominant core accompanied by multiple secondary supporting centers. While the Wuhan Metropolitan Area demonstrates high economic activity, internal horizontal linkages remain relatively weak, and the roles of Yichang and Xiangyang as regional sub-centers require further strengthening. Grid-based analysis further reveals pronounced cross-administrative economic linkages. Accordingly, this study suggests strengthening support for regional sub-centers and promoting better alignment between administrative space and functional space within the spatial planning system, with enhanced cross-regional coordination. Full article

Digital twins (DTs) enable innovation across industries. While business discourse promotes DTs as catalysts for new business models, the academic literature lacks a cohesive understanding of how DTs enable different types of business innovation and what distinguishes cross-organizational innovation from firm-level innovation. This paper conducts a systematic literature review of 60 articles, analyzing 25 business innovation cases through a typology derived from established frameworks extended to address cross-organizational innovation. Process innovation appeared in nearly all the cases (24 of 25), confirming DTs’ fundamental role as operational technology. Product innovation manifests in two patterns: the twin as offering and the twin enabling offerings. paradigm innovation appeared in over half of cases, taking context-specific forms including business model transformation, governance mechanisms, and organizational restructuring. Beyond-firm innovation clusters in healthcare, smart cities, sustainability transitions, and energy systems where cross-organizational coordination is required. Beyond-firm cases consistently co-occur with paradigm innovation and exhibit higher innovation type diversity than single-firm cases, suggesting that cross-boundary coordination requires accompanying organizational restructuring. The study contributes a Digital Twin Innovation Typology extending established frameworks to capture innovation no single firm can achieve alone. Practical implications address how domain context shapes innovation potential and coordination mechanisms required for beyond-firm innovation. Full article

Transport infrastructure serves as a critical physical carrier for constructing a unified national market and promoting coordinated regional economic development. Addressing the practical contradiction between rapid transport network expansion and persistent regional development imbalances, this paper constructs a comprehensive transport infrastructure service efficiency index using panel data from 297 prefecture-level cities in China from 2010 to 2023. We systematically investigate the nonlinear impact and underlying mechanisms of transport infrastructure on inter-city economic disparities. The findings reveal a significant inverted U-shaped relationship between transport infrastructure construction and regional economic disparity. Specifically, in the early stages of transport development, the dominance of the agglomeration effect leads to widening regional gaps; once a specific threshold is crossed (an index value of approximately 0.274), the diffusion effect emerges, facilitating convergence. This nonlinear relationship exhibits significant regional heterogeneity: the eastern region has largely crossed the inflection point into the convergence phase, while the western region remains in the “climbing” period dominated by polarization effects. Mechanism testing indicates that labor factor allocation is the core driver of this inverted U-shaped evolution. This study not only clarifies the dynamic boundaries of transport infrastructure’s impact on regional economic patterns but also provides empirical evidence for formulating differentiated transport and regional coordination policies for regions at different developmental stages. Full article

Urban neighborhood parks are essential infrastructure for sustainable cities, supporting physical and mental health, social cohesion, and climate adaptation. Equity-oriented park planning, however, requires accurate identification of residents who can access parks within network-constrained travel time thresholds. Many accessibility studies estimate served populations using coarse administrative zones and areal-weighting assumptions, which can bias results in heterogeneous, vertically developed districts. This study develops a building-based population allocation framework (implemented via a building centroid overlay) that integrates Statistics Korea’s census output areas (2023 Q4 release) with the Ministry of Land, Infrastructure and Transport (MOLIT)’s GIS Integrated Building Information database (2023 Q4 release) and applies it to Yongsan-gu (Yongsan District), Seoul. Park entrances were verified and digitized using street-view imagery available on multiple web map platforms, and walkable service areas (5 and 10 min) were delineated via network analysis. Potential service coverage and unserved population were then estimated under three spatial configurations—administrative dong (neighborhood-level administrative unit in Seoul; hereafter administrative unit), census output area, and building-based allocation—and compared. Under the 10 min scenario, the unserved share reached 24.6% at the administrative unit level but decreased to 5.9% and 4.3% when using census output areas and building-based allocation, respectively. The building-based approach additionally revealed micro-scale clusters of unserved residents near localized pedestrian constraints and boundary-crossing areas that are obscured by zone-based methods. These findings demonstrate the sensitivity of access-based potential service coverage diagnostics to spatial unit choice and population disaggregation and suggest that building-based population allocation can improve the targeting of park pro-vision policies and promote spatial equity in dense, vertically developed cities. Full article

Urban socio-economic resilience to climate change has emerged as a central research theme as cities increasingly confront interconnected environmental, economic, and social risks. Despite the rapidly expanding body of literature, the conceptual boundaries, thematic evolution, and analytical priorities of this field remain fragmented across disciplines, and no prior study has systematically mapped the socio-economic dimension of urban resilience through a combined bibliometric and thematic analysis over a multi-decadal horizon. This study addresses that gap by providing a systematic review of global research on urban socio-economic resilience to climate change, integrating bibliometric and thematic analyses of peer-reviewed publications from 1990 to 2025. Following the PRISMA 2020 guidelines, records were retrieved from the Web of Science Core Collection and subjected to a multi-stage screening procedure that combined automated relevance scoring with mandatory manual validation of the socio-economic dimension, resulting in a final dataset of 5076 publications. The analysis examines conceptual interpretations of socio-economic resilience, dominant climate hazards affecting urban systems, methodological approaches and assessment indicators, adaptation strategies and governance responses, and emerging research gaps. The results reveal a marked acceleration of scientific output after 2015, driven by the Paris Agreement and the IPCC Special Report on Global Warming of 1.5 °C (2018). The bibliometric network analyses identify adaptation, vulnerability, flooding, and sustainability transitions as the core thematic clusters. The findings trace a paradigmatic trajectory from equilibrist recovery frameworks toward transformative, socio-economically grounded resilience models and reveal persistent gaps in the operationalization of governance, equity measurement, and geographic representation. By synthesizing three-and-a-half decades of scholarship, this review clarifies the intellectual structure of the field and proposes four specific post-2026 research pathways that emphasize longitudinal cross-city comparisons, mixed-methods assessments, sector-specific compound hazard analyses, and governance mechanism studies. Full article

High-precision 3D building data are pivotal for smart city development, urban planning, and disaster management. However, large-scale building extraction from airborne LiDAR point clouds remains challenging due to semantic ambiguity, uneven point density, and complex architectural structures. To address these limitations, we propose a novel framework integrating geometric topology perception with cross-dimensional attention mechanisms within a Sparse Voxel Convolutional Neural Network (SPVCNN). The key contributions include: (1) an enhanced LaserMix++ multi-scale hybrid augmentation strategy featuring cross-scene block replacement, ground normal–constrained rotation, and non-uniform scaling; (2) a dual-branch SPVCNN architecture embedding a collaborative module of Geometric Self-Attention (GSA) and Cross-Space Residual Attention (CSRA) to preserve topological consistency and enable cross-dimensional feature interaction; and (3) a Boundary Enhancement Module (BEM) specifically designed to resolve boundary ambiguity and overlapping predictions. Evaluated on a 177 km² dataset covering Washington, D.C., our method significantly outperforms the baseline SPVCNN, improving accuracy by 12.04 percentage points (0.8212 to 0.9416) and Intersection over Union (IoU) by 9.96 percentage points (0.866 to 0.9656). Furthermore, it surpasses mainstream networks such as Cylinder3D and MinkResNet by over 50% in absolute accuracy gain. These results demonstrate the effectiveness of synergistically combining geometric perception with adaptive attention for robust building extraction from large-scale LiDAR data. Full article

Sewerage systems are a main element of a city’s infrastructure. Roughness coefficients are fundamental parameters for sewage system operation. The intermittent nature of the flow leads to the appearance of deposits that become an integral part of the sewerage systems. Deposited material not only leads to the loss of hydraulic capacity and decreases the concentration of dissolved oxygen (which is found in direct relation to all quality parameters), but it also results in more transported particles being intercepted. In the design calculations, the roughness coefficient is estimated rather than calculated. It has been demonstrated that the estimation of stress within and above roughness elements improves the predictive capability for the concentration of suspended sediment. In this study, we focused on a local evaluation of the roughness coefficient when the flow velocity is below the minimum self-cleansing velocity. Some authors consider the selection of the most reliable method for estimating bed shear stress to be the main challenge. Other authors have suggested that all possible methods should be applied simultaneously to achieve a reliable bed shear stress estimation, knowing that the roughness coefficient can be determined through the shear boundary stress. We calculate the local roughness coefficient in Manning’s equation using a laboratory model, considering clear water flowing over a solid boundary with consolidated deposits, represented by artificial roughness elements (calibrated hemispheres). The European standard EN 752:2017 specifies a minimum average cross-sectional velocity of 0.7 m/s for pipe self-cleansing. This study established the range of possible roughness coefficient values when the minimum velocity design criterion is not met. The second criterion was to consider acceptable a sediment deposit occupying between 1% and 2% of the collector diameter. Velocity distributions around artificial roughness and statistical parameters of the turbulent flow were obtained using a PIV system. Five methods were implemented and the range of roughness coefficient values varied between 0.007 and 0.023. This variation is closely related to sewer performance. We selected the dissipation method as the primary reference for this study, as it is most closely aligned with the underlying physics of flow over roughness elements. This approach allows for robust validation by correlating multiple characteristic mechanisms of the turbulent cascade. Full article

This study utilizes digital transformation and patent data from A-share listed companies on the Shanghai and Shenzhen stock exchanges in China between 2011 and 2021 to examine the influence of digital transformation on the quality of cross-regional collaborative innovation. The findings reveal that the cooperative innovation network exhibits pronounced small-world characteristics. In terms of spatio-temporal evolution, China’s urban collaborative innovation network demonstrates a notable quadrilateral spatial structure and has evolved toward a multicenter pattern. Moreover, the advancement of digital transformation positively contributes to both the quality and quantity of cross-regional cooperative innovation. By enhancing the relational embeddedness among cities, digital transformation facilitates improved outcomes in collaborative innovation. Furthermore, when the volume of digital patent applications surpasses a certain threshold, its positive effect on the quality of cross-regional collaborative innovation accelerates. These results provide empirical evidence from a major emerging economy, offering insights that can inform policies and strategies in other regions undergoing digital transition. The mechanisms identified, such as network structure evolution and relational embeddedness, contribute to a broader understanding of how digital transformation shapes innovation dynamics across geographical boundaries in a globalized knowledge economy. Full article

Amid rapid urbanization in China, widespread gated residential districts have created physical and visual isolation from surrounding nature, undermining environmental benefits and daily accessibility. The emergence of a twenty-first-century “sharing” paradigm reshapes how buildings and landscapes are used and experienced, opening new opportunities for diversified sharing between communities and natural systems. Yet, despite mature research on city-scale landscape sharing, micro-scale tools to balance sharing versus exclusive route allocation—and to operationalize cross-system sharing-route design—remain limited. This study examines nature-integrated community design through the Landscape Route Sharing Ratio (LRSR), a metric derived from the Length and Density of Sharing Landscape Route (L_s/D_s), the Length and Density of Non-shared Landscape Route (L_ns/D_ns). It analyzes eight cases using a mixed-methods approach (field surveys, spatial mapping, planning-document review and quantitative measurement), and identifies five core cross-system features through typological analysis: extension to surrounding landscapes (ENL), cross-boundary landscape axes (CBLA), multi-scale hierarchy (MSH), multi-elevation systems (MES), and non-motorized priority (NMP). This study demonstrates that higher LRSR values significantly enhance landscape integration and pedestrian experiences. By establishing actionable target ranges (0.50–0.70), the research provides a practical decision-support tool for nature-integrated community design, advancing the methodological understanding of how shared routes foster ecological and social vitality in contemporary urban environments. The framework effectively bridges the gap between quantification with design guidance for nature-integrated communities. Full article

Under the dual impact of environmental issues and the energy crisis, new energy vehicles (NEVs) have gradually become a phenomenal emerging industry in China, also essentially becoming a new engine to support the growth of China’s economy. While topics related to the NEV industry have gained widespread attention, there is a lack of studies specifically focusing on the characteristics of its industrial spatial distribution pattern. Based on the data related to NEV-listed companies located in the Yangtze River Delta (YRD) region in 2022, this study constructs the corresponding city network using the method of social network analysis (SNA) and interprets the structural features of this network. The results reveal the following: (1) The network exhibits three fundamental characteristics: low density, short path length, and multiple centers. (2) The NEV industry in the YRD has formed the agglomeration pattern of three major “clubs”, projected on the map in the shape of a “golden bow”. (3) Cities in the YRD show a “pyramid-type” collaboration in the NEV industry. (4) Collaboration between cities in the NEV industry can cross the limits of geographic proximity and even administrative boundaries. Full article

Assessing urban resilience under compound shocks requires observable and comparable process evidence that can inform resilient land governance and cross-jurisdiction planning. Using China’s Pilot Free Trade Zones (PFTZs) as a staged institutional setting, this research examines whether institutional exposure is associated with deviation–recovery trajectories of urban activity during the 2020 COVID-19 shock and whether these associations propagate through spatial spillovers with an identifiable scale profile. Institutional exposure is operationalized by the prefecture-level cities actually covered by PFTZ functional areas. With harmonized administrative boundaries, we construct an annual city-level VIIRS nighttime light (NTL) series for 2013–2024 and treat NTL as an activity-change signal rather than a direct proxy for output. We trace shock deviation in 2020 and subsequent recovery via staged differencing. Spatial interaction frictions are represented by least-cost path distance (LCPD) derived from a multi-source cost surface, which is used to build a gravity-based spatial weight matrix. Estimation relies on the Spatial Durbin Model (SDM), with LeSage–Pace impact decomposition to distinguish direct and spillover effects, complemented by distance-threshold diagnostics to map attenuation patterns. Results indicate persistent clustering within the PFTZ-related urban system. The shock year is characterized by compressed connectivity and fragmented brightening, whereas recovery proceeds in a layered manner with earlier core repair, partial corridor reconnection, and weaker adjustment at the periphery. Spatial dependence in activity change is statistically significant. Associations linked to institutional exposure are realized primarily locally, while structural and scale conditions more readily operate through spatial externalities. Spillovers are most detectable at meso-scales and attenuate gradually across distance thresholds. Overall, the integrated earth-observation and spatial-econometric framework provides replicable geospatial evidence to support resilient land governance and regional coordination under common shocks. Full article

Constructing ecological networks (ENs) is an effective measure to mitigate the conflict between urban development and ecological conservation. However, existing simulating methods lack adequate consideration of human ecological demands and the spatial scale differences between these demands and natural ecological processes. This might lead to issues such as incomplete ecological process cycles or structural mismatches being overlooked during ENs simulations. To address these gaps, this study proposed an urban multi-scale nested ENs simulating framework that integrates human ecological demands with natural ecological processes. The framework first simulated an ENs focused on natural ecological process cycles at a global scale (GS). Then, it simulated an ENs centered on human ecological needs within the core urban areas at local scale (LS). Finally, it nested these multi-scale ENs by using cross-scale ecological supply sources as connecting points. This framework was applied to simulate spatio-temporal pattern changes in ENs of Jinan City, a core city in downstream of the Yellow River in China, aiming to mitigate cross-scale ecological conflicts between human–nature interactions under the background of urbanization. The study’s findings revealed that the area of demand sources increased by 8.56 times over 20 years. the area of cross-scale supply sources decreased by 15 km² relative to 2000, and the deterioration in connectivity was more pronounced in GS compared to LS, with a decline of approximately 13.8%. These changes indicate the presence of incomplete ecological process cycles and structural mismatches across the multi-scale boundaries within the study area, which have been worsening annually. We recommend optimizing Jinan City’s multi-scale ecological network through three key strategies: rectifying internal structural mismatches, protecting core ecological areas, and aligning regional ecological demands. Implementing these strategies could significantly improve the network structure, reduce cross-scale mismatches, and enhance ecological connectivity by about 9%. This study highlights the importance of addressing structural mismatches and promoting complete ecological cycles in urban multi-scale ENs simulating, providing valuable insights for formulating urban multi-scale ecological conservation and restoration policies. Full article

Against the escalating challenges of global climate change and intensifying resource-environment constraints, exploring the green effects of industrial spatial organization has become crucial. Utilizing panel data from the Yangtze River Delta cities spanning 2011–2023, this study empirically examines the nonlinear impact of manufacturing-producer services co-agglomeration on urban green efficiency. The results reveal a significant U-shaped relationship: co-agglomeration initially suppresses efficiency due to coordination costs and congestion effects, but after crossing a specific threshold, the resulting scale economies and knowledge spillovers dominate and begin to promote green enhancement. Mechanism tests indicate that industrial upgrading serves as a direct mediating channel, while the mediating effect of green technological innovation exhibits a time lag. Further heterogeneity analysis shows that this U-shaped pattern is particularly pronounced in cities with low agglomeration levels, those not designated as low-carbon pilots, and non-resource-based cities. This study uncovers the nonlinear dynamics and key boundary conditions of the green effects arising from industrial co-agglomeration, providing an empirical basis for implementing differentiated regional spatial coordination policies. Full article