Search Results (10,328)

Understanding food production (FP) supply–demand relationships is crucial for achieving Sustainable Development Goal 2 (SDG 2). Previous studies often assessed these relationships by overlaying supply and demand without considering food production flow (FPF). This study developed a framework from the perspectives of supply, demand, and flow to analyze the Agrifood System (AFS) of four major urban agglomerations in China: Beijing–Tianjin–Hebei, the Yangtze River Delta, the Pearl River Delta, and Chengdu–Chongqing. It applied the enhanced two-step floating catchment area model to simulate the magnitude and direction of four types of FPF—grains, vegetables, fruits, and meat—under three scenarios: intra-city flow, intra-provincial flow, and free flow. Results revealed mismatches in the FP supply–demand, and incorporating FPF improved these relationships. As flow restrictions eased, intra-city flows decreased, cross-regional flows expanded, and supply–demand imbalances were alleviated. Enhancing regional cooperation plays a key role in addressing the spatial mismatch between food supply and demand. These findings provide useful insights for addressing food supply–demand mismatches through more proper agricultural land allocation, better alignment of consumption patterns, and improvements in the flow system. Full article

Assessment of cultural ecosystem services (CESs) is a key component in advancing the sustainable development of urban ecosystems. Mapping the spatial distribution of CESs provides spatially explicit insights for urban landscape planning. However, most assessments lack regional adaptability, particularly in cities with pronounced environmental and cultural heterogeneity. To address this gap, this study focused on the central urban area of Lhasa, using communities as units to develop a tailored CES assessment framework. The framework integrated the MaxEnt model with multi-source indicators to analyze the spatial distribution of five CES categories and their relationships with environmental variables. Spatial statistics and classification at community level informed the CES spatial optimization strategies. Results indicated that high-value CES areas were predominantly concentrated in the old city cluster, typified by Barkhor and Jibenggang subdistricts, following an east–west spatial pattern along the Lhasa River. Distance to tourist spot contributed 78.3% to cultural heritage, 86.1% to spirit and religion, and 42.2% to ecotourism and aesthetic services, making it the most influential environmental variable. At the community level, CESs exhibited a distinct spatial gradient, with higher values in the central area and lower values in the eastern and western peripheries. For the ecotourism and aesthetic category, 61.47% of the community area was classified as low service, whereas only 1.48% and 7.33% were identified as excellent and high. Moreover, communities within subdistricts such as Barkhor and Zhaxi demonstrated excellent service across four CES categories, with notably lower performance in the health category. This study presents a quantitative and adaptable framework and planning guidance to support the sustainable development of CESs in cities with similar characteristics. Full article

Efficient urban land use is a cornerstone of sustainable city development, yet the drivers of such efficiency are increasingly complex in an era of spatial transformation. As industrial specialization and collaboration deepen, cities are becoming interconnected through complex networks. These “invisible threads” are redefining the dynamics of land use and spatial efficiency. This study examines the influence of intercity industrial networks on urban land use efficiency by constructing urban networks from multi-regional input–output data and evaluating city performance using a super-SBM model. We employed Tobit regression and mediation analysis to identify the mechanisms. Results indicate that both the quantity and quality of urban network connections significantly enhance land use efficiency, with notable differences across city types. The positive effect of industrial network centrality is most pronounced in large cities. In growing cities, both the number and quality of industrial linkages promote efficiency, whereas in shrinking cities, connection quality is more critical than quantity. Mechanism analysis reveals that industrial networks improve land use efficiency primarily by expanding intermediate goods markets and fostering technological innovation. Full article

The scientific evaluation of the coordinated development level of the Yangtze River Delta Urban Agglomeration is crucial for promoting the localization of the Sustainable Development Goals (SDGs). This study, based on the SDGs framework, utilizes data from 41 prefecture-level cities in the Yangtze River Delta from 2013 to 2023 to establish a five-dimensional evaluation index system, covering urban–rural integration (SDG 10), scientific and technological innovation (SDG 9), infrastructure (SDG 9.1), ecological environment (SDG 13/14/15), and public services (SDG 3/4/11). By applying the coupling coordination degree model, kernel density estimation, and the standard deviation ellipse method, the study systematically assesses the regional coordinated development level and its spatio-temporal evolution patterns. The findings reveal that from 2013 to 2023, the development indices of the five subsystems showed a fluctuating upward trend, with significant disparities in growth rate and stability. The overall regional coordination degree continuously improved, and differences diminished, with the coupling degree and coupling coordination degree exhibiting a “polarization followed by an overall leap” pattern. The coupling coordination degree evolved in three stages: “imbalance in mutual feedback among elements, strengthening of coordination mechanisms, and deepening of policy innovation”, with spatial differentiation and clustered development coexisting. Spatially, the distribution center shifted through three phases: “policy-driven”, “market-regulated”, and “technology-led”, forming an axial reconstruction from northwest to southeast, ultimately establishing a multi-center coordinated development system. Full article

Urban community gardens (UCGs) have been expanding globally. Initially created to provide fresh, organic produce for low-income populations, UCGs have evolved into models of sustainable agriculture with increasing economic significance. Beyond their economic role, UCGs serve as vital social spaces and may be categorized as third places—informal gathering spaces that foster social connections and promote well-being. This study analyzes and compares the impact of UCGs as third places in Toronto and São Paulo, focusing on their contributions to social cohesion, financial resilience, environmental sustainability, cultural transmission, and mental well-being. It is a review-based study utilizing publicly available data from policy documents, the academic literature, and official websites. Although the practice of community gardening has a long-standing history, the concept of gardens as third places is relatively recent, emerging in the late 1980s. In recent decades, there has been growing interest in their association not only with aesthetic and functional benefits but also with health, well-being, and social connection. UCGs are valuable not only for food production but also for fostering social interaction, preserving cultural practices, and promoting overall well-being. Cities must develop policies that strengthen community resilience by recognizing and supporting UCGs as essential third places. Full article

Urban thermal environments critically impact human settlements and sustainable urban development. In this study, a multi-index framework integrating Landsat TM/ETM+/OLI observations (2004–2019) is developed to quantify the contributions of “source–sink” landscapes to urban heat island (UHI) dynamics in Guangzhou, China, with direct implications for advancing sustainable development. Urban–rural gradient analysis was combined with emerging spatiotemporal hotspot modeling, revealing the following results: (1) there were thermal spatial heterogeneity with pronounced heat accumulation in core urban zones and improved thermal profiles in northern sectors, reflecting a transition from “more sources, fewer sinks” in the southwest to “fewer sources, more sinks” in the northeast; (2) UHIs were effectively mitigated within 25–35 km of the city center, with the landscape effect index (LI > 1) indicating successful sink-dominated cooling; (3) spatiotemporal hotspots were observed, including persistent UHIs in old urban areas contrasting with environmentally vulnerable coldspots in suburban mountainous regions, highlighting uneven thermal risks. This framework provides actionable strategies for sustainable urban planning, including optimizing green–blue infrastructure in UHI cores, enforcing cool material standards, and zoning expansion based on source–sink dynamics. This study bridges landscape ecology and sustainable development, offering a replicable model for cities worldwide to mitigate UHI effects through evidence-based landscape management. Full article

Urban flooding, intensified by climate change, poses significant threats to sustainable development, necessitating accurate precipitation projections for effective risk management. This study utilized Bayesian Model Averaging (BMA) to optimize CMIP6 multi-model ensemble precipitation projections for Shanghai, integrating Delta statistical downscaling with observational data to enhance spatial accuracy and reduce uncertainty. After downscaling, RMSE values of daily precipitation for individual models range from 10.158 to 12.512, with correlation coefficients between −0.009 and 0.0047. The BMA exhibits an RMSE of 8.105 and a correlation coefficient of 0.056, demonstrating better accuracy compared to individual models. The BMA-weighted projections, coupled with Soil Conservation Service Curve Number (SCS-CN) hydrological model and drainage capacity constraints, reveal spatiotemporal flood risk patterns under Shared Socioeconomic Pathway (SSP) 245 and SSP585 scenarios. Key findings indicate that while SSP245 shows stable extreme precipitation intensity, SSP585 drives substantial increases—particularly for 50-year and 100-year return periods, with late 21st century maximums rising by 24.9% and 32.6%, respectively, compared to mid-century. Spatially, flood risk concentrates in peripheral districts due to higher precipitation exposure and average drainage capacity, contrasting with the lower-risk central urban core. This study establishes a watershed-based risk assessment framework linking climate projections directly to urban drainage planning, proposing differentiated strategies: green infrastructure for runoff reduction in high-risk areas, drainage system integration for vulnerable suburbs, and ecological restoration for coastal zones. This integrated methodology provides a replicable approach for climate-resilient urban flood management, demonstrating that effective adaptation requires scenario-specific spatial targeting. Full article

Rapid socio-economic development has made energy application and environmental issues increasingly prominent. Hydrogen energy, clean, eco-friendly, and highly synergistic with renewable energy, has become a global research focus. This study, using the EnergyPLAN model that includes the electricity, transportation, and industrial sectors, takes Jinan City as the research object and explores how hydrogen penetration changes affect the decarbonization path of the urban integrated energy system under four scenarios. It evaluates the four hydrogen scenarios with the entropy weight method and technique, placing them in an order of preference according to their similarity to the ideal solution, considering comprehensive indicators like cost, carbon emissions, and sustainability. Results show the China Hydrogen Alliance potential scenario has better CO₂ emission reduction potential and unit emission reduction cost, reducing them by 7.98% and 29.39%, respectively. In a comprehensive evaluation, it ranks first with a score of 0.5961, meaning it is closest to the ideal scenario when cost, environmental, and sustainability indicators are comprehensively considered. The Climate Response Pioneer scenario follows with 0.4039, indicating that higher hydrogen penetration in terminal energy is not necessarily the most ideal solution. Instead, appropriate hydrogen penetration scenarios should be selected based on the actual situation of different energy systems. Full article

Climate change has emerged as a critical global issue. Land-use/cover change (LUCC) plays a pivotal role in influencing terrestrial ecosystem carbon cycles and further regulates carbon emission intensity by reshaping the spatial characteristics of landscape patterns. Taking 300 Chinese cities as the study area, an analytical framework encompassing carbon emission accounting, regional land-use landscape pattern analysis, spatiotemporal correlation between landscape patterns and carbon emissions, and economic “core-periphery” disparities was presented. The land-use carbon emissions and landscape pattern indices of each city from 2005 to 2020 were calculated, and the geographically weighted regression (GWR) model was employed to examine the impact of land-use landscape pattern changes on carbon emissions from an urban perspective. Furthermore, the cities were categorized into developed and underdeveloped groups based on the median per capita GDP to compare how economic development levels moderate this impact mechanism. The results indicate that the relationship between landscape patterns and carbon emissions exhibits significant spatial heterogeneity, highlighting the complexity of the influence of land-use morphology on carbon emissions. Sustainable land-use strategies must account for regional disparities in economic levels, planning capacity, and administrative characteristics rather than pursuing a uniform urban form. Economic development significantly moderates the carbon mitigation effects of landscape patterns through its influence on spatial governance capacity, leading to pronounced differences between cities at varying development levels. Moving forward, regionally tailored approaches that integrate landscape optimization with industrial transformation and ecological conservation should be prioritized to provide spatial solutions for achieving the carbon peaking and carbon neutrality goals. Full article

Human perception of urban streetscapes plays a crucial role in shaping human-centered urban planning and policymaking. Traditional studies on safety perception often rely on labor-intensive field surveys with limited spatial coverage, hindering large-scale assessments. To address this gap, this study constructs a street safety perception dataset for Wuhan, classifying street scenes into three perception levels. A convolutional neural network model based on transfer learning is developed, achieving a classification accuracy of 78.3%. By integrating image-based prediction with spatial clustering and correlation analysis, this study demonstrates that safety perception displays a distinctly clustered and uneven spatial distribution, primarily concentrated along major arterial roads and rail transit corridors by high safety levels. Correlation analysis indicates that higher safety perception is moderately associated with greater road grade, increased road width, and lower functional level while showing a weak negative correlation with housing prices. By presenting a framework that integrates transfer learning and geospatial analysis to connect urban street imagery with human perception, this study advances the assessment of spatialized safety perception and offers practical insights for urban planners and policymakers striving to create safer, more inclusive, and sustainable urban environments. Full article

Autonomous public transport (APT) is revolutionizing urban mobility by integrating advanced technologies, including electric autonomous buses and shared autonomous vehicles (SAVs). This paper examines the historical evolution of APT, from early automation efforts in the 1920s to the deployment of autonomous shuttles in contemporary cities. It highlights technological milestones, legislative developments, and shifts in public perception that have influenced the adoption of APT. The research identifies key benefits of APT, including enhanced road safety, reduced greenhouse gas emissions, and improved cost-efficiency in public transport operations. Additionally, the environmental potential of SAVs to reduce traffic congestion and emissions is explored, particularly when integrated with renewable energy sources and sustainable urban planning. However, the study also addresses significant challenges, such as handling emergencies without human intervention, rising cybersecurity threats, and employment displacement in the transportation sector. Social equity concerns are also discussed, especially regarding access and the risk of increasing urban inequality. This paper contributes to the broader discourse on sustainable mobility, transportation innovation, and the future of smart cities by providing a comprehensive analysis of both opportunities and obstacles. Effective policy frameworks and inclusive planning are essential for the successful implementation of APT systems worldwide. Full article

As the urbanization and industrialization processes in developing countries continue to advance, environmental issues caused by carbon dioxide emissions (CDEs) have become a significant research topic in the field of sustainable development. However, existing research has primarily focused on macro and meso scales such as global, national, and urban levels, and due to limitations in data precision, in-depth exploration of spatial heterogeneity within cities remains insufficient. To address this, this study utilizes China high-resolution emission gridded data (CHRED) to establish a theoretical analytical framework for spatial zoning of urban carbon emissions. The main innovations of this study are as follows: first, a stepwise analysis method matching carbon emissions with spatial patterns was designed based on CHRED data; second, by establishing a “ring-layer and direction” model, the study systematically revealed the spatial differentiation characteristics of carbon emissions within cities. Empirical research using Shenzhen as a case study shows that the city’s CDE intensity (CDEI) is generally at a medium-to-low level, but exhibits significant spatial heterogeneity, with Nanshan District and Kuiyong District forming two major high-emission core areas. Further analysis reveals that during the processes of urbanization and industrialization, population density, nighttime light intensity index, and the proportion of construction land are the key drivers influencing the spatial pattern of carbon emissions. This study provides scientific basis and decision-making references for optimizing urban spatial layout to achieve the “dual carbon” goals. Full article

With intensifying watershed pollution pressures and growing ecological vulnerability, scientifically revealing and enhancing the water environmental carrying capacity is crucial for ensuring the long-term health of the basin and the sustainable socioeconomic development of the region. However, the dynamic regulatory mechanisms linking narrow-sense and broad-sense water environmental carrying capacity remain poorly understood, limiting the development of integrated management strategies. This study systematically investigated the changing trends of both the narrow-sense and broad-sense water environmental carrying capacity in the Harbin section of the Songhua River basin through model calculations, along with the regulatory mechanisms of its key influence indicators. The results of the study on the carrying capacity of the water environment in the narrow sense show that permanganate, total phosphorus, and ammonia nitrogen exhibited partial carrying capacity across water periods, while dissolved oxygen decreased during flat and dry periods, with only limited capacity remaining at the Ash River estuary and in the Hulan River. The biochemical oxygen demand in the Ash River was consistently overloaded, and total nitrogen showed insufficient capacity except during the abundant water period. Broad-sense analysis indicated that improving urbanization quality, water supply infrastructure, and drinking water safety could effectively reduce future overload risks, with projections suggesting a transition from critical to loadable levels by 2030, though latent threats persist. Correlation analysis between narrow- and broad-sense indicators informed targeted control strategies, including stricter regulation of nitrogen- and phosphorus-rich industrial discharges, restoration of aquatic vegetation, and periodic dredging of riverbed sediments. This work is the first to dynamically integrate pollutant and socio-economic indicators through a hybrid modelling framework, providing a scientific basis and actionable strategies for improving water quality and achieving sustainable management in the Songhua River Basin. Full article

Urban carbon reduction is instrumental in enabling cities to realize their developmental sustainability objectives. However, regional disparities in economic development pose significant challenges to low-carbon transitions. This study utilizes panel data from 282 cities in China spanning 2006–2021, considering the energy saving and emission reduction (ESER) fiscal policy as an external shock. Using a multi-period difference-in-differences approach, we assess how ESER impacts urban carbon emissions. Our findings indicate that ESER significantly reduces municipal carbon emissions by an average of 23.3% compared to non-pilot cities. Mechanism analyses suggest that this effect operates through reduced energy consumption, improved industrial structure, and enhanced green innovation. ESER’s impact exhibits heterogeneity across cities with different levels of economic development, population size, innovation capacity, and industrial composition. Moreover, we find evidence of spatial spillover effects, as ESER benefits extend to neighboring regions. These results confirm the effectiveness of ESER in promoting low-carbon development and offer practical implications for enhancing environmental governance through green fiscal instruments. Full article

Digital city planning increasingly relies on data-driven approaches to address complex urban sustainability challenges through innovative network analysis methodologies. This study introduces a comprehensive spatiotemporal network framework to examine digital innovation networks as fundamental infrastructure for urban sustainable development, focusing on the Yellow River Basin as a representative case study. Utilizing digital patent data as innovation indicators across 57 urban centers, we employ advanced network analysis techniques including Social Network Analysis (SNA) and the Quadratic Assignment Procedure (QAP) to investigate the spatiotemporal evolution patterns and underlying driving mechanisms of regional digital innovation networks. The methodology integrates big data analytics with urban planning applications to provide evidence-based insights for digital city planning strategies. Our empirical findings reveal three critical dimensions of urban sustainable development through digital innovation networks: First, the region demonstrated significant enhancement in digital innovation capacity from 2012 to 2022, with accelerated growth patterns post 2020, indicating robust urban resilience and adaptive capacity for sustainable transformation. Second, the spatial network configuration exhibited increasing interconnectivity characterized by strengthened urban–rural linkages and enhanced cross-regional innovation flows, forming a hierarchical centrality pattern where major metropolitan centers (Xi’an, Zhengzhou, Jinan, and Lanzhou) serve as innovation hubs driving coordinated regional development. Third, analysis of network formation mechanisms indicates that spatial proximity, market dynamics, and industrial foundations negatively correlate with network density, suggesting that regional heterogeneity in these characteristics promotes innovation diffusion and strengthens inter-urban connections, while technical human capital and governmental interventions show limited influence on network evolution. This research contributes to the digital city planning literature by demonstrating how data-driven network analysis can inform sustainable urban development strategies, providing valuable insights for policymakers and urban planners implementing AI technologies and big data applications in regional development planning. Full article