Search Results (97)

Building community resilience is essential for ensuring that communities can not only survive but also thrive in the face of various challenges and uncertainties. However, existing research has deficiencies in the comprehensive evaluation framework and systematic analysis of different types of urban communities within high-density Chinese cities. This study constructed a comprehensive urban community resilience assessment system (UCRA) that covers four dimensions: environmental, service, social, and governance resilience. In a case study of the Chinese megacity of Tianjin, urban communities were categorized into three physical types and three regional categories. The UCRA contained 40 detailed indicators, and the weighting of indicators was was determined using a mixed approach combining the AHP and entropy methods. The findings revealed that tower apartments in urban Chinese communities demonstrated relatively high resilience, whereas older residential complexes exhibited the lowest resilience performance. Furthermore, central urban communities generally displayed high resilience, in contrast to peripheral urban areas, where low levels of resilience were often discovered. Building upon these findings, this study discusses the characteristics and challenges associated with the resilience of various community types. By establishing a theoretical basis for creating intelligent assessment and monitoring systems, we advocate for targeted community development strategies, thereby promoting smart transformation of community resilience. Full article

To address urban flooding challenges exacerbated by climate change and urbanization, this study develops an integrated assessment framework combining the analytic hierarchy process (AHP), entropy weight method, and cloud model to quantify urban flood resilience. Resilience is deconstructed into resistance, adaptability, and recovery and evaluated through 24 indicators spanning water resources, socio-economic systems, and ecological systems. Subjective (AHP) and objective (entropy) weights are optimized via minimum information entropy, with the cloud model enabling qualitative–quantitative resilience mapping. Analyzing 2014–2024 data from 27 Chinese sponge city pilots, the results show resilience improved from “poor to average” to “good to average”, with a 2.89% annual growth rate. Megacities like Beijing and Shanghai excel in resistance and recovery due to infrastructure and economic strengths, while cities like Sanya enhance resilience via ecological restoration. Key drivers include water allocation (27.38%), economic system (18.41%), and social system (17.94%), with critical indicators being population density, secondary industry GDP ratio, and sewage treatment rate. Recommendations emphasize upgrading rainwater storage, intelligent monitoring networks, and resilience-oriented planning. The model offers a scientific foundation for urban disaster risk management, supporting sustainable development. This approach enables systematic improvements in adaptive capacity and recovery potential, providing actionable insights for global flood-resilient urban planning. Full article

Accelerated urbanization and intensified urban development globally lead to increased sewage discharge, challenging environmental protection. Therefore, exploring the correlation mechanism between the economic development level (EDL) and sewage discharge intensity (SDI) is crucial for sustainable development. This study uses panel data from 288 Chinese cities between 2003 and 2021, employs spatial analysis techniques to uncover the spatiotemporal evolution characteristics of SDI, and investigates the influence of economic development on this intensity using spatial panel models. The results reveal that (1) while the spatial distribution of SDI in China generally exhibits a downward trend, changes in the Northeast region are relatively modest, with SDI remaining higher than in other regions. Global autocorrelation analysis further indicates significant spatial agglomeration and positive correlation effects in urban SDI. (2) Economic development exerts a notable inhibitory effect on SDI, with a 0.570% decrease for every 1% rise in GDP per capita, thus demonstrating a significant spatial spillover effect. (3) For megacities, large cities, and small and medium-sized cities, EDLs have significant negative spatial spillover effects on SDI, with a more pronounced impact on large cities. This study provides a theoretical foundation for sewage management and empirical support for environmental policies, crucial for sustainable urban development. Full article

Rapid urbanization and escalating disaster risks necessitate resilient urban governance systems. Smart city initiatives that leverage digital technologies—such as the internet of things (IoT), big data analytics, and artificial intelligence (AI)—demonstrate transformative potential in enhancing emergency management capabilities. However, empirical evidence regarding their causal impact and underlying mechanisms remains limited, particularly in developing economies. Drawing on panel data from 275 Chinese prefecture-level cities over the period 2006–2021 and using China’s smart city pilot policy as a quasi-natural experiment, this study applies a multi-period difference-in-differences (DID) approach to rigorously assess the effects of smart city construction on emergency management capabilities. Results reveal that smart city construction produced a statistically significant improvement in emergency management capabilities, which remained robust after conducting multiple sensitivity checks and controlling for potential confounding policies. The benefits exhibit notable heterogeneity: emergency management capability improvements are most pronounced in central China and in cities at the extremes of population size—megacities (>10 million residents) and small cities (<1 million residents)—while effects remain marginal in medium-sized and eastern cities. Crucially, mechanism analysis reveals that digital technology application fully mediates 86.7% of the total effect, whereas factor allocation efficiency exerts only a direct, non-mediating influence. These findings suggest that smart cities primarily enhance emergency management capabilities through digital enablers, with effectiveness contingent upon regional infrastructure development and urban scale. Policy priorities should therefore emphasize investments in digital infrastructure, interagency data integration, and targeted capacity-building strategies tailored to central and western regions as well as smaller cities. Full article

Long-term source apportionment of PM_2.5 during high-pollution periods is essential for achieving sustained reductions in both PM_2.5 levels and their health impacts. This study conducted PM_2.5 sampling in Shenzhen from January to March over the years 2021–2024 to investigate the long-term impact of coronavirus disease 2019 and the short-term impact of the Spring Festival on PM_2.5 levels. The measured average PM_2.5 concentration during the research period was 22.5 μg/m³, with organic matter (OM) being the dominant component. Vehicle emissions, secondary sulfate, secondary nitrate, and secondary organic aerosol were identified by receptor model as the primary sources of PM_2.5 during the observational periods. The pandemic led to a decrease of between 30% and 50% in the contributions of most anthropogenic sources in 2022 compared to 2021, followed by a rebound. PM_2.5 levels in January–March 2024 dropped by 1.4 μg/m³ compared to 2021, mainly due to reduced vehicle emissions, secondary sulfate, fugitive dust, biomass burning, and industrial emissions, reflecting Shenzhen’s and nearby cities’ effective control measures. However, secondary nitrate and fireworks-related emissions rose significantly. During the Spring Festival, PM_2.5 concentrations were 23% lower than before the festival, but the contributions of fireworks burning exhibited a marked increase in both 2023 and 2024. Specifically, during intense peak events, fireworks burning triggered sharp, short-term spikes in characteristic metal concentrations, accounting for over 50% of PM_2.5 on those peak days. In the future, strict control over vehicle emissions and enhanced management of fireworks burning during special periods like the Spring Festival are necessary to reduce PM_2.5 concentration and improve air quality. Full article

Urbanization is accompanied by an increased use of building materials. However, the lack of high-resolution building material stock (BMS) maps limits our understanding of the relationship between BMS and urban heat. To address this, we estimated BMS across eight typical Chinese megacities using multi-source geographic data and investigated the relationship between BMS and land surface temperature (LST). The results showed that (1) the total BMS for the eight megacities was 9175.07 Mt, with Beijing and Shanghai having the largest shares. While BMS correlated significantly with population, growth patterns varied across cities. (2) Spatial autocorrelation between BMS and LST was evident. Around 16% of urban areas exhibited High–High clustering between BMS and LST, decreasing to 10% during the daytime. The relationship between BMS and LST is nonlinear, and also prominent at night, especially in Beijing. (3) Diverse building forms, especially building height, contribute to a nonlinear relationship between BMS and LST. Full article

Although China has achieved substantial reductions in particulate matter pollution, continually rising ground-level ozone now constitutes the primary challenge to further air-quality improvements. A systematic assessment of the long-term spatiotemporal behavior of ozone (O₃) and its links to meteorology and emissions is still lacking. Here, we develop a novel framework that couples Kolmogorov–Zurbenko (KZ) filtering with an optimized random forest (RF) regression model to examine daily maximum 8 h average ozone (O₃-8h) in 372 Chinese cities from 2013 to 2023. The approach quantitatively disentangles meteorological and emission contributions at the national scale, overcoming the limitations of traditional linear methods in capturing non-linear processes. Long-term components explain, in general, <40% of total O₃ variance. In eastern urban agglomerations, long-term meteorological factors—particularly temperature and surface ultraviolet radiation—account for up to 80% of the trend, whereas long-term emission contributions remain modest (≈5–6%), with pronounced signals in the Beijing–Tianjin–Hebei and Fenwei Plain regions. Empirical orthogonal function analysis further reveals distinct spatial patterns of emission influence: long-term O₃ trends in mega-cities such as Beijing, Tianjin, and Shanghai are driven mainly by local emissions (1.5–3% contribution), while key transport hubs including Xi’an, Tangshan, and Langfang are markedly affected by traffic-related emissions (>2%). These findings clarify the heterogeneous mechanisms governing O₃ formation across China and provide a scientific basis for designing and implementing the next phase of region-specific, joint prevention-and-control policies. Full article

This study investigates the annual carbon emission disparities between privately-owned electric vehicles (EVs) and internal combustion engine vehicles (ICEVs) by developing a usage-phase life cycle assessment (LCA) model, with a focus on the synergistic impacts of grid carbon intensity, driving intensity (e.g., annual mileage), and vehicle energy efficiency. Through scenario analyses and empirical case studies in four Chinese megacities, three key findings are obtained: (1) Grid carbon intensity is the primary factor affecting the emission advantages of EVs. EVs demonstrate significant carbon reduction benefits in regions with low-carbon power grids, even when the annual mileage is doubled. However, in coal-dependent grids under intensive usage scenarios, high-energy-consuming EVs may experience emission reversals, where their emissions exceed those of ICEVs. (2) Higher annual mileage among EV owners (1.5–2 times that of ICEV owners) accelerates carbon accumulation, particularly diminishing per-kilometer emission advantages in regions where electricity grids are heavily reliant on fossil fuels. (3) Vehicle energy efficiency heterogeneity plays a critical role: compact, low-energy EVs (e.g., A0-class sedans/SUVs) maintain emission advantages across all scenarios, while high-energy models (e.g., C-class sedans/SUVs) may exceed ICEV emissions even in regions with low-carbon power grids under specific conditions. The study proposes a differentiated policy framework that emphasizes the synergistic optimization of grid decarbonization, vehicle-class-specific management, and user behavior guidance to maximize the carbon reduction potential of EVs. These insights provide a scientific foundation for refining EV adoption strategies and achieving sustainable transportation transitions. Full article

Background: Both distance to the hospital and hospital reputation influence patient choice of hospital; but the combined effect of these factors and how they relate to hospitalization outcomes has yet to be determined. The purpose of this study was to assess the combined influence of distance to hospital and hospital reputation on the hospitalization outcomes in patients with stroke. Methods: This retrospective observational study utilized data from 69,107 stroke patients hospitalized in southern Chinese megacity between 2019 and 2021. A generalized linear model was used to assess the association between hospital reputation, distance to the hospital, hospitalization costs, and the length of stay. Multivariate logistic regression was used to estimate the combined effect on in-hospital mortality. Results: Compared with patients who chose hospitals without a good reputation and close to home, those who chose hospitals with a good reputation had lower hospitalization costs (−0.05; 95% CI: −0.08 to −0.02), a shorter length of stay (−0.18; 95% CI: −0.20 to −0.16), and lower in-hospital mortality (0.52; 95% CI: 0.40 to 0.67). However, patients who chose hospitals with a good reputation but farther distance experienced higher hospitalization costs (0.20; 95% CI: 0.17 to 0.23). Conclusions: A shorter distance to the hospital and a higher reputation of the hospital are associated with lower costs and better outcomes. Our study indicates that improving outcomes for patients with stroke requires equitable distribution of quality medical resources. Full article

With the acceleration of urbanization, urban regeneration has become a critical strategy for megacities to address spatial fragmentation and inefficient resource allocation. However, the mismatch between transportation nodes and land development potential remains a key barrier to sustainable urban renewal. This research takes the urban renewal areas in Changsha as a typical case. Based on the “Node–Place–Value” (NPV) model, a multi-dimensional evaluation system was constructed. Through multiple empirical analysis methods such as spatial data analysis, field research, and economic indicator evaluation, this study deeply explores how this evaluation system provides a theoretical and data basis for detailed planning and further provides guidance for meeting the needs of urban renewal. Through the empirical analysis of the urban renewal areas in Changsha, this study quantifies the matching relationship among transportation nodes, land use, and economic value and reveals the current imbalance issues of these elements in the areas. For example, there is a common mismatch between the functions of transportation nodes and the potential of land development. Specifically, the land use in transportation hub areas fails to fully utilize their transportation advantages, resulting in the waste of transportation resources and low economic benefits. The results reveal significant imbalances in the following areas: Transportation–Land Mismatch: High-accessibility areas (e.g., Martyrs’ Park and Railway Station ) exhibit underdeveloped land use and low economic conversion efficiency. Peripheral Lag: Remote areas (e.g., Wang Xin and Sunshine 100 ) lack both transportation infrastructure and land development potential, leading to resource waste. Value Dimension Impact: The added “value” dimension highlights thatareas with cultural assets (e.g., Martyrs’ Park) achieve higher comprehensive scores despite spatial constraints. The findings of this study not only provide a scientific basis for urban renewal in Changsha but also offer crucial theoretical support and practical references for other megacities in China to address similar issues and achieve sustainable development. Full article

This study examines the mediating effect of subjective housing quality between housing conditions and mental health, using survey data from ten Chinese mega-cities. The results from multi-level linear regression models show that housing areas are highly associated with subjective housing quality and that renters have lower levels of subjective housing quality than homeowners. At the community level, the age of housing tends to diminish its subjective quality, while a lower plot ratio is associated with more favorable evaluations of housing conditions. Surprisingly, educational resources in proximity to housing are negatively associated with subjective housing quality. Subjective housing quality is closely linked to mental health. Additionally, the results show that home ownership significantly strengthens the association between subjective housing quality and mental health. Namely, the mediating effect of subjective housing quality on the relationship between housing conditions and mental health is stronger for homeowners than for renters. Full article

Accelerated urbanization in China poses significant challenges for developing urban planning strategies that are responsive to diverse climatic conditions. This demands a sophisticated understanding of the complex interactions between 3D urban forms and local climate dynamics. This study employed the Conditional Generative Adversarial Network (cGAN) of the Pix2Pix algorithm as a predictive model to simulate 3D urban morphologies aligned with Local Climate Zone (LCZ) classifications. The research framework comprises four key components: (1) acquisition of LCZ maps and urban form samples from selected Chinese megacities for training, utilizing datasets such as the World Cover database, RiverMap’s building outlines, and integrated satellite data from Landsat 8, Sentinel-1, and Sentinel-2; (2) evaluation of the Pix2Pix algorithm’s performance in simulating urban environments; (3) generation of 3D urban models to demonstrate the model’s capability for automated urban morphology construction, with specific potential for examining urban heat island effects; (4) examination of the model’s adaptability in urban planning contexts in projecting urban morphological transformations. By integrating urban morphological inputs from eight representative Chinese metropolises, the model’s efficacy was assessed both qualitatively and quantitatively, achieving an RMSE of 0.187, an R² of 0.78, and a PSNR of 14.592. In a generalized test of urban morphology prediction through LCZ classification, exemplified by the case of Zhuhai, results indicated the model’s effectiveness in categorizing LCZ types. In conclusion, the integration of urban morphological data from eight representative Chinese metropolises further confirmed the model’s potential in climate-adaptive urban planning. The findings of this study underscore the potential of generative algorithms based on LCZ types in accurately forecasting urban morphological development, thereby making significant contributions to sustainable and climate-responsive urban planning. Full article

This study enhances our understanding of urban park accessibility and social equity through a novel methodological framework in Chengdu, China. By improving the three-step floating catchment area (3SFCA) method with space syntax metrics and multi-modal transportation analysis, we identify spatial disparities in green space access. Our methodology, validated with Baidu heat map data, demonstrates improved accuracy in estimating population demand patterns. Key findings include: (1) The enhanced 3SFCA method outperforms traditional approaches in predicting park accessibility, providing reliable evidence for urban planning; (2) significant accessibility disparities exist across transportation modes, particularly affecting non-motorized transport users; (3) newly developed areas show greater park access inequities than established neighborhoods; (4) important mismatches exist between park accessibility and vulnerable population distributions. This research provides targeted recommendations for reducing spatial inequities and improving green space access for all residents, particularly benefiting children and elderly populations in rapidly urbanizing contexts. Full article

The development of park cities is an important exploration for better satisfying people’s aspirations for a better life, promoting sustainable social development, and advancing the transformation of green ecological values. As a basic industry for sustainable development, the combination of agriculture and urban development is an important way to build an ecological civilization. Clarifying the relationship between a park city and green development of agriculture is of great significance to the construction of a green base and ecological system of the city, sustainable development of agriculture, and integrated development of urban and rural areas. Chengdu is a mega-city in western China, and the Chengdu-led park city development program is unique in Chinese urban development. Chengdu’s park city development is a pioneering example of urban ecological civilization construction. Taking Chengdu as an example and combining the data of other prefecture-level cities in Sichuan, this study explored the correlation and interaction between agricultural green development (AGD) and park city development (PCD) in Chengdu and other prefecture-level cities in Sichuan from 2011 to 2022 based on the coupling coordination degree, gray correlation degree, and spatial autocorrelation analysis. The results showed the following: (1) Based on the entropy method, the level of AGD in Chengdu rises from 0.353 in 2011 to 0.537 in 2022, and the level of PCD rises from 0.368 to 0.826. The level of AGD and the level of PCD as a whole show an upward trend. (2) The degree of coupling and coordination between the PCD and AGD levels rises from 0.600 to 0.816, realizing the leap from coordination to good coordination, and the degree of coupling has been at a high level. (3) Based on the grey correlation degree, in the process of the influence of AGD on the PCD, the correlation degree of the influencing factors of each indicator is basically above 0.5, and each influencing factor has a strong contribution to the level of the PCD. (4) Spatial self-analysis shows that the coupling coordination degree of AGD and PCD in a region is affected by the neighboring region. Therefore, we believe that AGD plays a more obvious role in driving and radiating PCD and that it can effectively promote the economic, social, and ecological upgrading in the process of PCD. Full article

Chinese rural elderly care services face challenges such as low levels of pensions and social security, as well as high proportions of the elderly living alone and those who are incapacitated and lack assistance. The rural elderly surrounding megacities have been more significantly impacted by urbanization (with relatives moving away to the megacities for jobs) than in other areas, so the well-being of this particular group deserves even more attention. However, existing major studies in China are mainly limited to those in need in specific regions, and there is little research on the well-being of special age groups. To fill the research gap, this study constructs an indicator system for the well-being assessment with five dimensions and explores the well-being of the rural elderly surrounding Xi’an and its obstacles using questionnaire data. The results indicate that (1) the well-being index of the rural elderly surrounding Xi’an in each dimension, in descending order, are medical health, spiritual fulfillment (the pursuit of the spiritual world of the elderly and their desire for a better life), quality of life, social relationships, and economic income status; (2) the comprehensive well-being of the rural elderly varies considerably in the northern counties and districts of Xi’an, and is relatively low in the south; and (3) spiritual fulfillment and medical health are the main obstacles to the improvement of well-being of the rural elderly surrounding Xi’an. Based on these findings, corresponding policy implications are proposed on the five dimensions of well-being, such as improving the rural social old-age insurance and medical insurance systems, providing old-age support for the families of the rural elderly, establishing a model of village old-age care, and promoting the rural habitation renovation, to provide guarantees for the improvement of the well-being of the rural elderly surrounding megacities. Full article